Using Mass Spectrometry for Drug Metabolism Studies

USING MASS SPECTROMETRY FOR DRUG METABOLISM STUDIES

EDITED BY

Walter A. Korfmacher

CRC PR E S S Boca Raton London New York Washington, D.C. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-FM.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:29pm Page: 4/12

Library of Congress Cataloging-in-Publication Data Using mass spectrometry for drug metabolism studies/edited by Walter A. Korfmacher. p. cm. Includes bibliographical references and index. ISBN 0-8493-1963-3 (alk. paper) 1. Drugs–Metabolism. 2. Drugs–Spectra. 3. Mass spectrometry. [DNLM: 1. Pharmaceutical Preparations–metabolism. 2. Drug Design. 3. Drug Evaluation, Preclinical–methods. 4. Spectrum Analysis, Mass–methods. QV 38 U85 2004] I. Korfmacher, Walter A. II. Title. RM301. U85 2004 6150 .7–dc22

2004050306

This book contains information obtained from authentic and highly regarded sources. Reprinted material is quoted with permission, and sources are indicated. A wide variety of references are listed. Reasonable efforts have been made to publish reliable data and information, but the author and the publisher cannot assume responsibility for the validity of all materials or for the consequences of their use. Neither this book nor any part may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, microfilming, and recording, or by any information storage or retrieval system, without prior permission in writing from the publisher. All rights reserved. Authorization to photocopy items for internal or personal use, or the personal or internal use of specific clients, may be granted by CRC Press, provided that $1.50 per page photocopied is paid directly to Copyright Clearance Center, 222 Rosewood Drive, Danvers, MA 01923 USA. The fee code for users of the Transactional Reporting Service is ISBN 0-8493-1963-3/04/$0.00+$1.50. The fee is subject to change without notice. For organizations that have granted a photocopy license by the CCC, a separate system of payment has been arranged. The consent of CRC Press does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific permission must be obtained in writing from CRC Press for such copying. Direct all inquiries to CRC Press, 2000 N.W. Corporate Blvd., Boca Raton, Florida 33431. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation, without intent to infringe.

Visit the CRC Press Web site at www.crcpress.com ß 2005 by CRC Press No claim to original U.S. Government works International Standard Book Number 0-8493-1963-3 Library of Congress Card Number 2004050306 Printed in the United States of America 1 2 3 4 5 6 7 8 9 0 Printed on acid-free paper

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-FM.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:29pm Page: 5/12

Preface

The impetus for this book came from a combination of factors, but can be summarized by the statement that we live in exciting times. It is an exciting time to be a drug metabolism specialist involved in drug discovery efforts and it is an exciting time for mass spectrometry. I feel fortunate to have been able to live during these times and I look forward to what the future holds in store for all of us. This book was designed to be a resource book for professionals in both mass spectrometry and drug metabolism areas, but will also be helpful to medicinal chemists interested in learning more about drug metabolism issues in new drug discovery. The chapters were written so that scientists in these fields could benefit from the state-of-the-art expertise and knowledge that is contained in each chapter and the references cited by each chapter’s author. While each chapter was written so that it could be read separately from the other chapters, I have inserted notes into most of the chapters referring to another chapter for more information on a given topic. The book has chapters on general topics as well as specific areas of interest. There are also specific chapters devoted to newer technology that has more recently been introduced and appears to have great potential. I would like to thank all of the authors of these chapters for their efforts and attention to detail that have allowed this book to become a reality. I also thank ScheringPlough Research Institute management for their support of this effort. Finally, I would like to thank my family for their continuing support, especially Madeleine, my wife. Walter A. Korfmacher February 14, 2004

v

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-FM.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:29pm Page: 7/12

Editor

Walter A. Korfmacher, Ph.D. Dr. Korfmacher is a director of exploratory drug metabolism at ScheringPlough Research Institute in Kenilworth, New Jersey. He received his B.S. in chemistry degree from St. Louis University in 1973. He then went on to obtain his M.S. in chemistry in 1975, and Ph.D. in chemistry in 1978, both from the University of Illinois in Urbana. In 1978, he joined the FDA and was employed at the National Center for Toxicological Research (NCTR) in Jefferson, Arkansas. While at the NCTR, he also held adjunct associate professor positions at the College of Pharmacy in the University of Tennessee (Memphis) and the Department of Toxicology in the University of Arkansas for Medical Sciences (Little Rock). After 13 years at the NCTR, Dr. Korfmacher joined Schering-Plough Research Institute as a principal scientist in October, 1991. He is currently a Director and the leader for a group of fifteen scientists. His research interests include the application of mass spectrometry to the analysis of various sample types, particularly metabolite identification and trace organic quantitative methodology. His most recent applications are in the use of HPLC combined with atmospheric pressure ionization mass spectrometry and tandem mass spectrometry for both metabolite identification as well as nanogram/ml quantitative assay development for various pharmaceutical molecules in plasma. He is also a leader in the field of developing strategies for the application of new MS techniques for drug metabolism participation in new drug discovery and is frequently invited to speak at scientific conferences. In 1999–2000, Dr. Korfmacher was the chairperson of the North Jersey Mass Spectrometry Discussion Group and in 2002, Dr. Korfmacher received the New Jersey Regional Award for Achievements in Mass Spectrometry. Dr. Korfmacher has over 100 publications in the scientific literature and has made over 75 presentations at various scientific forums. vii

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-FM.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:29pm Page: 9/12

Contributors

University of Geneva Geneva, Switzerland

Bradley L. Ackermann, Ph.D. Senior Research Scientist Drug Disposition Eli Lilly and Company Indianapolis, Indiana

Yunsheng Hsieh, Ph.D. Principal Scientist Exploratory Drug Metabolism Department of Drug Metabolism and Pharmacokinetics Schering-Plough Research Institute Kenilworth, New Jersey

Richard M. Caprioli, Ph.D. Professor of Biochemistry and Director Mass Spectrometry Research Center Department of Biochemistry Vanderbilt University Nashville, Tennessee

Daniel B. Kassel, Ph.D. Senior Director Analytical Discovery & Development Syrrx, Inc. San Diego, California

Kathleen Cox, Ph.D. Associate Director Exploratory Drug Metabolism Department of Drug Metabolism and Pharmacokinetics Schering-Plough Research Institute Kenilworth, New Jersey

Walter A. Korfmacher, Ph.D. Director Exploratory Drug Metabolism Department of Drug Metabolism and Pharmacokinetics Schering-Plough Research Institute Kenilworth, New Jersey

Jean-Marie Dethy, MSc. Senior Scientist Department of Toxicology and Drug Metabolism Lilly Development Center Mont-Saint-Guibert, Belgium

Hong Mei, Ph.D. Associate Principal Scientist Exploratory Drug Metabolism Department of Drug Metabolism and Pharmacokinetics

Ge´rard Hopfgartner, Ph.D. Professor School of Pharmacy ix

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-FM.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:29pm Page: 10/12

x

Schering-Plough Research Institute Kenilworth, New Jersey Michelle L. Reyzer, Ph.D. Research Fellow Department of Biochemistry Vanderbilt University Nashville, Tennessee Thomas N. Thompson, Ph.D. Consultant 12328 Noland Overland Park, Kansas Sam Wainhaus, Ph.D. Associate Principal Scientist Exploratory Drug Metabolism

Copyright © 2005 CRC Press, LLC

Contributors

Department of Drug Metabolism and Pharmacokinetics Schering-Plough Research Institute Kenilworth, New Jersey Xiaoying Xu, Ph.D. Associate Principal Scientist Exploratory Drug Metabolism Department of Drug Metabolism and Pharmacokinetics Schering-Plough Research Institute Kenilworth, New Jersey Manfred Zell Senior Scientist F. Hoffmann-La Roche, Ltd. Basel, Switzerland

File: {Books}4354-Korfmacher/Revises-II/4354-FM.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:29pm Page: 11/12

Contents

Chapter 1

Bioanalytical Assays in a Drug Discovery Environment Walter A. Korfmacher, Ph.D.

Chapter 2

Drug Metabolism In Vitro and In Vivo Results: How do these Data Support Drug Discovery? Thomas N. Thompson, Ph.D.

35

High Throughput Strategies for In Vitro ADME Assays: How Fast Can We Go? Daniel B. Kassel, Ph.D.

83

Chapter 3

1

Chapter 4

Matrix Effects: Causes and Solutions Hong Mei, Ph.D.

103

Chapter 5

Direct Plasma Analysis Systems Yunsheng Hsieh, Ph.D.

151

Chapter 6

Acyl Glucuronides: Assays and Issues Sam Wainhaus, Ph.D.

175

Chapter 7

Utilizing Higher Mass Resolution in Quantitative Assays Xiaoying Xu, Ph.D.

203

Chapter 8

Special Requirements for Metabolite Characterization Kathleen Cox, Ph.D.

229

Chapter 9

APPI: A New Ionization Source for LC and MS/MS Assays Yunsheng Hsieh, Ph.D.

xi

Copyright © 2005 CRC Press, LLC

253

File: {Books}4354-Korfmacher/Revises-II/4354-FM.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:29pm Page: 12/12

Contents

xii

Chapter 10

Q Trap MS: A New Tool for Metabolite Identification Ge´rard Hopfgartner, Ph.D. and Manfred Zell

Chapter 11

MS Imaging: New Technology Provides New Opportunities Michelle L. Reyzer, Ph.D. and Richard M. Caprioli, Ph.D.

305

Understanding the Role and Potential of Infusion Nanoelectrospray Ionization for Pharmaceutical Bioanalysis Bradley L. Ackermann, Ph.D. and Jean-Marie Dethy, MSc.

329

Chapter 12

Copyright © 2005 CRC Press, LLC

277

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 1/34

Chapter 1 Bioanalytical Assays in a Drug Discovery Environment Walter A. Korfmacher

1.1

Introduction

The challenge of working in the pharmaceutical industry during this time of rapid expansion of our knowledge of the causes and potential cures for many diseases is both exciting and formidable. It is exciting because we are now learning how to make potent drugs that can target specific receptors in order to relieve symptoms or block the progression of a disease. It is formidable because the number of potential targets is large and the size of our chemical libraries that need to be screened against these targets is in the millions and growing even larger. While ultra-high throughput screening effectively reduces these numbers by screening out the inactive compounds, the numbers of compounds that need to be screened through drug metabolism studies can still be overwhelming. As shown in Figure 1.1, the amount of effort in terms of compound screening, lead optimization and attrition is a daunting task. Of the two million compounds that might be screened for activity, perhaps 10,000 are selected and optimized in the drug discovery stage. Next, 20 compounds might be selected for development and five of these may survive the toxicity testing and be suitable for phase I clinical screening. At current rates of success, one of the five compounds would become an approved drug. In a 2003 report by the 0-8493-1963-3/05/$0.00+$1.50 ß 2005 by CRC Press

Copyright © 2005 CRC Press, LLC

1

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 2/34

Using Mass Spectrometry for Drug Metabolism Studies

2

Figure 1.1 Schematic chart showing the compound attrition in drug discovery to development to drug approval. The X axis is the stage or point in the process. The Y axis is the number of compounds at that point.

Tufts Center for the Study of Drug Development, the cost of bringing a new drug to market was estimated to be $897 million [1]. By the time this book is published, the average cost may well be $1 billion or more. Over the last 12–15 years, mass spectrometry (MS) has played an increasingly important role in all phases of drug discovery and drug development. In that same time, mass spectrometry has undergone tremendous changes. Mass spectrometers have become more sensitive, easier to use and have been applied to multiple areas of drug metabolism activity. At the same time, new types of mass spectrometers have been introduced. Figure 1.2 shows four of the most widely used types of mass spectrometers; of these four types, the triple quadrupole mass spectrometer (QqQ MS) has become the ‘‘gold standard’’ for quantitative assays in the drug metabolism arena. The focus of this chapter will be on the use of liquid chromatography combined with tandem mass spectrometry (LC–MS/MS) for drug metabolism participation in new drug discovery, specifically in support of in vivo pharmacokinetic (PK) screens and studies.

1.2

Review of Recent Literature

While medicinal chemists will continue to search for in silico programs and in vitro (for more details on in vitro assays, see Chapter 3) techniques to predict animal and human pharmacokinetics [2–12], the need to obtain experimental PK data from laboratory animals early in the discovery paradigm is still paramount [4, 13–15] (for more details on how to use PK data, see Chapter 2). Several review articles have been published in the last few years on the use of mass spectrometry when assaying samples from in vivo PK studies in support of Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 3/34

Bioanalytical Assays in a Drug Discovery Environment

3

Figure 1.2 Four types of mass spectrometer that are used for various drug metabolism assays. Figure provided by Jerry Pappas and used with the permission of Thermo-Finnigan Instruments.

new drug discovery and development [15–28]. Therefore, this review will cover, primarily, recent publications dealing with the use of LC–MS/MS for the analysis of PK samples in a drug discovery environment. While there will be some overlap with other chapters in this book, many citations of interest that are not included here will be found in the other chapters. One important theme that can be found in multiple citations is the need for speed when working in a discovery setting. This is important because, in a drug discovery setting, the goal is to learn as much as possible about many compounds of interest in a short time. Thus, a fast turnaround time from sample receipt to the PK report provides one important set of information about the potential lead drug—often producing ‘‘go/no go’’ feedback to chemists. For this reason, much of the recent literature discusses how best to speed up the LC–MS/MS assay. For example, Shou et al. [29], discuss the use of packed silica columns to provide rapid analysis of polar analytes. They have found that silica columns can be operated at 4 mL/min or more, which can turn a 4-min runtime into a 30-s runtime. As shown in Figure 1.3, an assay for midazolam and its two hydroxy metabolites is completed in 30 s. As shown in Figure 1.4, the authors also demonstrated that this new, ultrafast assay provided data equivalent to the standard, high-performance liquid chromatography–tandem mass spectrometry (HPLC–MS/MS) assay, which was performed at a flow rate of 0.6 mL/min. Chromatography is an important part of the LC–MS/MS system [30–33]. Romanyshyn et al. [34] compare the advantages of ultrafast gradients (also Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 4/34

4

Using Mass Spectrometry for Drug Metabolism Studies

Figure 1.3 LC–MS/MS chromatograms showing a high-speed assay with a 0.5-min duration for midazolam and its two hydroxy metabolites. Source: Shou et al. [29]. With permission.

called ballistic gradients) with fast isocratic chromatographic systems. They conclude that the gradient systems provide better chromatographic separation of the analyte and its metabolites with much less development time needed. They discuss the potential for glucuronide metabolites to interfere with the analysis of the dosed compound, therefore, they stress the need for good chromatography even when high-speed assays are being developed. For Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 5/34

Bioanalytical Assays in a Drug Discovery Environment

5

Figure 1.4 Comparison of the PK (concentration vs time after dose) data obtained using the standard (0.6 mL/min) HPLC conditions (solid line) or the high speed (4.5 mL/min) HPLC conditions (dotted line). Source: Shou et al. [29]. With permission.

example, as shown in Figure 1.5, in less than 2 min, they have complete chromatographic separation of the dosed compound and two of its glucuronide metabolites [34]. Naidong et al. [35] discuss the importance of selecting the right injection solvent when developing LC–MS/MS methods. Zhao et al. [36] described the importance of selecting the proper mobile phase buffer when setting up an LC–MS/MS assay. In an article by Tiller and Romanyshyn [37], the authors compare ultrafast gradients with fast isocratic gradients in terms of avoiding matrix effects. While they concluded that both systems have trouble with very dirty samples, such as rat bile or urine, they stated that ultrafast gradients were better at keeping the column clean, due to the mobile phase gradient. They also pointed out the importance of using a divert valve after the HPLC column to send the first portion of the chromatographic eluant (typically 20% of the gradient time) to waste instead of going into the MS source. In another article by Hsieh et al. [38], the authors describe the use of a fast gradient in combination with MS/MS for the analysis of drug discovery PK samples. In this report, the authors use the postcolumn infusion system to test for the extent of the matrix effect (see MillerStein et al. [39] and King et al. [40] for a discussion of post-column infusion techniques). The authors reported that while matrix effects were observed in both fast gradients and standard gradients, if properly understood, either technique could be used for discovery PK assays. As shown in Figure 1.6, while the assay time was reduced from 4 min to 1 min, good chromatographic peak shapes for both the analyte and internal standard were maintained [38]. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 6/34

6

Using Mass Spectrometry for Drug Metabolism Studies

Figure 1.5 LC–MS/MS chromatogram showing a fast assay (less than 2 min) where complete chromatographic separation of the parent (dosed) compound and two of its glucuronide metabolites (potential interferences in this assay) was achieved. Source: Romanyshyn et al. [34]. With permission.

Figure 1.6 LC–MS/MS chromatograms showing the use of a high-speed gradient; the upper trace shows the standard assay for an analyte and its internal standard (IS) with a 4-min run time, while the lower trace shows the fast assay with a minibore column for the same two compounds with a 1-min run time. While the assay time was reduced from 4 min to 1 min, good chromatographic peak shapes for both the analyte and internal standard were maintained in the higher speed assay. Source: Hsieh et al. [38]. With permission.

The authors also reported that while atmospheric pressure chemical ionization (APCI) was less affected by matrix effects, electrospray ionization (ESI) could also be utilized as long as one was careful to ensure that the analyte and internal standard eluted in the matrix ion suppression-free region of the Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 7/34

Bioanalytical Assays in a Drug Discovery Environment

7

Figure 1.7 Comparison of the PK (concentration vs time after dose) data obtained using the standard HPLC conditions or the high speed gradient (minibore) conditions shown in Figure 1.6. The assay was performed in each case with an APCI source and an ESI source. For the data set labeled A, the samples were from a monkey PK study dosed using a 20% hydroxypropylbetacyclodextrin (HPBCD) formulation. For the data set labeled B, the samples were from a monkey PK study dosed with the same compound but with a 0.4% methylcellulose (MC) formulation. Source: Hsieh et al. [38]. With permission.

chromatogram (see Chapter 4 for more information on this topic). As a final test that either ESI or APCI could be used in the fast gradient mode, results were compared from a monkey i.v./p.o. PK study for a discovery compound when the samples were assayed by a standard gradient and a fast gradient (with a minibore column) using either APCI or ESI. As shown in Figure 1.7, this four-way comparison resulted in very similar data being produced by each assay methodology. Another approach for speeding assay throughput has been the use of parallel HPLC columns feeding into one MS/MS system [41–48]. For example, Jemal et al. [42] showed that by connecting two parallel HPLC systems with a ‘‘T’’, one could double the throughput of an assay simply by staggering the injection times of the samples. Their two-column system, as shown in Figure 1.8, was able to reduce the sample assay times from 5 min per sample to 2.5 min per sample, using this procedure [42]. This concept has been commercialized in the development of the Aria LX4Õ (Cohesive Technologies) system, which was described and tested by King et al. [43] In this system, four HPLC pumps, a specialty autosampler and various switching valves are all under the control of a single computer which has software to determine the timing of all the events so that a minimum amount of the MS acquisition time is needed for each sample that is injected. The result is an increase in sample throughput, while maintaining good chromatographic conditions for each sample. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 8/34

Using Mass Spectrometry for Drug Metabolism Studies

8

  !

  

 !!


  ! "


  


                       

"T

" 

"  

     

Figure 1.8 Schematic diagram showing a two-column LC–MS/MS system that can be used to double the sample throughput. Source: Jemal et al. [42]. With permission.

Another approach for increasing throughput has been to add additional ESI sprayers to the MS/MS system. Hiller et al. [44] described a dual ESI source that could be used for performing two separate assays at one time. As Hiller discusses, there were some disadvantages to this approach in that careful preselection of the analytes was needed so that the two assays did not interfere with each other. As described by Bayliss et al. [45], another commercial solution to the throughput issue was provided by the MUXÕ (Micromass, Inc.) interface. This interface allows one to attach four parallel HPLC columns to one triple quadrupole MS/MS system. Each column feeds an independent ESI sprayer; as shown in Figure 1.9, and each sprayer is sampled sequentially by a rotating interface device. Bayliss et al. [45] reported that ‘‘cross-talk’’ between sprayers was minimal and that one could assay 120 plasma samples per hour using four 50
1 mm columns. Deng et al. [46] showed an impressive use of the MUX system for high throughput assays. As shown in Figure 1.10, four parallel monolithic HPLC columns were hooked up to the MUX system using a four-injector autosampler [46]. The chromatographic run time for each column was 2 min per sample; since four samples were injected at once, that provided a sample throughput of 30 s per sample. In another report, Deng et al. [49] tested the utility of the MUX system for analyzing samples from a drug discovery PK study. They found equivalent results could be obtained whether the samples were assayed in the four-sprayer mode or the single-sprayer mode. In the four-sprayer mode, they reported inter-channel (between sprayers) ‘‘cross-talk’’ of less than 0.1%. The authors also reported a four-fold higher value for the lower limit of quantitation (LLOQ) on the four-sprayer MUX system than was obtained for the same compound on a standard single sprayer system. Several reports have described various studies looking at different chromatographic parameters in order to assess their effect on increasing Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 9/34

Bioanalytical Assays in a Drug Discovery Environment

9

Figure 1.9 Schematic diagram of the MUXÕ (Micromass, UK) ESI source design showing four ESI sprayers and an indexed sample rotor that allows ions from one sprayer at a time to enter the MS ion sampling region. Diagram provided by and used with the permission of Micromass, UK.

Figure 1.10 Schematic diagram showing a four-injector autosampler and four monolithic HPLC columns feeding a MUX ESI source to provide a four-fold increase in sample throughput. Source: Deng et al. [46]. With permission.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 10/34

10

Using Mass Spectrometry for Drug Metabolism Studies

sample throughput [19, 50, 51]. Murphy et al. [50] studied the effect that increasing the mobile phase flow rate had on analyte signal and assay cycle time; the authors reported that signal peak area and cycle were both reduced as the flow rate increased in a gradient system set to assay discovery PK samples after protein precipitation. The assays were performed on a triple quadrupole (QqQ) MS/MS system operated in the ESI mode. The authors attributed the reduction in signal to the concentration-dependent nature of the ESI source because the peak widths were kept constant, therefore the analyte concentration was reduced as the flow rate was increased. The authors also noted that protein precipitation was their sample preparation method of choice for drug discovery PK samples. In addition, they stated that they use methanol instead of acetonitrile in the mobile phase because methanol tends to provide an enhanced signal as compared to acetonitrile. Jemal [19] and Jemal and Hawthorne [52] have also stated that methanol in the mobile phase can provide significant signal enhancement in the positive ESI mode as compared to acetonitrile in the mobile phase. Under negative ESI conditions, Jemal [19] reported no response difference when using either methanol or acetonitrile in the mobile phase. In a recent presentation by Seliniotakis et al. [53], the authors reported that mixing methanol 1:1 with the HPLC effluent and then splitting the flow 1:1 improved the MS signal in test samples. New chromatographic column types have also gained attention as possible ways to enhance sample throughput in LC–MS/MS assays. Several authors have described the potential advantages of the monolithic HPLC columns [54– 61]. In general, monolithic columns offer the possibility of using mobile phases at very high flow rates (5–10 mL/min), which can produce very fast assays. For example, Wu et al. [54] describe the utility of using a monolithic column as part of an LC–MS/MS system in a drug discovery environment. In their report, they used 96-well plate solid phase extraction (SPE) for sample preparation. The authors noted that good chromatographic separation is still important, in order to separate the analyte from endogenous matrix components as well as for the need to provide separation from potential metabolites. They also noted that ESI is primarily a concentration-dependent detector, therefore good peak shape is also an important factor for a successful assay. For their evaluation of the monolithic column, they used a mixture of three analytes and one internal standard; the chromatography was a gradient system and positive ESI was the ionization mode. As shown in Figure 1.11, the authors demonstrated that good separation and peak shape were maintained while changing the flow rate from 1 mL/min to 6 mL/min for the same mixture of four compounds. At a flow rate of 6 mL/min, the eluant was split so that 0.4 mL/min entered the MS source. The authors found that the peak area dropped significantly as the flow rate increased, but the absolute ion abundance (peak height) decreased by only a factor of 2. The authors also reported that the signal–noise ratio (S/N) was unaffected by the increase in flow rate. Finally, by testing a sample with two known metabolites, the authors were able to demonstrate that the monolithic columns still demonstrated good separation power even at a flow rate of Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 11/34

Bioanalytical Assays in a Drug Discovery Environment

11

Figure 1.11 LC–MS/MS chromatograms showing the use of a monolithic column to shorten the assay time by increasing the mobile phase flow rate. The flow rates are 1 mL/min, 3 mL/min and 6 mL/min for the bottom, middle and top traces, respectively. Good peak shape and analyte separation was still seen at the 6-mL/min flow rate. Source: Wu et al. [54]. With permission.

6 mL/min. As a final test, the authors stated that the column was used successfully to analyze 600 plasma extracts in one overnight test. Hsieh et al. [57] have also described the utility of monolithic columns for use in drug discovery PK assays. In this work, the authors developed an assay for a compound and its metabolite. The authors made a standard curve in plasma that contained both the dosed compound and the metabolite of interest. The authors then showed that by using a flow rate of 4 mL/min, the assay time could be reduced to less than 1 min per sample. Finally, the authors demonstrated that the high flow rate assay provided assay results for the dosed drug and metabolite that were equivalent to those obtained using standard flow rate LC–MS/MS conditions. In another article, Hsieh et al. [62] have recently described the possible utility of using zirconia-based HPLC columns for drug discovery PK assays. One advantage of the zirconia-based HPLC column is that it can be heated to 200 C. The authors stated that the ability Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 12/34

12

Using Mass Spectrometry for Drug Metabolism Studies

to heat the column allows one to increase the flow rate of the mobile phase without exceeding the pressure limits of the column. There has been much interest in documenting the need to obtain good chromatographic separation in order to avoid the potential issue of one or more metabolites showing up in the same selected reaction monitoring (SRM) transition that is selected for the parent (dosed) compound [63]. The basis for this potential problem is that in-source fragmentation can occur for some types of molecules and that this fragmentation can produce ions that are identical to those formed as [MH]þ ions (positive ionization mode) from the parent compound, thus these ions would produce a signal in the SRM transition for the parent compound. The most commonly cited metabolite class that can produce this effect is glucuronides. While this problem is well known to occur in APCI sources, it is sometimes assumed to not be an issue when using ESI sources. Yan et al. [64] studied the problem, specifically looking at in-source fragmentation of glucuronides in an ESI source. They tested over 100 N- and O-glucuronides in both the positive and the negative ESI mode and varied source temperature and cone voltage to see what effect, if any, these parameters had on the extent of in-source fragmentation. They noted that source temperature had little effect on the amount of in-source fragmentation and that at normal (25–40 V) cone voltage, in-source fragmentation was detected for all glucuronides; at lower cone voltages, the in-source fragmentation was reduced or eliminated. Figure 1.12 [64] shows an example of this effect for an assay of a compound, 7 and its two N-glucuronides, 7-GI and 7-GII. In trace A1 and A2, the cone voltage was set to 29 V and two extra peaks can be seen in the channel for the parent compound, 7 — one of them causing a significant shoulder on the peak for the parent compound. These extra peaks were not observed when the cone voltage was reduced to 18 V (trace B1 and B2). Liu and Pereira [65] reported that both carbamoyl glucuronides and acyl glucuronides, in-source fragmentation was a problem in both ESI and APCI modes of ionization. They stressed that this was a potential issue when using fast gradient chromatographic systems. As an example, as shown in Figure 1.13, the SRM trace for the parent (dosed) compound (a) shows a significant shoulder; this shoulder is separated when a more shallow gradient system was used (b) to assay the same sample [65]. The shoulder peak was found to be caused by a partially co-eluting carbamonyl glucuronide metabolite of the dosed compound. The need to separate acyl glucuronide metabolites from the parent compound to avoid this assay problem has been highlighted in several papers [63, 66–68]. (See Chapter 6 for more discussion of acyl glucuronides.) In papers by Tong et al. [69] and Ramanathan et al. [70], the issue of insource fragmentation by N-oxide metabolites is investigated. In the first paper, they showed that for two N-oxide compounds studied, both [MH]þ and [MH  16]þ ions were formed under APCI conditions, but not ESI conditions. In their second report, they demonstrated that in APCI and ESI sources that utilize a heated transport capillary tube, elevating the temperature of the heated transport capillary tube caused thermal deoxygenation leading to Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 13/34

Bioanalytical Assays in a Drug Discovery Environment

13

Figure 1.12 LC–MS chromatograms showing the potential interference from glucuronide metabolites. The upper two traces (A1, A2) are from a single assay with the ESI source cone voltage set to 29 V; the lower two traces (B1, B2) are from a single assay with the ESI source cone voltage set to 18 V. The sample being assayed is a microsomal incubation sample containing test compound 7 and two glucuronide metabolites of 7, 7-GI and 7-GII. The A1 and B1 channels are for the glucuronide metabolites; the A2 and B2 channels are set to monitor the [MH]þ for the test compound. At 29 V, the interferences can be seen in the A2 trace; this problem is resolved by setting the cone voltage to 18 V as shown in trace B2. Source: Yan et al. [64]. With permission.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 14/34

14

Using Mass Spectrometry for Drug Metabolism Studies

Figure 1.13 LC–MS/MS SRM chromatograms demonstrating the potential for interference in the assay of a test compound, I, from a co-eluting carbamonyl glucuronide metabolite of the compound, I-CG. The internal standard is labeled as IS. The upper traces (a) show the results from a fast chromatography system, while the lower traces show the results from a longer assay for the same sample. The shoulder peak in the analyte trace (a) was found to be caused by a partially co-eluting carbamonyl glucuronide metabolite of the dosed compound that was resolved when the longer assay was used as shown in trace (b). Source: Liu and Pereira [65]. With permission.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 15/34

Bioanalytical Assays in a Drug Discovery Environment

15

Table 1.1 Putative metabolites of drugs of different chemical structures and the SRM transitions for the metabolites vis-a-vis the SRM transitions of the drug Drug type

Drug SRM

Metabolite

Metabolite SRM

Carboxylic acid

[M þ H]þ ! Pþ

Acylglucuronide

g or d-Hydroxycarboxylic acid Lactone

[M þ H]þ ! Pþ

Lactone

[M þ H]þ ! Pþ

Hydroxy acid

(a) [M þ H þ 176]þ ! [M þ H]þ (b) [M þ H þ 176]þ ! Pþ (a) [M þ H  18]þ ! [M þ H]þ (b) [M þ H  18]þ ! Pþ (a) [M þ H þ 18]þ ! [M þ H]þ (b) [M þ H þ 18]þ ! Pþ (a) [M þ H þ 176]þ ! [M þ H]þ (b) [M þ H þ 176]þ ! Pþ (a) [M þ H þ 80]þ ! [M þ H]þ (b) [M þ H þ 80]þ ! Pþ (a) [M þ H þ 176]þ ! [M þ H]þ (b) [M þ H þ 176]þ ! Pþ (a) [M þ H þ 16]þ ! [M þ H]þ (b) [M þ H þ 16]þ ! Pþ (a) [M þ M  1]þ ! [M þ H]þ (b) [M þ M  1]þ ! Pþ (a) [M þ H þ 16]þ ! [M þ H]þ (b) [M þ H þ 16]þ ! Pþ

þ

þ

Alcohol or phenol

[M þ H] ! P

Alcohol or phenol

[M þ H]þ ! Pþ þ

þ

Amine

[M þ H] ! P

Amine

[M þ H]þ ! Pþ þ

þ

Thiol (sulfhydryl)

[M þ H] ! P

Sulfide

[M þ H]þ ! Pþ

O-Glucuronide O-Sulfate N-Glucuronide N-Oxide Disulfide S-Oxide

The SRM transitions shown are for ESI in the positive ion mode. M is the monoisotopic mass of the drug. P is the product ion in the SRM transition used for quantitation of the drug. For each drug type, the fragmentation exhibited by the metabolite SRM transition designated as (a) can potentially take place within the source of the mass spectrometer as well. If such in-source fragmentation occurs and there is no chromatographic separation between the drug and the metabolite, the concentration of the drug determined by using the [M þ H]þ ! Pþ transition would be inflated. A similar list of SRM transitions can be prepared for negative ESI, and for atmospheric pressure chemical ionization in the positive or negative ion mode. (Reprinted, with permission, from Jemal et al. Rapid Commun. Mass Spectrom., 16, 1545, 2002.)

[MH  16]þ ions for three N-oxide compounds that were studied. The authors stated that while this could be a problem when performing quantitative assays for dosed compounds that have N-oxide metabolites, it could also be useful for metabolite identification purposes when trying to distinguish between isobaric metabolites that could be either N-oxides or hydroxylated species. In a report by Jemal et al. [71], the authors list a series of putative metabolites that have the potential to interfere with an assay for the dosed drug. As shown in Table 1.1, this list shows drug types and potential metabolites that could be formed that could, through in-source fragmentation provide false signals in the parent selected reaction monitoring (SRM) chromatogram [71]. The authors then propose a strategy for pretesting important samples to avoid being misled by these potential problem metabolites if they are in the samples. For their example compound, they have a drug with a carboxylic acid moiety and they test to see if one or more acyl glucuronide metabolites are in the samples (for more on acyl glucuronide metabolites, see Chapters 6 and 8). Tiller and Romanyshyn [66] discuss the value of monitoring metabolites in discovery PK studies. These authors give a rat PK example in which six metabolites were monitored along with the dosed drug. They also discuss a Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 16/34

16

Using Mass Spectrometry for Drug Metabolism Studies

Figure 1.14 The assay results from a dog PK study. The results are plotted as amount vs time after dosing. The graph shows the amounts for the dosed compound, C, as well as a monitored monohydroxy metabolite, C OH. It can be seen that the levels of the monohydroxy metabolite, C OH, were much higher that the levels of the dosed compound, C, for both dogs. Source: Tiller and Romanyshyn [66]. With permission.

dog PK study where they monitored a monohydroxy as well as a dihydroxy metabolite. In the dog study, as shown in Figure 1.14, the hydroxylated metabolite (C OH) was found to be at concentrations higher than the dosed drug throughout the PK profile [66]. The pharmacodynamic (PD) observations from this dog study correlated well with the hydroxlylated metabolite— therefore, it was very helpful to the project team to get this type of data early in the discovery stage. Kostiainen et al. [26] reviewed the use of LC–MS/MS for drug metabolism studies including metabolite identification and Cox et al. [72] and Clarke et al. [73] have described general procedures for metabolite characterization in a drug discovery setting. Recently, Ramanathan et al. [74], Nassar and Adams [75], and Jemal et al. [76] have all described strategies for rapid metabolite identification for in vitro samples. (For more details on metabolite identification, see Chapter 8.) Off-line sample preparation has received a great deal of attention in the literature. The most common procedures are liquid–liquid extraction [77–79], solid phase extraction [80–85], and protein precipitation [86–88]. Of these three, the most common procedure, in a drug discovery environment, is protein precipitation because it is easy to implement and easy to semi-automate [88]. Most semi-automation procedures are based on the use of 96-well plates. One of the first steps that needs to be done is to transfer an aliquot of the plasma into the proper well of the 96-well plate. Ideally, this step should be performed using a robot to make the transfer; Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 17/34

Bioanalytical Assays in a Drug Discovery Environment

17

one of the practical problems is that thrombin clots tend to form in the plasma, and this can be a problem for a robotic system [89, 90]. Sadagopan et al. [91] investigated the merits of using EDTA as the anticoagulant instead of the more commonly used heparin. They found that neither anticoagulant was a problem for the LC–MS/MS assay, but EDTA was superior in that it was better in the prevention of thrombin clots relative to heparin, therefore they recommended using EDTA as the anticoagulant when collecting samples to be assayed by LC–MS/MS. Berna et al. [90] also found that EDTA was better than heparin in reducing the formation of thrombin clots in the plasma samples. In addition, they studied a special polypropylene 96-well filter plate that could be used to store and filter plasma samples as another means of avoiding the problem of thrombin clots. Mallet et al. [92, 93] have described a low elution volume 96well solid phase extraction (SPE) plate that was designed for low volume plasma studies (50-mL samples). The plate was designed to work with a Quadra 96 (Tomtec, Hamden, CT) robotic liquid handler. The authors state that this new low-elution volume SPE plate should be useful for drug discovery PK studies. Eerkes et al. [77] discuss an automated liquid/liquid extraction (L/L) procedure based on a 96-well plate format. There has also been a lot of activity in terms of on-line extraction procedures (see, for example, Ackermann et al. [94], Wu [95], Kerns et al. [96] and Cass et al. [97]). A more complete discussion of this topic can be found in Chapter 5. As sample throughput increases, so does the number of compounds that can be studied each week. Another area of interest, therefore, is automated MS/MS method development. Higton [98] has shown an MS and MS/MS automated method building system that can create SRM methods for new test compounds at a rate of close to 30 per hour. Whalen et al. [99] described the Autoscan software that can be used to obtain MS as well as MS/MS conditions for assaying 96 compounds in 1 h. In a series of articles, Watt et al. [89] and Locker et al. [100] have described the utility and application of an automated sample preparation system designed for drug discovery PK samples. In the more recent of these two articles Locker et al. [100] describe an integrated robotic system that not only makes the standard curves, but also precipitates the samples and develops an optimized MS/MS procedure for each analyte. The issue of matrix ion suppression, often called matrix effects, has received increasing attention in the literature recently [38, 40, 101–106]. Miller-Stein et al. [39] discuss some of the issues regarding the matrix effect problem and provide a procedure for evaluating matrix effects in a given assay by using post-column infusion of the analyte of interest. Muller et al. [107] studied the effect of various sample preparation techniques in terms of the observed matrix effect in the described assay; they concluded that matrix effects could be avoided when using standard chromatographic systems, but could be a problem for high throughput applications. Avery [108] suggested trying more than one potential internal standard and looking at several lots of plasma when evaluating an analytical method. Both Schuhmacher et al. [104] and Shou and Naidong [109] discussed the potential problems of the dosing formulation Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 18/34

Using Mass Spectrometry for Drug Metabolism Studies

18

vehicle in terms of potential matrix effect issues; in both articles, PEG 400 was cited as causing matrix effect problems. Mei et al. [103] described a study of the potential for sample tubes to cause matrix effect issues. While not commonly available in a drug discovery setting, it has generally been assumed that the use of a stable-isotope labeled (SIL) internal standard will eliminate any matrix effect problem; a recent article by Jemal et al. [110] showed an example of a matrix effect problem that was observed even with the use of an SIL internal standard. A complete discussion of matrix effects can be found in Chapter 4. Another area of interest is the development of new technology with new capabilities. One example of this advance is the development of a higher mass resolution triple quadrupole mass spectrometer. Jemal and Ouyang [111] evaluated an enhanced mass resolution triple quadrupole mass spectrometer in terms of utility, stability and reproducibility. They demonstrated the potential utility of this new technology and also suggested ways to utilize it properly to minimize problems. Yang et al. [112] studied the stability of an enhanced mass resolution triple quadrupole mass spectrometer and found it to be suitable for typical bioanalytical applications. Xu et al. [113] compared the results of a conventional triple quadrupole mass spectrometer with those of an enhanced mass resolution triple quadrupole mass spectrometer and found that in some cases, improved lower limits of quantitation could be obtained from the enhanced mass resolution triple quadrupole mass spectrometer. Additional discussion of enhanced mass resolution mass spectrometers can be found in Chapters 7 and 8. Other new technologies that may be advantageous and are therefore important to follow are: atmospheric pressure photoionization (APPI) as discussed by Hsieh et al. [62, 114], Raffaelli and Saba [115] and Yang and Henion [116] (see also Chapter 9); the quadrupole linear ion trap mass spectrometer (see Xia et al. [117] and Chapter 10); MS imaging for small molecules (see Chapter 11); and nanospray/chip technologies (see Dethy et al. [118], Kapron et al. [119], and Chapter 12).

1.3

Current Practices

As shown in Figure 1.15, drug discovery PK analyses include multiple steps, which need to be performed in sequence so that the PK results can be distributed to the drug discovery project team as well as entered into a database for future reference. Many talks and papers have discussed speeding up drug discovery PK assays; most of these articles have focussed on one step in the process—typically the LC–MS/MS assay step. It is important to consider the whole process from start to completion when trying to determine how best to decrease the time it takes to get PK results back to the drug discovery project team. Figure 1.16 shows the major steps in the discovery bioanalytical process as a sequential series with the point that any one step can be the bottleneck. Over the last several years, these steps have been streamlined so that what used to Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 19/34

Bioanalytical Assays in a Drug Discovery Environment

19

Figure 1.15 Discovery PK analysis flowchart showing the multiple steps that are involved from the dosing to the assay to the report preparation and electronic delivery to the discovery team.

Figure 1.16 Potential bottlenecks in PK assays based on LC–MS/MS.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 20/34

20

Using Mass Spectrometry for Drug Metabolism Studies

Figure 1.17 Semi-automated sample preparation procedure used in the CARRS assay. Adapted from Korfmacher et al. [87]. With permission.

take 4–5 weeks can now be performed in a few days. Sample tracking can be performed using either an ExcelÕ (Microsoft Corp.) -based tracking system or a laboratory LIMS system such as WATSONÕ (InnaPhase Corp., www. innaphase.com). Standard curve preparation can be readily performed using robotic sample handling systems (e.g., Packard MultiPROBEÕ ) that can not only make dilutions of the standard stock solution, but also add the required amount of these solutions to the plasma matrix to make the plasma standards that are required for the assay. As discussed above, many researchers have described ways to speed up the sample preparation process. One of the best ways is to use 96-well plates for all of the sample handling steps. One can then use semi-automated sample preparation via protein precipitation and a liquid handling robot (e.g., TOMTEC Quadra 96Õ ) to add the acetonitrile solution including the internal standard (see Figure 1.17). This procedure has greatly improved the efficiency of the process—a chemist can now prepare 96 samples in less than 20 min; previous manual procedures based on single vials for each sample were very laborious—it was common to need up to 4 h to prepare 96 samples when each sample was handled individually. Robotics can not only save time, but if properly set up and maintained, should be more reproducible than manual procedures. The LC–MS/MS assay itself has been the focus of many recent articles regarding speeding up the process (vide supra). By using high-speed HPLC systems, one can now routinely assay plasma samples using 2-min cycle times per sample. Cycle times are the amount of time from injection of one sample Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 21/34

Bioanalytical Assays in a Drug Discovery Environment

21

to the injection of the next sample. Typical setups utilize short (2–3 cm) narrow-bore (1–2 mm, i.d.) HPLC columns with flow rates up to 1 mL/min or more. Often a divert valve is built into the LC–MS/MS system and can be used to divert the first 20% of the total sample cycle time; this allows much of the ‘‘junk’’ to be diverted to waste, thereby keeping the mass spectrometer source cleaner than it would be without the divert valve in use. The most commonly used mass spectrometer for bioanalytical applications is the triple quadrupole instrument. By using the SRM mode, a skilled operator can set up very specific MS/MS methods for the analyte and internal standard. In the positive ionization mode, this would typically be based on selecting the [MH]þ ions using the first quadrupole (Q1); the [MH]þ ions are then focussed into the collision cell (q2) where they are fragmented using collisioninduced dissociation (CID) into various product ions; one of the product ions is selected using the third quadrupole (Q3) and only ions of that specific m/z are sent to the detector. The highly specific nature of the SRM use of the triple quadrupole mass spectrometer was first noted by Brotherton and Yost [120] in 1983. The basic analytical principle that Brotherton and Yost described in their landmark article [120] was that the multiple stages of selection in the MS/MS system reduced the noise faster than the signal, thereby creating a net improvement in the S/N ratio. More recently, Korfmacher et al. [86] described the basic principles for using LC–MS/MS for drug metabolism support of new drug discovery applications. These principles include the use of SRM, whereby multiple analytes including the internal standard, can be monitored in a single LC–MS/MS assay; these basic principles are still in use today. By spiking the analyte of interest into plasma from the same species as the samples to be assayed, one can compare the response ratio of the analyte to the internal standard (a separate compound that is added in the sample preparation process) to make the calibration curve and then use this to determine the concentration of the analyte in the plasma samples. The assay data calculations are typically performed using the mass spectrometer vendor’s software, but can also be performed using other software with linear (or other smooth curve functions, e.g., power curve or quadratic as needed) regression capabilities (e.g., WATSON or Excel). For assays over a range of three orders of magnitude or more, it is common to use weighting when performing the standard curve regression—typical weighting parameters are 1/x or 1/x2. Simple PK calculations (AUC, Cmax, Tmax) can be performed using Excel or similar software. For more complicated PK calculations (e.g., clearance, volume of distribution, mean residence time), WATSON or other PK calculation programs are required. WATSON has the advantage that it is able to export sample lists to major vendors’ mass spectrometer systems and import tabular results from such systems—this is an important capability in that it avoids having to type summary assay data into the computer used for the PK report calculations. Once the PK reports are completed, they can then be saved into a database or reformatted into Excel reports, which can be issued via e-mail to the discovery project team Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 22/34

22

Using Mass Spectrometry for Drug Metabolism Studies

Figure 1.18 Stages in new drug discovery. A large number of compounds are screened out by each stage. The levels I–IV refer to the assay rules outlined in this chapter.

that is awaiting the data. Thus, the whole procedure outlined in Figures 1.16 and 1.17 can be expedited through careful evaluation of each step in the process, resulting in a higher throughput operation by utilizing a combination of robotics, state-of-the-art LC–MS/MS equipment and smart software tools. One way to view the drug discovery process is that it is a series of stages through which compounds must pass in order to qualify for being a development compound. These stages represent various in vitro and in vivo tests that are performed on a series of compounds in order to select those few compounds that have the correct properties for the desired activity. As shown in Figure 1.18, there are multiple stages that involve measuring various drug metabolism and pharmacokinetic (DMPK) parameters. In terms of in vivo tests that require bioanalytical assays, there have been no clear guidelines to follow until a compound enters the development stage where most of the bioanalytical assays are required to be performed under good laboratory practice (GLP) regulations [121, 122]. Before the development stage, one could envisage a series of assay requirements that become stricter as one approaches the development stage. As shown in Figure 1.18, various levels (I–IV) have been assigned to the stages leading up to and including the development stage. As shown in Table 1.2, these drug stages have been assigned assay types (level I to level IV). level I is the screening stage, level II is lead optimization, level III is lead qualification and level IV is development. Screening can be defined as the stage where a larger number of compounds are tested in order to select a smaller number for optimization. In the optimization phase, the lead compound Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 23/34

Bioanalytical Assays in a Drug Discovery Environment

23

Table 1.2 Assay levels for bioanalytical methods Drug stage Screening Lead optimization Lead qualification Development

Assay type Level Level Level Level

I II III IV

Summary of major rules

GLP

Use a two-point standard curve Use a multi-point standard curve but no quality control Use a multi-point standard curve plus quality control GLP rules

No No No Yes

structures are varied until an optimum structure is selected (see Chapter 2 for more on this topic). In lead qualification, the optimized structure undergoes lower throughput testing (e.g., single rising dose PK, multiple dose rat enzyme induction study, etc.). Compounds that show the acceptable DMPK properties after all of these assays have been completed are then considered as candidates for development. Table 1.2 also lists the major rules for each assay level in our laboratory. These rules were designed to become stricter as the compounds move from level I to level III. Level I assays are designed to be easy to implement in a higher throughput manner. Table 1.3 lists in detail the rules for Table 1.3 Rules for discovery (non-GLP) screen assays (level I) 1. Samples should be assayed using HPLC–MS/MS technology. 2. Sample preparation should consist of protein precipitation using an appropriate internal standard (IS). 3. Samples should be assayed along with a standard curve in duplicate (at the beginning and end of the sample set). 4. The zero standard is prepared and assayed, but is not included in the calibration curve regression. 5. Standard curve stock solutions are prepared after correcting the standard for the salt factor. 6. The standard curve should be three levels, typically ranging from 25 to 2500 (they can be lower or higher as needed for the program) ng/mL; each standard is 10
the one below (thus, a typical set would be 25, 250 and 2500 ng/mL). The matrix of the calibration curve should be from the same animal species and matrix type as the samples. 7. QC samples are not used and the assay is not validated. 8. After the assay, the proper standard curve range for the samples is selected; this must include only two concentrations in the range that covers the samples. A one order of magnitude range is preferred, but two orders of magnitude is acceptable, if needed to cover the samples. 9. Once the range is selected, at least three of the four assayed standards in the range must be included in the regression analysis. Regression is performed using unweighted linear regression (not forced through zero). 10. All standards included in the regression set must be back calculated to within 27.5% of their nominal values. 11. The limit of quantitation (LOQ) may be set as either the lowest standard in the selected range or as 0.4 times the lowest standard in the selected range, but the LOQ must be greater than three times the mean value for the back-calculated value of the two zero standards. 12. Samples below the LOQ are reported as zero. 13. If the LOQ is 0.4 times the lowest standard in the selected range, then samples with backcalculated values between the LOQ and the lowest standard in the selected range may be reported as their calculated value provided the S/N for the analyte is at least 3. 14. Samples with back-calculated values between 1.0
and 2.0
the highest standard in the selected range are reportable by extending the calibration line up to 2
the high standard. 15. Samples found to have analyte concentrations more than 2
the highest standard in the regression set are not reportable; these samples must be reassayed after dilution or along with a standard curve that has higher concentrations so that the sample is within 2
the highest standard.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 24/34

24

Using Mass Spectrometry for Drug Metabolism Studies

Figure 1.19 A schematic diagram showing how one 96-well plate can be used to hold all of the samples and standards needed to assay six compounds in the CARRS assay. Source: Korfmacher et al. [87]. With permission.

a level I assay. A good example for a level I assay is the cassette-accelerated rapid rat screen (CARRS) assay for higher throughput analyses of plasma sample from multiple rat PK screen studies [87]. Because this assay only requires a two-point calibration curve, as shown in Figure 1.19, it is possible to assemble all the standards and samples for six mini-PK studies onto one 96-well plate [87]. Due to the two-point linear calibration curve, it is also easy to perform the calculations using an Excel-based template. The template can also be used to summarize the PK data and make it available to the drug discovery team as an e-mail attachment. The reason that this simple assay is still accurate is that triple quadrupole mass spectrometers are generally linear over at least one to two orders of magnitude. In addition, the rules allow one to estimate above and below the upper and lower standards, respectively; thus, if the standards used are 25 and 250 ng/mL, the useful quantitation range is 10 to 500 ng/mL, as long as rules 11 and 13 are followed (see Table 1.3). Level II assays are required for lead optimization studies (e.g., rat, dog or monkey PK studies); in these studies, there are higher numbers of samples (30–60) for each compound and the goal is to obtain enough data to be able to calculate several PK parameters (e.g., clearance, half-life, AUC, volume of distribution). Therefore, these assays need to be more rigorous. As shown in Table 1.4, the rules for the level II assays are more extensive than for level I assays. The biggest change is the need for a multipoint standard curve (a minimum of five concentrations is required). Because the level II assay can be several orders of magnitude (typically three to four), both weighted and nonlinear regression is allowed. Typical weighting parameters are 1/x and 1/x2; these are needed to make the low end of the calibration curve fit correctly. A power curve fitting is a very useful nonlinear fit; it is based on the equation, Y ¼ mxc þ b, where Y is the area ratio (analyte/internal standard), m is the slope, x is the analyte Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 25/34

Bioanalytical Assays in a Drug Discovery Environment

25

Table 1.4 Rules for discovery (non-GLP) full PK assays (level II) 1. Samples should be assayed using HPLC–MS/MS technology. 2. Sample preparation should consist of protein precipitation using an appropriate internal standard (IS). 3. Samples should be assayed along with a standard curve in duplicate (at the beginning and end of the sample set). 4. The zero standard is prepared and assayed, but is not included in the calibration curve regression. 5. Standard curve stock solutions are prepared after correcting the standard for the salt factor. 6. The standard curve should be 10–15 levels, typically ranging from 1 to 5000 or 10,000 (or higher as needed) ng/mL. The matrix of the calibration curve should be from the same animal species and matrix type as the samples. 7. QC samples are not used. 8. After the assay, the proper standard curve range for the samples is selected; this must include at least five (consecutive) concentrations. 9. Once the range is selected, at least 75% of the assayed standards in the range must be included in the regression analysis. 10. Regression can be performed using weighted or unweighted linear or smooth curve fitting (e.g., power curve or quadratic), but is not forced through zero. 11. All standards included in the regression set must be back calculated to within 27.5% of their nominal values. 12. The regression r2 must be 0.94 or larger. 13. The limit of quantitation (LOQ) may be set as either the lowest standard in the selected range or as 0.4 times the lowest standard in the selected range, but the LOQ must be greater than three times the mean value for the back-calculated value of the two zero standards. 14. Samples below the LOQ are reported as zero. 15. If the LOQ is 0.4 times the lowest standard in the selected range, then samples with backcalculated values between the LOQ and the lowest standard in the selected range may be reported as their calculated value provided the S/N for the analyte is at least 3. 16. Samples with back-calculated values between 1.0
and 2.0
the highest standard in the selected range are reportable by extending the calibration curve up to 2
the high standard as long as the calibration curve regression was not performed using quadratic regression. 17. Samples found to have analyte concentrations more than 2
the highest standard in the regression set are not reportable; these samples must be reassayed after dilution or along with a standard curve that has higher concentrations so that the sample is within 2
the highest standard. 18. The assay is not validated. 19. The final data does not need to have quality assurance (QA) approval. This is an exploratory, non-GLP study.

concentration, b is the intercept and c is a curve fitted power value usually between 0.9 and 1.1. The need for a nonlinear curve fit is based in part on the fact that LC–MS/MS assays (especially those based on ESI) often have a nonlinear response over a range of three or more orders of magnitude. These rules for level II assays have been tested on thousands of compounds over several years and have been found to work well. Good assays meet the rules and poor ones do not. As shown in Table 1.5, for level III assays, the main change is the use of quality control (QC) samples. This additional level of analytical rigor was put in place for those assays that are used on the smaller number of studies that are performed on compounds that are close to development. The addition of QC samples provides additional confidence in the results that are obtained with these assays. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 26/34

Using Mass Spectrometry for Drug Metabolism Studies

26

Table 1.5 Additional rules for discovery (non-GLP) PK assays requiring QC samples (level III) 1. Use all the rules for full PK (level II) assays (except rule 7) plus the following rules. 2. Quality control (QC) standards are required, and a minimum of six QCs at three concentrations (low, middle, high) are to be used. The QC standards should be frozen at the same freezer temperature as the samples to be assayed. 3. The QC standards need to be traceable to a separate analyte weighing from the one used for the standard curve standards. 4. The standard curve standards should be prepared on the same day the samples are prepared for assay. The standard curve solutions needed for this purpose may be stored in a refrigerator until needed for up to 6 months. 5. At least 2/3 of the QC samples must be within 25% of their prepared (nominal) values. 6. If dilution of one or more samples is required for this assay, then an additional QC at the higher level must be prepared, diluted and assayed along with the sample(s) needing dilution. This QC should be run in duplicate and at least one of the two assay results must meet the 25% criteria.

1.4

Conclusions

The current practice for the use of LC–MS/MS systems for bioanalytical assays in a drug discovery environment is to make use of the special capabilities of triple quadrupole mass spectrometers in a high throughput manner to provide high quality assays without following all the requirements for having validated (as per GLP regulations) assays. It is important to view the assay as merely one step in the process that must take place when one is asked to provide high quality data in a high throughput manner to support new drug discovery needs. As both mass spectrometry and sample robotic instrumentation improve, there will continue to be opportunities for increasing the throughput of these discovery pharmacokinetic studies.

References 1. Kaitin, K., Total Cost to Develop a New Prescription Drug. Vol. 5(3). Tufts Center for the Study of Drug Development, Boston, MA, 2003. 2. Beresford, A.P., Selick, H.E., and Tarbit, M.H., The emerging importance of predictive ADME simulation in drug discovery, Drug Discov. Today, 7(2), 109, 2002. 3. Chaturvedi, P.R., Decker, C.J., and Odinecs, A., Prediction of pharmacokinetic properties using experimental approaches during early drug discovery, Curr. Opin. Chem. Biol., 5(4), 452, 2001. 4. Savchuk, N.P., In silico ADME-Tox as part of an optimization strategy, Curr. Drug. Discov., (April 2003), 17, 2003. 5. Di, L. and Kerns, E.H., Profiling drug-like properties in discovery research, Curr. Opin. Chem. Biol., 7(3), 402, 2003. 6. Kerns, E.H. and Di, L., Pharmaceutical profiling in drug discovery, Drug Discov. Today, 8(7), 316, 2003. 7. Kerns, E.H. and Di, L., Multivariate pharmaceutical profiling for drug discovery, Curr. Top. Med. Chem., 2(1), 87, 2002. 8. Eddershaw, P.J., Beresford, A.P., and Bayliss, M.K., ADME/PK as part of a rational approach to drug discovery, Drug Discov. Today, 5(9), 409, 2000.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 27/34

Bioanalytical Assays in a Drug Discovery Environment

27

9. Caldwell, G.W., Compound optimization in early- and late-phase drug discovery: acceptable pharmacokinetic properties utilizing combined physicochemical, in vitro and in vivo screens, Curr. Opin. Drug Discov., 3(1), 30, 2000. 10. Lipinski, C.A., Drug-like properties and the causes of poor solubility and poor permeability, J. Pharmacol. Toxicol. Methods, 44(1), 235, 2000. 11. Korolev, D. et al. Modeling of human cytochrome p450-mediated drug metabolism using unsupervised machine learning approach, J. Med. Chem., 46(17), 3631, 2003. 12. Bugrim, A., Nikolskaya, T., and Nikolsky, Y., Early prediction of drug metabolism and toxicity: systems biology approach and modeling, Drug Discov. Today, 9(3), 127, 2004. 13. Newton, C.G. and Lockey, P.M., The importance of early pharmacokinetics, Curr. Drug Discov., (April 2003), 33, 2003. 14. Spalding, D.J.M., Harker, A.J., and Bayliss, M.K., Combining high-throughput pharmacokinetic screens at the hits-to-leads stage of drug discovery, Drug Discov. Today, 5(12), 70, 2000. 15. Korfmacher, W.A., Lead optimization strategies as part of a drug metabolism environment, Curr. Opin. Drug Discov. Devel., 6(4), 481, 2003. 16. Ackermann, B.L., Berna, M.J., and Murphy, A.T., Recent advances in use of LC/ MS/MS for quantitative high-throughput bioanalytical support of drug discovery, Curr. Top. Med. Chem., 2(1), 53, 2002. 17. Cox, K.A., White, R.E., and Korfmacher, W.A., Rapid determination of pharmacokinetic properties of new chemical entities: in vivo approaches, Comb. Chem. High Throughput Screen, 5(1), 29, 2002. 18. Hopfgartner, G., Husser, C., and Zell, M., High-throughput quantification of drugs and their metabolites in biosamples by LC-MS/MS and CE-MS/MS: possibilities and limitations, Ther. Drug Monit., 24(1), 134, 2002. 19. Jemal, M., High-throughput quantitative bioanalysis by LC/MS/MS, Biomed. Chromatogr., 14(6), 422, 2000. 20. O’Connor, D., Automated sample preparation and LC-MS for high-throughput ADME quantification, Curr. Opin. Drug Discov. Devel., 5(1), 52, 2002. 21. Papac, D.I. and Shahrokh, Z., Mass spectrometry innovations in drug discovery and development, Pharm. Res., 18(2), 131, 2001. 22. Tarbit, M.H. and Berman, J., High-throughput approaches for evaluating absorption, metabolism and excretion properties of lead compounds, Curr. Opin. Chem. Biol., 2, 411, 1998. 23. Lee, M.S. and Kerns, E.H., LC/MS applications in drug development, Mass Spectrom. Rev., 18(3–4), 187, 1999. 24. Oliveira, E.J. and Watson, D.G., Liquid chromatography–mass spectrometry in the study of the metabolism of drugs and other xenobiotics, Biomed. Chromatogr., 14(6), 351, 2000. 25. Rudewicz, P.J. and Yang, L., Novel approaches to high throughput quantitative LC-MS/MS in a regulated environment, Am. Pharm. Rev., 4(2), 64, 2001. 26. Kostiainen, R. et al. Liquid chromatography/atmospheric pressure ionization-mass spectrometry in drug metabolism studies, J. Mass Spectrom., 38(4), 357, 2003. 27. Plumb, R.S. et al. Quantitative analysis of pharmaceuticals in biological fluids using high-performance liquid chromatography coupled to mass spectrometry: a review, Xenobiotica, 31(8–9), 599, 2001. 28. Niessen, W.M., Progress in liquid chromatography–mass spectrometry instrumentation and its impact on high-throughput screening, J. Chromatogr., A, 1000(1–2), 413, 2003.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 28/34

28

Using Mass Spectrometry for Drug Metabolism Studies

29. Shou, W.Z. et al. Ultrafast liquid chromatography/tandem mass spectrometry bioanalysis of polar analytes using packed silica columns, Rapid Commun. Mass Spectrom., 16(17), 1613, 2002. 30. Hsieh, Y., Brisson, J.-M., and Wang, G., Fast HPLC-MS/MS for small molecules, Am. Pharm. Rev., 6(4), 14, 2003. 31. Heinig, K. and Henion, J., Fast liquid chromatographic–mass spectrometric determination of pharmaceutical compounds, J. Chromatogr. B. Biomed. Sci. Appl., 732(2), 445, 1999. 32. Heinig, K. and Bucheli, F., Ultra-fast quantitative bioanalysis of a pharmaceutical compound using liquid chromatography–tandem mass spectrometry, J. Chromatogr. B. Anal. Technol. Biomed. Life Sci., 795(2), 337, 2003. 33. Henion, J. et al. Sample preparation and analysis strategies for high throughput LC/MS/MS analysis of biological samples, Am. Pharm. Rev., 3, 19, 2000. 34. Romanyshyn, L. et al. Ultra-fast gradient vs. fast isocratic chromatography in bioanalytical quantification by liquid chromatography/tandem mass spectrometry, Rapid Commun. Mass Spectrom., 15(5), 313, 2001. 35. Naidong, W. et al. Importance of injection solution composition for LC-MS-MS methods, J. Pharm. Biomed. Anal., 26(5–6), 753, 2001. 36. Zhao, J.J., Yang, A.Y., and Rogers, J.D., Effects of liquid chromatography mobile phase buffer contents on the ionization and fragmentation of analytes in liquid chromatographic/ionspray tandem mass spectrometric determination, J. Mass Spectrom., 37(4), 421, 2002. 37. Tiller, P.R. and Romanyshyn, L.A., Implications of matrix effects in ultra-fast gradient or fast isocratic liquid chromatography with mass spectrometry in drug discovery, Rapid Commun. Mass Spectrom., 16(2), 92, 2002. 38. Hsieh, Y. et al. Quantitative screening and matrix effect studies of drug discovery compounds in monkey plasma using fast-gradient liquid chromatography/tandem mass spectrometry, Rapid Commun. Mass Spectrom., 15(24), 2481, 2001. 39. Miller-Stein, C. et al. Rapid method development of quantitative LC-MS/MS assays for drug discovery, Am. Pharm. Rev., 3, 54, 2000. 40. King, R. et al. Mechanistic investigation of ionization suppression in electrospray ionization, J. Am. Soc. Mass Spectrom., 11(11), 942, 2000. 41. Korfmacher, W.A. et al. Demonstration of the capabilities of a parallel high performance liquid chromatography tandem mass spectrometry system for use in the analysis of drug discovery plasma samples, Rapid Commun. Mass Spectrom., 13(20), 1991, 1999. 42. Jemal, M. et al. Increased throughput in quantitative bioanalysis using parallelcolumn liquid chromatography with mass spectrometric detection, Rapid Commun. Mass Spectrom., 15(12), 994, 2001. 43. King, R.C. et al. Description and validation of a staggered parallel high performance liquid chromatography system for good laboratory practice level quantitative analysis by liquid chromatography/tandem mass spectrometry, Rapid Commun. Mass Spectrom., 16(1), 43, 2002. 44. Hiller, D.L. et al. Application of a non-indexed dual sprayer pneumatically assisted electrospray source to the high throughput quantitation of target compounds in biological fluids, Rapid Commun. Mass Spectrom., 14(21), 2034, 2000. 45. Bayliss, M.K. et al. Parallel ultra-high flow rate liquid chromatography with mass spectrometric detection using a multiplex electrospray source for direct, sensitive determination of pharmaceuticals in plasma at extremely high throughput, Rapid Commun. Mass Spectrom., 14(21), 2039, 2000.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 29/34

Bioanalytical Assays in a Drug Discovery Environment

29

46. Deng, Y. et al. High-speed gradient parallel liquid chromatography/tandem mass spectrometry with fully automated sample preparation for bioanalysis: 30 seconds per sample from plasma, Rapid Commun. Mass Spectrom., 16(11), 1116, 2002. 47. Yang, L. et al. Evaluation of a four-channel multiplexed electrospray triple quadrupole mass spectrometer for the simultaneous validation of LC/MS/MS methods in four different preclinical matrixes, Anal. Chem., 73(8), 1740, 2001. 48. Xia, Y.Q. et al. Parallel extraction columns and parallel analytical columns coupled with liquid chromatography/tandem mass spectrometry for on-line simultaneous quantification of a drug candidate and its six metabolites in dog plasma, Rapid Commun. Mass Spectrom., 15(22), 2135, 2001. 49. Deng, Y. et al. Multiple-sprayer tandem mass spectrometry with parallel high flow extraction and parallel separation for high-throughput quantitation in biological fluids, Rapid Commun. Mass Spectrom., 15(17), 1634, 2001. 50. Murphy, A.T. et al. Effects of flow rate on high-throughput quantitative analysis of protein-precipitated plasma using liquid chromatography/tandem mass spectrometry, Rapid Commun. Mass Spectrom., 16(6), 537, 2002. 51. Dams, R. et al. Influence of the eluent composition on the ionization efficiency for morphine of pneumatically assisted electrospray, atmospheric-pressure chemical ionization and sonic spray, Rapid Commun. Mass Spectrom., 16(11), 1072, 2002. 52. Jemal, M. and Hawthorne, D.J., Effect of high performance liquid chromatography mobile phase (methanol versus acetonitrile) on the positive and negative ion electrospray response of a compound that contains both an unsaturated lactone and a methyl sulfone group, Rapid Commun. Mass Spectrom., 13(1), 61, 1999. 53. Seliniotakis, E. et al. The use of post column addition to improve signal response and reduce matrix effects in bioanalytical LC/MS/MS assays, in ASMS Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, 2003, ASMS. 54. Wu, J.T. et al. High-speed liquid chromatography/tandem mass spectrometry using a monolithic column for high-throughput bioanalysis, Rapid Commun. Mass Spectrom., 15(13), 1113, 2001. 55. van Nederkassel, A.M. et al. Fast separations on monolithic silica columns: method transfer, robustness and column ageing for some case studies, J. Pharm. Biomed. Anal., 32(2), 233, 2003. 56. Smith, J.H. and McNair, H.M., Fast HPLC with a silica-based monolithic ODS Column, J. Chromatogr. Sci., 41(4), 209, 2003. 57. Hsieh, Y. et al. Simultaneous determination of a drug candidate and its metabolite in rat plasma samples using ultrafast monolithic column high-performance liquid chromatography/tandem mass spectrometry, Rapid Commun. Mass Spectrom., 16(10), 944, 2002. 58. Hsieh, Y. et al. Direct plasma analysis of drug compounds using monolithic column liquid chromatography and tandem mass spectrometry, Anal. Chem., 75(8), 1812, 2003. 59. Peng, S.X., Barbone, A.G., and Ritchie, D.M., High-throughput cytochrome p450 inhibition assays by ultrafast gradient liquid chromatography with tandem mass spectrometry using monolithic columns, Rapid Commun. Mass Spectrom., 17(6), 509, 2003. 60. Tanaka, N. et al. Monolithic LC columns, Anal. Chem., 73(15), 420A, 2001.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 30/34

30

Using Mass Spectrometry for Drug Metabolism Studies

61. Vallano, P.T. et al. Monolithic silica liquid chromatography columns for the determination of cyclooxygenase II inhibitors in human plasma, J. Chromatogr., B: Anal. Technol. Biomed. Life Sci., 779(2), 249, 2002. 62. Hsieh, Y., Merkle, K., and Wang, G., Zirconia-based column high performance liquid chromatography/atmospheric pressure photoionization tandem mass spectrometric analyses of drug molecules in rat plasma, Rapid Commun. Mass Spectrom., 17, 1775, 2003. 63. Jemal, M. and Xia, Y.Q., The need for adequate chromatographic separation in the quantitative determination of drugs in biological samples by high performance liquid chromatography with tandem mass spectrometry, Rapid Commun. Mass Spectrom., 13(2), 97, 1999. 64. Yan, Z. et al. Cone voltage induced in-source dissociation of glucuronides in electrospray and implications in biological analyses, Rapid Commun. Mass Spectrom., 17(13), 1433, 2003. 65. Liu, D.Q. and Pereira, T., Interference of a carbamoyl glucuronide metabolite in quantitative liquid chromatography/tandem mass spectrometry, Rapid Commun. Mass. Spectrom., 16(2), 142, 2002. 66. Tiller, P.R. and Romanyshyn, L.A., Liquid chromatography/tandem mass spectrometric quantification with metabolite screening as a strategy to enhance the early drug discovery process, Rapid Commun. Mass Spectrom., 16(12), 1225, 2002. 67. Poon, G.K. et al. Integrating qualitative and quantitative liquid chromatography/ tandem mass spectrometric analysis to support drug discovery, Rapid Commun. Mass Spectrom., 13(19), 1943, 1999. 68. Wainhaus, S.B. et al. Semi-quantitation of acyl glucuronides in early drug discovery by LC-MS/MS, Am. Pharm. Rev., 5(2), 86, 2002. 69. Tong, W. et al. Fragmentation of N-oxides (deoxygenation) in atmospheric pressure ionization: investigation of the activation process, Rapid Commun. Mass. Spectrom., 15(22), 2085, 2001. 70. Ramanathan, R. et al. Liquid chromatography/mass spectrometry methods for distinguishing N-oxides from hydroxylated compounds, Anal. Chem., 72(6), 1352, 2000. 71. Jemal, M., Ouyang, Z., and Powell, M.L., A strategy for a post-method-validation use of incurred biological samples for establishing the acceptability of a liquid chromatography/tandem mass-spectrometric method for quantitation of drugs in biological samples, Rapid Commun. Mass Spectrom., 16(16), 1538, 2002. 72. Cox, K.A. et al. Higher throughput metabolite identification in drug discovery: current capabilities and future trends, Am. Pharm. Rev., 4(1), 45, 2001. 73. Clarke, N.J. et al. Systematic LC/MS metabolite identification in drug discovery, Anal. Chem., 73(15), 430A, 2001. 74. Ramanathan, R. et al. Application of semi-automated metabolite identification software in the drug discovery process for rapid identification of metabolites and the cytochrome P450 enzymes responsible for their formation, J. Pharm. Biomed. Anal., 28(5), 945, 2002. 75. Nassar, A.E. and Adams, P.E., Metabolite characterization in drug discovery utilizing robotic liquid-handling, quadrupole time-of-flight mass spectrometry and in-silico prediction, Curr. Drug Metab., 4(4), 259, 2003. 76. Jemal, M. et al. A strategy for metabolite identification using triple-quadrupole mass spectrometry with enhanced resolution and accurate mass capability, Rapid Commun. Mass Spectrom., 17(24), 2732, 2003.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 31/34

Bioanalytical Assays in a Drug Discovery Environment

31

77. Eerkes, A., Shou, W.Z., and Naidong, W., Liquid/liquid extraction using 96-well plate format in conjunction with hydrophilic interaction liquid chromatography– tandem mass spectrometry method for the analysis of fluconazole in human plasma, J. Pharm. Biomed. Anal., 31(5), 917, 2003. 78. Chen, Y.L. et al. Determination of ketoconazole in human plasma by highperformance liquid chromatography–tandem mass spectrometry, J. Chromatogr., B: Anal. Technol. Biomed. Life Sci., 774(1), 67, 2002. 79. Brignol, N. et al. High-throughput semi-automated 96-well liquid/liquid extraction and liquid chromatography/mass spectrometric analysis of everolimus (RAD 001) and cyclosporin a (CsA) in whole blood, Rapid Commun. Mass Spectrom., 15(12), 898, 2001. 80. Naidong, W. et al. Liquid chromatography/tandem mass spectrometric bioanalysis using normal-phase columns with aqueous/organic mobile phases—a novel approach of eliminating evaporation and reconstitution steps in 96-well SPE, Rapid Commun. Mass Spectrom., 16(20), 1965, 2002. 81. Chen, Y.L. et al. Simultaneous determination of hydrocodone and hydromorphone in human plasma by liquid chromatography with tandem mass spectrometric detection, J. Chromatogr., B: Anal. Technol. Biomed. Life Sci., 769(1), 55, 2002. 82. Shou, W.Z. et al. An automatic 96-well solid phase extraction and liquid chromatography–tandem mass spectrometry method for the analysis of morphine, morphine-3-glucuronide and morphine-6-glucuronide in human plasma, J. Pharm. Biomed. Anal., 27(1–2), 143, 2002. 83. Shou, W.Z. et al. A highly automated 96-well solid phase extraction and liquid chromatography/tandem mass spectrometry method for the determination of fentanyl in human plasma, Rapid Commun. Mass Spectrom., 15(7), 466, 2001. 84. Schuster, A. et al. Quantitative determination of the HIV protease inhibitor atazanavir (BMS-232632) in human plasma by liquid chromatography–tandem mass spectrometry following automated solid-phase extraction, J. Chromatogr., B: Anal. Technol. Biomed. Life Sci., 788(2), 377, 2003. 85. Yang, L. et al. Validation of a sensitive and automated 96-well solid-phase extraction liquid chromatography–tandem mass spectrometry method for the determination of desloratadine and 3-hydroxydesloratadine in human plasma, J. Chromatogr. B. Anal. Technol. Biomed. Life Sci., 792(2), 229, 2003. 86. Korfmacher, W.A. et al. HPLC-API/MS/MS: a powerful tool for integrating drug metabolism into the drug discovery process, Drug Discov. Today, 2, 532, 1997. 87. Korfmacher, W.A. et al. Cassette-accelerated rapid rat screen: a systematic procedure for the dosing and liquid chromatography/atmospheric pressure ionization tandem mass spectrometric analysis of new chemical entities as part of new drug discovery, Rapid Commun. Mass Spectrom., 15(5), 335, 2001. 88. Shou, W.Z. et al. Development and validation of a liquid chromatography/tandem mass spectrometry (LC/MS/MS) method for the determination of ribavirin in human plasma and serum, J. Pharm. Biomed. Anal., 29(1–2), 83, 2002. 89. Watt, A.P. et al. Higher throughput bioanalysis by automation of a protein precipitation assay using a 96-well format with detection by LC-MS/MS, Anal. Chem., 72(5), 979, 2000. 90. Berna, M. et al. Collection, storage, and filtration of in vivo study samples using 96well filter plates to facilitate automated sample preparation and LC/MS/MS analysis, Anal. Chem., 74(5), 1197, 2002.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 32/34

32

Using Mass Spectrometry for Drug Metabolism Studies

91. Sadagopan, N.P. et al. Investigation of EDTA anticoagulant in plasma to improve the throughput of liquid chromatography/tandem mass spectrometric assays, Rapid Commun. Mass Spectrom., 17(10), 1065, 2003. 92. Mallet, C.R., Mazzeo, J.R., and Neue, U., Evaluation of several solid phase extraction liquid chromatography/tandem mass spectrometry on-line configurations for high-throughput analysis of acidic and basic drugs in rat plasma, Rapid Commun. Mass Spectrom., 15(13), 1075, 2001. 93. Mallet, C.R. et al. Performance of an ultra-low elution-volume 96-well plate: drug discovery and development applications, Rapid Commun. Mass Spectrom., 17(2), 163, 2003. 94. Ackermann, B.L., Murphy, A.T., and Berna, M.J., The resurgence of column switching techniques to facilitate rapid LC/MS/MS based bioanalysis in drug discovery, Am. Pharm. Rev., 5(1), 54, 2002. 95. Wu, J.T., The development of a staggered parallel separation liquid chromatography/tandem mass spectrometry system with on-line extraction for highthroughout screening of drug candidates in biological fluids, Rapid Commun. Mass Spectrom., 15(2), 73, 2001. 96. Kerns, E.H. et al. Integrated high capacity solid phase extraction–MS/MS system for pharmaceutical profiling in drug discovery, J. Pharm. Biomed. Anal., 34(1), 1, 2004. 97. Cass, R.T. et al. Rapid bioanalysis of vancomycin in serum and urine by high-performance liquid chromatography tandem mass spectrometry using on-line sample extraction and parallel analytical columns, Rapid Commun. Mass Spectrom., 15(6), 406, 2001. 98. Higton, D.M., A rapid, automated approach to optimisation of multiple reaction monitoring conditions for quantitative bioanalytical mass spectrometry, Rapid Commun. Mass Spectrom., 15(20), 1922, 2001. 99. Whalen, K.M. et al. AutoScan: an automated workstation for rapid determination of mass and tandem mass spectrometry conditions for quantitative bioanalytical mass spectrometry, Rapid Commun. Mass Spectrom., 14(21), 2074, 2000. 100. Locker, K.L., Morrison, D., and Watt, A.P., Quantitative determination of L-775,606, a selective 5-hydroxytryptamine 1D agonist, in rat plasma using automated sample preparation and detection by liquid chromatography– tandem mass spectrometry, J. Chromatogr., B: Biomed. Sci. Appl., 750(1), 13, 2001. 101. Matuszewski, B.K., Constanzer, M.L., and Chavez-Eng, C.M., Matrix effect in quantitative LC/MS/MS analyses of biological fluids: a method for determination of finasteride in human plasma at picogram per milliliter concentrations, Anal. Chem., 70(5), 882, 1998. 102. Matuszewski, B.K., Constanzer, M.L., and Chavez-Eng, C.M., Strategies for the assessment of matrix effect in quantitative bioanalytical methods based on HPLCMS/MS, Anal. Chem., 75(13), 3019, 2003. 103. Mei, H. et al. Investigation of matrix effects in bioanalytical high-performance liquid chromatography/tandem mass spectrometric assays: application to drug discovery, Rapid Commun. Mass Spectrom., 17(1), 97, 2003. 104. Schuhmacher, J. et al. Matrix effects during analysis of plasma samples by electrospray and atmospheric pressure chemical ionization mass spectrometry: practical approaches to their elimination, Rapid Commun. Mass Spectrom., 17(17), 1950, 2003.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 33/34

Bioanalytical Assays in a Drug Discovery Environment

33

105. Mallet, C.R., Lu, Z., and Mazzeo, J.R., A study of ion suppression effects in electrospray ionization from mobile phase additives and solid-phase extracts, Rapid Commun. Mass. Spectrom., 18(1), 49, 2004. 106. Liang, H.R. et al. Ionization enhancement in atmospheric pressure chemical ionization and suppression in electrospray ionization between target drugs and stable-isotope-labeled internal standards in quantitative liquid chromatography/tandem mass spectrometry, Rapid Commun. Mass Spectrom., 17(24), 2815, 2003. 107. Muller, C. et al. Ion suppression effects in liquid chromatography–electrospray– ionisation transport-region collision induced dissociation mass spectrometry with different serum extraction methods for systematic toxicological analysis with mass spectra libraries, J. Chromatogr., B: Anal. Technol. Biomed. Life Sci., 773(1), 47, 2002. 108. Avery, M.J., Quantitative characterization of differential ion suppression on liquid chromatography/atmospheric pressure ionization mass spectrometric bioanalytical methods, Rapid Commun. Mass Spectrom., 17(3), 197, 2003. 109. Shou, W.Z. and Naidong, W., Post-column infusion study of the ‘dosing vehicle effect’ in the liquid chromatography/tandem mass spectrometric analysis of discovery pharmacokinetic samples, Rapid Commun. Mass Spectrom., 17(6), 589, 2003. 110. Jemal, M., Schuster, A., and Whigan, D.B., Liquid chromatography/tandem mass spectrometry methods for quantitation of mevalonic acid in human plasma and urine: method validation, demonstration of using a surrogate analyte, and demonstration of unacceptable matrix effect in spite of use of a stable isotope analog internal standard, Rapid Commun. Mass Spectrom., 17(15), 1723, 2003. 111. Jemal, M. and Ouyang, Z., Enhanced resolution triple-quadrupole mass spectrometry for fast quantitative bioanalysis using liquid chromatography/tandem mass spectrometry: investigations of parameters that affect ruggedness, Rapid Commun. Mass Spectrom., 17(1), 24, 2003. 112. Yang, L. et al. Investigation of an enhanced resolution triple quadrupole mass spectrometer for high-throughput liquid chromatography/tandem mass spectrometry assays, Rapid Commun. Mass Spectrom., 16(21), 2060, 2002. 113. Xu, X., Veals, J., and Korfmacher, W.A., Comparison of conventional and enhanced mass resolution triple-quadrupole mass spectrometers for discovery bioanalytical applications, Rapid Commun. Mass Spectrom., 17(8), 832, 2003. 114. Hsieh, Y. et al. High-performance liquid chromatography–atmospheric pressure photoionization/tandem mass spectrometric analysis for small molecules in plasma, Anal. Chem., 75(13), 3122, 2003. 115. Raffaelli, A. and Saba, A., Atmospheric pressure photoionization mass spectrometry, Mass Spectrom. Rev., 22(5), 318, 2003. 116. Yang, C. and Henion, J., Atmospheric pressure photoionization liquid chromatographic–mass spectrometric determination of idoxifene and its metabolites in human plasma, J. Chromatogr., A, 970(1–2), 155, 2002. 117. Xia, Y.Q. et al. Use of a quadrupole linear ion trap mass spectrometer in metabolite identification and bioanalysis, Rapid Commun. Mass Spectrom., 17(11), 1137, 2003. 118. Dethy, J.M. et al. Demonstration of direct bioanalysis of drugs in plasma using nanoelectrospray infusion from a silicon chip coupled with tandem mass spectrometry, Anal. Chem., 75(4), 805, 2003.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-01.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/9:04pm Page: 34/34

34

Using Mass Spectrometry for Drug Metabolism Studies

119. Kapron, J.T. et al. Quantitation of midazolam in human plasma by automated chip-based infusion nanoelectrospray tandem mass spectrometry, Rapid Commun. Mass Spectrom., 17(18), 2019, 2003. 120. Brotherton, H.O. and Yost, R.A., Determination of drugs in blood serum by mass spectrometry/mass spectrometry, Anal. Chem., 55(3), 549, 1983. 121. Shabir, G.A., Validation of high-performance liquid chromatography methods for pharmaceutical analysis. Understanding the differences and similarities between validation requirements of the US Food and Drug Administration, the US Pharmacopeia and the International Conference on Harmonization, J. Chromatogr., A, 987(1–2), 57, 2003. 122. Bajpai, M. and Esmay, J.D., In vitro studies in drug discovery and development: an analysis of study objectives and application of good laboratory practices (GLP), Drug Metab. Rev., 34(4), 679, 2002.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 35/82

Chapter 2 Drug Metabolism In Vitro and In Vivo Results: How Do these Data Support Drug Discovery? Thomas N. Thompson

2.1 2.1.1

Introduction Scope

The application of drug metabolism and pharmacokinetic (DMPK) principles to drug design is hardly a new concept. Throughout the past three decades, numerous reviews have documented examples of how DMPK data have influenced drug design [1–7]. Several recent reviews have put this concept in the context of current drug discovery in the new era of combinatorial chemistry and high-throughput screening (HTS) [8–18]. The purpose of this chapter is two-fold: (1) to summarize some of key points relating drug structure to DMPK properties that have been made by these earlier reviews, and (2) to review selected examples of new technologies that will facilitate the evaluation of DMPK properties as part of the lead optimization process. The emphasis of this review is on experimental techniques, particularly those that utilize LC–MS as the mode of analysis. Therefore, although so-called in silico techniques are making strides towards becoming a very important tool in the effort to optimize DMPK properties, they will not be reviewed here. The reader is referred to two excellent recent reviews for more 0-8493-1963-3/05/$0.00+$1.50 ß 2005 by CRC Press

Copyright © 2005 CRC Press, LLC

35

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 36/82

Using Mass Spectrometry for Drug Metabolism Studies

36

information on in silico methods [19, 20]. Likewise, other kinds of metabolism studies which address the potential for drug interactions, including enzyme inhibition, enzyme induction and enzyme mapping studies (also known as reaction phenotyping), have recently been reviewed elsewhere [21, 22], so they will not be treated in any detail here. 2.1.2

Perspective on modern drug discovery

The process by which drugs are developed from discovery to regulatory approval is inherently inefficient. By one estimate, 90% of all drugs in clinical development fail to make it to the market place [23]. As shown in Figure 2.1, among the reasons for this are poor pharmacokinetics (40%), poor clinical efficacy (30%), toxicity (animals or humans, 20%) or other unspecified causes (10%). Given the inherent inefficiency of the development process, research programs have a mandate to continually improve the discovery process to ensure a higher quality in the prospective drugs that make it through to clinical development, thereby improving the ultimate rate of successful submission [24]. One solution is the ‘‘sheer numbers’’ approach whereby increasingly more compounds are driven through the process. While this approach presumably results in more drugs with suitable clinical efficacy surviving to NDA submission, it does little to improve the efficiency of this process. Moreover, it does nothing to address the failure rate accounted for by PK and toxicity factors. Thus, it has been recognized that the ability to improve the DMPK profiles of leads is a strategic necessity in order to help minimize the number failed leads [8]. Although it is understandable that many drugs fail because of toxicity or lack of efficacy, it is not immediately obvious why in Prentis’ study the single largest factor for failure in clinical development was due to poor

Figure 2.1

Common reasons for drugs to fail in clinical trials [8].

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 37/82

Drug Metabolism In Vitro and In Vivo Results

37

pharmacokinetics. One possible explanation is that toxicity or lack of efficacy is easier to detect in preclinical development. Ironically, another explanation may lie in the previously mentioned improvements in the drug discovery process. As the endeavor to find new drugs progressed from empirical discovery to rational design, a disconnect began to develop between the intrinsic activity of a drug towards its biochemical target in vitro and biological activity in vivo. The best explanation for this is that, in empirical drug discovery, drugs are discovered after they are observed to be effective in an animal model of disease. Of necessity, this demanded at least some level of a useful pharmacokinetic profile. However, the desire for a more rational approach drove the demand for ever-increasing amounts of data in order to derive structure activity relationships. In turn, this led to an increasing reliance on in vitro methods to provide the amount of data with the appropriate cycle time to feed the iterative design process [11]. To further complicate the picture, chemists either did not yet appreciate the importance of pharmacokinetics for in vivo activity, or, if they did, were resigned that little could be done to influence pharmacokinetic properties. As a result, too many drug candidates were developed based solely on their ability to inhibit an enzyme or interact with a receptor with optimized in vitro affinity, only to fail in the clinic because of unfavorable pharmacokinetic parameters [25]. 2.1.3

A rational approach to early screening for DMPK properties

Drug discovery teams today have an impressive array of biological targets, biochemical techniques to refine and exploit those targets and synthetic, analytical and computational chemistry tools to design and prepare new molecules. However, it is only comparatively recently have we been able to automate pharmacokinetic screening to evaluate many potential drug candidates in parallel [8, 9, 11, 26, 27]. For the first time, significant tools are now available to help define DMPK properties either at the very point of drug design, or at least during lead optimization. The availability of these tools has led to the realization that it is now feasible to optimize the pharmacokinetic properties of drug candidates with rational application of DMPK principles. For example, an in vivo efficacy problem (lack of potency or short duration of action) can often be redefined as a pharmacokinetic problem (e.g., low oral bioavailability, short plasma half-life) in relevant in vitro or in vivo models. Of course, in order to use this information to solve the problem, one has to assign selection criteria such as threshold intrinsic clearances (CLint), inhibition constants (Ki or IC50) or permeability coefficients (Papp) for a given series of compounds. While this takes extra time and other resources, it is obviously a far preferable position than to have to fail molecules with poor DMPK properties later in development. As stated by Tarbit and Berman, it is better to ‘‘fail fast, but fail cheap’’ [28]. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 38/82

Using Mass Spectrometry for Drug Metabolism Studies

38

2.1.3.1

Strategic considerations for incorporating early DMPK data

Powerful new high-throughput techniques notwithstanding, without a careful, comprehensive strategy for their use, there is a danger that discovery scientists will be inundated with more information than they can use in a timely, rational manner. The same conclusion has been reached by other authors who have recently written about opportunities to bring DMPK data into the discovery process at an earlier point [11]. For example, Rodrigues called for a rational HTS strategy based on automation, validation and integration of in vitro absorption–metabolism (AM) models and database management (AVID) [26, 27]. Tarbit and Berman make a similar point when they refer to implementation of a strategy with potentially several iterations through a ‘‘virtuous cycle’’ of drug design, automated screens, data capture and data analysis [28]. This iteration allows optimization of drug design with respect to DMPK properties as well as biological activity. There is a trade-off when using pharmacokinetics to select drug candidates. The time spent optimizing PK properties may come at the expense of time spent optimizing affinity for the primary target. Chemists may need to accept hand-in-mitten fits between their synthetic ligands and their targets rather than hand-in-glove fits. As a result, we may learn less about special interactions between ligands and receptors that might lead to high-affinity ligand–receptor complexes, but the payoff will be in improved activity in vivo [25]. Eddershaw and Dickins [21] discussed at some length the question of whether the resources required to apply high-throughput techniques to optimizing PK properties is worth the effort. As they point out, there has been some debate over whether high-throughput DMPK screening is even a good idea. The charge is that such approaches ‘‘de-intellectualize’’ the process of candidate optimization and should therefore be resisted. However, these authors maintain that this viewpoint fails to appreciate the enormous opportunities provided by such systems for increasing our understanding of the fundamental physicochemical and enzymatic factors that govern drug metabolism. If we accept the challenge to study large, diverse compound sets using well-defined and controlled methods, this in turn will provide reliable data that can be used to develop computational models that describe various aspects of drug metabolism. In this way, the drug metabolism scientist can have a much greater ‘‘intellectual’’ influence on the drug design process than has hitherto been possible. 2.1.3.2

Selection of the right drug metabolism tools suitable for early DMPK studies

If the first major decision is one of strategy for using DMPK data, the second major decision involves selection of the proper tool(s) at the proper time [8, 11]. Because many of these techniques have been recently discussed elsewhere [16, 29, 30], few experimental details will be presented here. Table 2.1 serves as a reminder that a continuum of techniques is available ranging from theoretical Copyright © 2005 CRC Press, LLC

Human in vivo

Physiological relevance

Compound throughput

Time needed

Cost

Comment

Most

Lowest

Most

Most

Least

Highest

Least

Least

Need regulatory approval, toxicology, formulation and bulk drug Still considered best predictor, yet expensive and increasingly controversial Time-consuming, requires animal or human donor Generally considered reliable, in vitro–in vivo correlations are improving, immortal cell lines available Generally considered reliable, in vitro–in vivo correlations are improving, immortal cell lines available Requires, animal or human donor, but enables higher throughput Now readily available, necessary for today’s high throughput assays

Animal in vivo Isolated whole organ Cellular Subcellular Isolated enzyme/receptor Recombinant enzyme/receptor

39

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 39/82

Mode

Drug Metabolism In Vitro and In Vivo Results

Table 2.1 Comparison of the predictive value of various models for metabolic stability studies

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 40/82

Using Mass Spectrometry for Drug Metabolism Studies

40

calculations to in vivo studies in animals or humans. Among these techniques, one intuitively realizes a gradient in the degree of confidence and level of validation. As a consequence, it is reasonable to believe that the most directly applicable and most highly validated information comes from the animal or human studies. However, these are also the most expensive, time-consuming experiments with the least capacity for compound throughput. In marked contrast, theoretical calculations are ultimately the cheapest experiments with potentially the highest throughput and could be applied at the earliest point in the process, yet they are the least validated. Luckily, a single choice of which technique to use does not have to be made. A series of studies can be rationally chosen to provide an appropriate degree of information at every step of the way [8, 11]. 2.1.3.3

The importance of integration of early DMPK data with other HTS data

Although multiple tools/screens are available, the decision to employ a screen within a drug discovery project must come from a rational appraisal of the project requirements, rather than simply because that screen is capable of providing the needed throughput. Furthermore, the point must be made that any improvements in throughput are worthless unless they are supported by rigorous and continued validation of the overall screen performance [21]. The integration element of rational HTS is very critical and ties together a number of issues (Figure 2.2). It is not sufficient to conduct one kind of DMPK screen without integrating them with other DMPK screens and with HT

Figure 2.2

Integration of in vitro ADME data with other HT screens in the discovery process.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 41/82

Drug Metabolism In Vitro and In Vivo Results

41

pharmacology screens. In other words, solving a metabolic stability problem may not necessarily lead to a compound with an overall improvement in activity or even PK properties if the compounds with improved metabolic stability have absorption problems [11]. 2.1.3.4

The evolving role of DMPK studies in drug design

By the end of the 1980s, it was becoming common practice to obtain PK/ metabolism data, if not in the design stage, then at least before the compound(s) advanced far into development. Initially, the PK/metabolism data collected was predominantly whole animal data. As shown in Table 2.1 there is a natural inclination to this approach. In general, while whole animal studies are considered more physiologically relevant, they are also more expensive and time consuming than in vitro studies. Gradually, as the correlations to in vivo data became evident, in vitro metabolism (and other DMPK) data have become more widely accepted. Because in vitro studies generally allow for higher throughput at less cost than in vivo studies, they have now become an important part of modern drug discovery [8, 11]. Today, drug discovery is a highly driven, fast moving and iterative process. Medicinal chemists are constantly refining structural features in search of the elusive ‘‘ideal’’ molecule. In order to have an impact, metabolism data must be generated and interpreted rapidly, often in a matter of days or, at most, weeks. Usually, several iterations of metabolism studies and molecular redesign are necessary. Furthermore, experience has shown that in the absence of timely, real, metabolism data, the chemists will resort to the use of empirical data, i.e., structure–metabolism rules, literature precedent, or even anecdotal information. These realities dictate that minimal experimental design, rapid throughput analysis, and expedient data calculation/management are imperative [11]. Ideally, at the earliest stages, the so-called lead identification or hit finding stage, the chemists need to know the metabolically vulnerable moieties within a molecule. This enables them to know what changes they can make to impart improved DMPK properties. Once chemists are armed with this information, they can embark on a lead optimization campaign. At this point, it quite helpful to get feedback on the effect that various structural changes have on metabolic stability even as the pharmacological activity is being optimized. The challenge for the metabolism groups that support drug discovery is to generate data that are rigorous enough to make reliable assessments of modifications the chemists should make. Yet, at the same time, acquisition of the data should not be so rigorous as to be untenable for a large number of compounds or impede multiple iterations of the design process [11].

2.2

Pharmacokinetic Principles used in Drug Discovery

Medicinal chemistry now has decades of extensive experience in understanding structure–activity relationships with the 500 or so favorite targets of enzymes, Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 42/82

Using Mass Spectrometry for Drug Metabolism Studies

42

receptors and other macromolecules. Any progress that will be made in optimizing DMPK properties in the drug design stage will rely on the generation of a comparable understanding of the relation of absorption, distribution, metabolism, and excretion (ADME) properties to chemical structure. By understanding the factors involved in the interaction with membranes and drug metabolizing enzymes or transporter proteins, medicinal chemists can capitalize on experience they already possess [8]. A second key point to make is that both the pharmacokinetic and pharmacodynamic properties are linked to the molecular properties of drugs. Predictably, each usually has its own unique structure–activity relationship. Experience tells us that modification of the structure to improve absorption, metabolic stability or distribution may, and often does, adversely impact intrinsic pharmacological activity and vice versa [2, 6]. Thus, the chemist must think in terms of the optimal intersection of multiple parameters to ultimately ensure activity in vivo. Some of the key factors and relationships between structure and DMPK properties have been assembled from existing reviews and selected examples from primary literature and are summarized below. The reader is directed to several of these excellent review articles and the references therein for more detail [1–3, 5, 6, 31–33]. As our understanding of drug disposition at the theoretical and experimental levels improves, a pattern begins to emerge that permits some degree of prediction of the two arguably most relevant pharmacokinetics properties to pharmacologic activity, i.e., bioavailability (F) and half-life (t1/2). As Figure 2.3 indicates, these two key properties are related to more basic PK properties of fraction absorbed ( fa), clearance (CLsys) and volume of distribution (Vd). These intermediate properties are, in turn, derived from basic drug properties that can be measured in vitro in a modern drug metabolism laboratory [8, 13]. 2.2.1

Oral bioavailability

Oral bioavailability (F ) is important because, along with intrinsic pharmacological activity, it determines the dose level required to achieve the desired

Figure 2.3 properties.

The relationship between early DMPK screening data and pharmacokinetic

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 43/82

Drug Metabolism In Vitro and In Vivo Results

43

effect. Oral bioavailability of drugs is defined as the fraction of the ingested dose that is available to the systemic circulation after both absorption and first pass clearance. Mammalian anatomy dictates that during and after absorption, the drug encounters the intestinal wall, liver and lung, all of which may metabolize or excrete the drug before it reaches systemic circulation. Thus, oral bioavailability can be estimated as F ¼ fa fG fH fL ,

ð2:1Þ

where fa is the fraction absorbed across the intestinal wall, and fG fH fL is the product of the fractions escaping clearance by the gastrointestinal tract, liver and lung. Generally speaking, intestinal and liver metabolism are the major determinants of first pass clearance and are usually the only tissues modeled in DMPK screens [10, 12]. Figure 2.4 depicts the anatomical arrangement of intestine and liver in first pass clearance and illustrates the processes of permeation, efflux and metabolism, all of which will be discussed later in this chapter. An alternative estimate of bioavailability may be obtained as the ratio of the systemic clearance (CLsys) to the apparent oral clearance (CLoral),

Figure 2.4

Anatomical barriers to drug bioavailability.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 44/82

Using Mass Spectrometry for Drug Metabolism Studies

44

as follows [10]: F ¼ CLsys =CLoral :

2.2.2

ð2:2Þ

Half-life

The other key property, half-life (t1/2), is defined as the time needed to clear the blood compartment of 50% of the initial drug level. The half-life of any drug is related to its apparent volume of distribution (Vd) and its systemic clearance (CLsys) as: t12 ¼ 0:693ðVd =CLsys Þ:

ð2:3Þ

Thus, the half-life of any drug is a function of blood and tissue binding of the drug as well as its total clearance and is a derived parameter from CLsys and Vd [2, 12]. 2.2.3

Fraction absorbed

Fraction absorbed ( fa) is the fraction of dose that traverses from the luminal to the serosal side of the intestinal wall, taking into account both unchanged and metabolized drug. Fraction absorbed can be computed from PK determinations of clearance and oral bioavailability using the following relationship: fa ¼ F=ð1
CLH =QH Þ,

ð2:4Þ

where fa is the fraction absorbed, F is the oral bioavailability, CLH is the hepatic clearance, and QH is the hepatic blood flow in that species [13]. Methods to determine fraction absorbed can range from simple permeability studies in vitro to measurements across the gut wall in situ or, ultimately, to in vivo comparison of total radioactivity profiles after intravenous and oral administration. 2.2.4

Clearance

Clearance is defined as the volume of blood that must be cleared of drug in a unit of time in order to account for the rate of drug elimination. Thus, clearance is the ratio of elimination rate of the drug to the drug concentration in blood entering the organ. It is well known that total systemic clearance (CLsys) of a drug is estimated as the ratio of dose to area under the curve (AUC) following intravenous administration of the drug [12, 13]: CLsys ¼ doseðivÞ =AUCðivÞ :

Copyright © 2005 CRC Press, LLC

ð2:5Þ

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 45/82

Drug Metabolism In Vitro and In Vivo Results

45

The total clearance is the sum of all individual organ clearances that occur in sequence: CLsys ¼ CLG þ CLH þ CLr ,

ð2:6Þ

where CLG is clearance by the gut wall, CLH is hepatic clearance and is the sum of liver metabolism and biliary excretion, and CLr is renal clearance. If there is significant clearance by lung tissue, then an extra CL factor must also be added to account for lung clearance. 2.2.5

Volume of distribution

The third intermediate PK property, volume of distribution (Vd), is a measure of the extent of drug distribution and is determined by the binding of the drug in plasma as well as tissues. Volume of distribution is the proportionality constant relating the drug concentration in blood or plasma to the amount of drug in the body and is affected by plasma protein binding: Vd ¼ Vp þ Vt ð fp =ft Þ,

ð2:7Þ

where Vd is the volume of distribution, Vp is the plasma volume, Vt is the extravascular tissue space volume, fp is the unbound fraction in plasma and ft is the unbound fraction in tissues [2, 7, 13].

2.3

Absorption

By far, the oral route is the primary route of administration for most drugs [34]. Consequently, absorption from the gastrointestinal tract (GIT) is an important determinant of drug action. In order to be absorbed, a drug must undergo transit through the GIT, dissolution from a tablet form, diffusion through an aqueous environment, and finally, permeation through the intestinal wall [6, 13, 18]. A drug can permeate through the intestinal wall either between the junction of intestinal cells (paracellular) or through the intestinal cells (transcellular). Transcellular permeability may occur by passive diffusion through intestinal cell membranes, in which case it is governed by the physiological environment of the GIT (intestinal motility and pH) and the physicochemical properties of the drug (molecular weight, polar surface area, lipophilicity and pKa). Alternately, diffusion may be due to active transport through the intestinal cells via one of several transporter proteins. In that case, permeability is governed by structure–activity relationships particular to the given transporter. Lipinski et al. have summarized several properties which appear to be common to compounds which are well absorbed [35]. According to the Lipinski rule of five, as these properties have come to be known, well absorbed Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 46/82

Using Mass Spectrometry for Drug Metabolism Studies

46

compounds typically have a molecular weight <500, log P<5 and have fewer than five H-bond donors and 10 H-bond acceptors. Generally speaking, when exceptions to these rules occur, active transport may be involved. 2.3.1

Physicochemical properties

As mentioned, passive transport is a major mechanism of absorption and is driven by physicochemical properties such as solubility, pKa and lipophilicity. In a recent review, Kerns has summarized the literature concerning recent attempts to profile drug candidate’s physicochemical properties during early discovery phases [36]. High throughput methods to measure solubility as well as other properties such as permeability, lipophilicity, pKa, stability and integrity are described and compared in this article. Given the rapid pace and high numbers of compounds in the discovery process, many attempts have been made to miniaturize classical dissolution tests used for pharmaceutical formulations. Ideally, these tests should consume a few milligrams of powder and should allow the evaluation of the influence of proteins, bile acids, for example, in the media. In addition to the intrinsic solubility values used mainly for ranking purposes, dissolution profiles over time or as a function of the pH should also be generated because these are more physiologically relevant to the dynamics of the GIT [18]. Recent literature reports for high throughput methods to measure solubility include a small-scale shake flask method [37], turbidity measurements [35] and nephelometry [38]. Lipophilicity is the ability of a compound to dissolve in a lipid environment. Historically, it has been determined by measuring the equilibrium solubility of a compound in a lipophilic phase such as octanol to its solubility in aqueous media. It is usually reported as either log P, which is the intrinsic partitioning of unchanged drug between octanol and water, or else as log D, which is the distribution at a specific pH, usually pH 7.4. In a high throughput format, lipophilicity has been measured by a modified shake flask method, by potentiometric titrations and by correlation of log D with retention time in reverse phase HPLC [36]. The latter method is typified by the work of Lombardo et al. in which they describe a reversed phase HPLC method for the determination of the octanol–water distribution coefficients at pH 7.4 (as log values) for neutral and basic drugs, which they referred to as E log D7.4 [39]. 2.3.2 2.3.2.1

Mechanisms of permeability Passive diffusion

As mentioned above, passive diffusion is influenced by physicochemical determinants such as (1) lipophilicity, (2) intrinsic aqueous solubility, (3) surface charge and (4) molecular weight (MW) [10]. In general, aqueous solubility is inversely related to lipophilicity. Compounds with log D7.4<0 are readily dissolved in the aqueous environment (i.e., hydrophilic), but will Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 47/82

Drug Metabolism In Vitro and In Vivo Results

47

progressively rely on the slower paracellular mechanism as the log D7.4 decreases below 0. At the other extreme, compounds with log D7.4 greater than 3 are considered to be highly lipophilic and hence may show poor dissolution resulting in poor bioavailability. In contrast to these extremes, drugs with log D7.4 values above 0 but less than 3 are considered to be have an optimal balance between lipophilicity and hydrophilicity and usually will be rapidly absorbed by the transcellular route [6, 10]. Another common factor that has long been thought to favor passive diffusion is relatively low molecular weight (MW), as seen by the MW distribution of all marketed drugs. The increased absorption of compounds of low MW can be explained, in part, on the basis of passive diffusion principles [10]. 2.3.2.2

Active transport

If drug absorption were facilitated by only by passive diffusion, then absorption should be well predicted by physicochemical parameters as described above and only lipophilic, un-ionized drugs would be absorbed. However, there are consistent exceptions to those rules and both direct and indirect evidence points to the existence of active transport mechanisms to facilitate absorption. A review by Tsuji and Tamai [40] provides an excellent summary of carrier-mediated intestinal absorption of amino acids, oligopeptides, monosaccharides, monocarboxylic acids, phosphate, bile acids and several water-soluble vitamins across brush-border and basolateral membranes. While these active transporters undoubtedly evolved to aid the body in absorption of essential nutrients, absorption of many drugs can also be attributed, at least in part, to these systems (Table 2.2) [41–64]. 2.3.2.3

Efflux

In addition to active transport in the absorptive (mucosal to serosal) direction, it is now evident that active transporters exist that can limit absorption by causing the efflux of drugs in the reverse (serosal to mucosal) direction. One such transporter, the multidrug resistance gene product P-glycoprotein (P-gp), was initially discovered because it is expressed at high levels in some cancers cells and causes the net efflux of certain chemotherapeutic agents out of the cells, rendering them ineffective. However, it is now known that P-gp exists in many normal tissues, including the canalicular domain of hepatocytes, kidney (proximal tubule), small intestine, colon, adrenal glands, and the capillary endothelium of the brain and testes [65]. It is the expression of P-gp in the intestinal brush-border membrane of the small intestine that leads to net secretion of some drugs in the serosal-to-mucosal direction, serving as a secretory detoxifying mechanism and as a part of the absorption barrier in the intestine [40]. Because of its ubiquitous nature in so many other tissues, P-gp also plays an important role in drug distribution and excretion, so it will be considered again later in this review. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 48/82

Using Mass Spectrometry for Drug Metabolism Studies

48

Table 2.2 Transporter proteins involved in intestinal absorption of drugs Transporter

Experimental model

Amino acid

Rat intestinal perfusion

Oligopeptide

Caco-2 cells Rat, rabbit and human transporter expressed in Xenopus laevis oocytes

Glucose

Rat everted jejunum

Monocarboxylic acid

Caco-2 cells

Phosphate

Rat intestinal brush border membrane vesicles Rat intestinal preparation

Compound

Reference

Gabapentin a-Methyl dopa l-Dopa Baclofen d-cycloserin Cefadrine Cefadroxil

41 42, 43 44 45 46 47, 48 49

Ceftibuten Captopril Enalopril Lisinopril Renin inhibitor S 86 3390 Bestatin Thrombin inhibitors p-Nitrophenol-b-dglucopyranoside Salicylic acid

50 51 52 53 54, 55 56 57 58 59, 60, 61

Benzoic acid Pravastatin Foscarnet

60 62 63

Foscarnet

64

Adapted from Reference 40.

Drug substrates of P-gp include cyclosporin A, verapamil, quinidine, erythromycin, terfenadine, fexofenadine and HIV-1 protease inhibitors [66–69]. This represents a chemically diverse set of compounds, and it is evident that the structure–activity relationships for P-gp are still being determined. It is known that P-gp has significant substrate overlap with CYP 3A4, although not all CYP 3A substrates are P-gp substrates and vice versa [65]. In order to design drugs which are not going to have limited absorption due to P-gp efflux, the safest approach is probably to avoid interaction altogether. Thus, there is a need for a reliable, high-throughput screen to evaluate compounds as P-gp substrates. To this end, Polli et al. tested 66 compounds in the high-throughput ATPase and calcein AM assays, and compared the results to those from a medium throughput monolayer efflux assay [70]. They determined that the efflux assay is more reliable for low and moderate Papp compounds and is the method of choice for evaluating drug candidates despite moderate throughput and reliance on liquid chromatography with tandem mass spectrometry. 2.3.3

Experimental models

Prediction of the key structural features that control human intestinal permeability has been a major area of research for many years. A range of Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 49/82

Drug Metabolism In Vitro and In Vivo Results

49

different models of varying complexity have been used to study and optimize absorption [13]. Three of the more common models used for higher throughput assays are summarized below. Over the past few years some groups have developed a purely physical– organic model for absorption based on a phospholipid membrane soaked pad separating an aqueous donor and receiver compartment, the parallel artificial membrane permeation assay (PAMPA) screen [71]. PAMPA is based on a multi-well microtiter plate technology and allows reasonable throughput, although it lacks similarity to natural membranes in that it does not possess pores or active transport mechanisms. It enables fast determination of the trends in the ability of the compounds to permeate membranes by passive diffusion and is thus suited for the screening of large libraries [12]. Quantitative structure activity relationships (QSARs) based upon the PAMPA assay produce good data for this mechanism of absorption [13]. Cell lines are more physiologically relevant than the PAMPA assay in that they also express transporters and, hence, can measure both active and passive transport. The most popular and extensively characterized is the Caco-2 cell line, derived from human adenocarcinoma. Because it is derived from human colonic cells, its morphology is thought to be a reasonable model of human small intestinal permeability. Caco-2 cell monolayers have been shown to express a variety of active transporters relevant to gut absorption including the dipeptide transporters such as PepT1 and efflux proteins such as P-gp [13, 18, 72, 73]. Figure 2.5 demonstrates that permeability to Caco-2 cell monolayers provides a good correlation with in vivo absorption in humans [73]. Caco-2 cells have some disadvantages, including a 21-day culture period. To overcome these limitations, the use of Madin–Darby canine kidney (MDCK) cells as an alternate cellular model for assessing intestinal epithelial drug transport has been reported [74]. Like Caco-2 cells, MDCK cells differentiate into columnar epithelium and form tight junctions on semipermeable

Figure 2.5

Correlation between caco-2 permeability and in vivo human absorption data [73].

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 50/82

Using Mass Spectrometry for Drug Metabolism Studies

50

membranes. Unlike Caco-2 cells, transporter proteins are not expressed in the simple primary culture. Nevertheless, Irvine et al. compared permeability data from MDCK cells with that obtained from Caco-2 cells for 55 drugs [74]. These data show that the permeability of passively absorbed compounds was similar to that obtained from Caco-2 cells. The major advantage of the use of MDCK cells is its ability to assess reliable permeability estimates after only 3 days of culture rather than the 21 days required by Caco-2 cells. Thus, some groups have concluded that the ease of handling of MDCK cells with shorter culture times (7–14 days) and their low expression of transporter proteins and metabolizing enzymes, make them perfect for evaluation of permeability of passively absorbed compounds [12].

2.4

Clearance

Like absorption, clearance of drugs is also determined by both compoundspecific physicochemical properties, physiological determinants, such as organ blood flow and tissue volume, and pharmacokinetic parameters, such as dose and route of administration. However, unlike drug absorption, which can be improved by different formulation strategies, intrinsic clearance cannot generally be modified unless the structure of the molecule itself is changed. In other words, to alter a drug’s clearance behavior, a new analog must be designed [2, 8, 10, 11]. As shown earlier, clearance is a central parameter influencing both bioavailability and half-life [13]. As such, predictive rules governing clearance derived from theoretical models would be immensely useful to guide structurebased drug design to ensure in vivo efficacy. However, probably because of the relative contribution of enzymatic processes to overall clearance, predictive models have had limited success to date. Nevertheless, limited success in predicting structure–activity relationships for clearance has been achieved within narrowly defined classes [10]. As described earlier, total clearance is the sum of all individual organ clearances that occur in sequence. Although all organs can contribute to clearance by virtue of either metabolic or excretory capacity, generally speaking, metabolism by the intestine and liver, together with biliary and renal excretion, are the major determinants of clearance. 2.4.1 2.4.1.1

Metabolic clearance Clearance concepts

In the context of drug discovery support, metabolic clearance is often referred to as metabolic stability. Either way, the terms describe the rate and extent to which a molecule is metabolized. A molecule that is rapidly and extensively metabolized is said to have a low degree of metabolic stability. Medicinal chemists have come to understand that low metabolic stability can be Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 51/82

Drug Metabolism In Vitro and In Vivo Results

51

a contributing factor to undesirable pharmacodynamic properties, such as poor oral efficacy or short duration of action. By now, the theoretical basis for this intuitive understanding has been thoroughly evaluated and well documented. As illustrated in Figure 2.3, the ability to evaluate metabolic stability of numerous analogs early in the discovery process, together with the ability to evaluate absorption potential improves the chances of selecting a molecule with good in vivo activity. Perhaps the first practical attempt to relate in vivo pharmacokinetics to in vitro drug metabolism was reported by Rane et al. [75]. Using the concept of intrinsic metabolic clearance (CLint), these authors demonstrated in vitro metabolism rates for a selected set of model substrates correlated well with hepatic extraction ratios determined from isolated perfused rat livers. More recently, the concept of in vitro–in vivo correlations has been systematically reviewed [76–80]. The pivotal concept in these correlations is that of CLint, which is related to parameters that can be measured from in vitro metabolism experiments. According to Houston [76, 77], intrinsic clearance is defined as the proportionality constant between drug concentration at the enzyme site (Ce) and rate of metabolism (v0): v0 ¼ CLint  Ce :

ð2:8Þ

Rearranging this equation leads to v0 =Ce ¼ CLint :

ð2:9Þ

From the Michaelis–Menten relationship for enzyme-catalyzed reactions, the rate of metabolism is related to concentration at the catalytic site, maximum velocity of reaction (Vmax) and a constant known as the Michaelis constant (Km) which, in practical terms, is defined as the substrate concentration at half maximal velocity: v0 ¼ ðVmax Ce Þ=ðKm þ Ce Þ:

ð2:10Þ

When, Ce  Km, Equation (3) reduces to v0 ¼ Vmax Ce =Km :

ð2:11Þ

By rearrangement of terms, this becomes v0 =Ce ¼ Vmax =Km :

ð2:12Þ

Because v0/Ce ¼ CLint then CLint ¼ Vmax =Km :

Copyright © 2005 CRC Press, LLC

ð2:13Þ

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 52/82

52

Using Mass Spectrometry for Drug Metabolism Studies

Figure 2.6 Relationship of in vitro intrinsic clearance in microsomes or hepatocytes to in vivo intrinsic clearance [76].

Thus, when measured under appropriate conditions, a simple relationship can be defined between a property related to in vivo kinetics, CLint, and two parameters which can easily be measured in vitro, Km and Vmax. The consensus is that reasonable correlations between in vivo pharmacokinetic properties and parameters derived from in vitro metabolism studies are possible (Figure 2.6). However, for good correlation, it is imperative that careful attention is paid to appropriate experimental design in the collection of the in vitro data as well as appropriate extrapolation to approximate in vivo conditions [76, 77]. Recently, the principles reviewed above were used by a group who systematically made correlations between a large number of compounds for which clinical PK data were available with properties they could derive from in vitro experiments. A unifying concept for their work was the prediction of human clearance from CLint data determined from in vitro metabolism experiments [77]. The authors opted to use in vitro half-life method to Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 53/82

Drug Metabolism In Vitro and In Vivo Results

53

determine CLint, which is shown in Equation 2.14: CLint ¼ 0:693wL =t12 mL fu ,

ð2:14Þ

where wL is the liver weight, mL is the amount of liver in the incubation, t12 is the half-life of the in vitro incubation and fu is the fraction unbound to microsomal protein. The in vitro half-life was determined by incubating a given drug with liver subcellular preparations for an appropriate period and measuring the disappearance of parent drug. Half-life was determined by plotting ln% remaining vs time, then measuring the slope of this plot: t12 ¼ 0:693=slope:

ð2:15Þ

This approach has the advantage that only a single substrate concentration needs to be used, so long as the concentration is kept as low as possible given the detection limits of the analytical method. The Pfizer workers have reported that so long as [S]/Km is 1 (where [S] is the concentration of substrate in the incubation and Km is the apparent Michaelis constant), the CLint measured will be within 90% of the actual CLint as measured by more detailed experiments [81]. This is a powerful tool because, when coupled with a high-throughput analytical method, this approach lends itself to determination of in vitro CLint for a large number of individual compounds. 2.4.1.2

Relationship of metabolic clearance to physicochemical properties

Metabolic clearance is influenced by passive diffusion through cell membranes to the site of the metabolizing enzymes. This diffusion, in turn, depends on molecular properties such as lipid/water solubility and degree of ionization [6, 8, 11]. However, once at the enzyme site, metabolic clearance is also further influenced by other aspects of molecular structure, including geometric features and stereoelectronic properties. Because of the involvement of enzyme catalysis, there is a further element of complexity due to the existence of both substrate and product selectivity. This selectivity can be viewed in terms not only of which reaction among many possibilities is catalyzed, but also where they occur among many possibilities (regioselectivity) [2]. A great deal can be understood about metabolism by considering general chemical principles related to the physical properties of drugs which, in turn, are a consequence of their structure. Several of these physical principles are considered below. 2.4.1.2.1

Lipophilicity

The fact that binding or transport processes influence metabolism probably accounts for the high degree of correlations between lipophilicity and metabolism, especially phase I metabolism. Often, variability in metabolism Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 54/82

Using Mass Spectrometry for Drug Metabolism Studies

54

within a series, whether in vitro or in vivo, can be attributed to variation in lipophilicity [2]. The octanol–water partition coefficient (log P, or log D7.4) has been the most convenient measurement of lipophilicity and has been used extensively to correlate with metabolism rates [6]. 2.4.1.2.2

Ionization

Apart from lipophilicity, another important general structural property for metabolism such as that catalyzed by cytochrome P450 is the presence of ionizable functions. First of all, the presence of ionizable groups affects net lipophilicity. For that reason, log D7.4 of the molecule is perhaps more a more useful parameter than log P because it incorporates both lipophilicity and degree of ionization at the physiologically relevant pH 7.4. Ionization is also important because the ionized group may have a key role in binding to CYPs and thus have an effect on the regioselectivity of metabolism [6]. 2.4.1.2.3

Electronic properties

Electronic properties may influence metabolism in at least two different ways. First, electronic factors can affect binding of substrates to metabolizing enzymes just as they do with binding to other biological receptors. Second, electronic factors can influence the catalytic step of the interaction. For example, there is a slightly larger electron density in sp3-hybridized carbon atoms in benzylic, allylic or penultimate positions, or in positions alpha to heteroatoms, which probably explains why these sites are favorite targets of hydroxylation [2]. Another example is the observation that by substituting aromatic rings with strongly electron withdrawing groups (e.g., CF3, SO2NH2, SO
3 ), oxidation can be reduced or even blocked. Finally, the observation that glutathione conjugation of para substituted 1-chloro-2-nitrobenzene derivatives was correlated with their Hammett resonance
-values (a measure of their electrophilicity) is also evidence of the importance of electronic effects [2]. 2.4.1.2.4

Configuration and conformation

The effect of stereochemistry on the outcome of metabolism is well documented. This effect includes substrate specificity (i.e., substrates with different stereochemistry proceed to products of different stereochemistry), as well as product specificity. The degree of stereoselectivity ranges from moderate to practically complete whereas examples of lack of at least some degree of stereoselectivity are rare. Even when the substrate is achiral, stereoselective formation of metabolites can be observed, a phenomenon known as enantioselectivity. For example, in many drugs, the methylene group is frequently a center of prochirality, and the enzymatic reaction can discriminate between the two enantiotopic or distereotopic hydrogens [2]. Unlike configurational factors (i.e., stereochemistry), the role of conformational factors in drug metabolism is much less studied. What knowledge we do Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 55/82

Drug Metabolism In Vitro and In Vivo Results

55

have usually comes by inference from differing outcomes observed when a molecule of constrained conformation is compared its corresponding analog with free rotation. Nevertheless, conformational factors may play a subtle yet decisive role in biotransformation and must be taken into account in relevant cases for a proper assessment of structure–metabolism relationships [2]. 2.4.1.3

Relationship of metabolism to enzymology

The discussion to this point has focused on the chemical properties inherent to their structure that govern metabolism of molecules. However, any attempt to design metabolic stability into a molecule would be futile without an understanding of biological or enzymatic factors. One of the more significant findings is the realization that many drug metabolizing enzymes are not single enzymes, but, rather, are families of structurally related isoenzymes. It is this characteristically unique protein environment around the active site provided by each isozyme which is the key enzymatic factor accounting for regioselectivity. Unfortunately, in contrast to chemical factors, it appears that the effects of biological factors are not easily predictable. Nevertheless, understanding the differences in structure and active site interactions among different isozymes is key to manipulating drug structure to promote metabolic stability [2]. Recently, with the aid of new computational tools, a significant effort has been spent developing structure–metabolism relationships for enzymecatalyzed metabolism. In these studies, the goal is to characterize the active site requirements of the enzyme. Use this knowledge could facilitate design of new molecules to either enhance or limit metabolism by these enzymes. Alternately, it is becoming possible to predict a priori whether a new drug molecule will be a substrate or inhibitor of the isozyme in question, thus anticipating potential drug interaction issues [8]. 2.4.1.3.1. Phase I metabolism Phase I metabolism is considered to occur when there is an enzymatic transformation of the parent structure. The main classes of phase I metabolism are oxidation and hydrolysis of esters or amides. Several enzyme systems are capable of catalyzing the phase I oxidation of lipophilic substrates. Among these are cytochrome P450, flavin-containing monooxygenases, aldehyde oxidase and xanthine oxidase, just to name a few. Of these, cytochrome P450 (CYP) is generally considered to have the widest significance when it comes to metabolism of drug-like molecules. For this reason, we will consider CYP oxidation in more detail. CYP catalyzed oxidation. The CYPs represent an extensive family of closely related isozymes. The catalytic mechanism has been studied extensively through the years. According to Guengerich and Macdonald, it is likely that, despite the differences in individual CYPs, the mechanism of cytochrome P450 catalysis is essentially the same across all isozymes [82]. The first step is Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 56/82

Using Mass Spectrometry for Drug Metabolism Studies

56

activation of oxygen, then oxidation of the substrate proceeds by abstraction of a hydrogen atom or an electron from the substrate and, finally, oxygen rebound (radical recombination). As a consequence of this mechanism, it can be reasoned that metabolism by CYPs is determined by three general factors [6 and references therein]:  The degree of steric hindrance of the access of the iron–oxygen complex to the possible sites of metabolism  The topography of the active site  The possible ease of electron or hydrogen abstraction from the various carbons or heteroatoms of the substrate

Examples of this mechanism include dealkylation of amines and ethers, and hydroxylation at carbon or nitrogen. Extensive study of these reactions reveals several predictable characteristics which are a consequence of the catalytic mechanism. For example, dealkylation of N-alkylamino sidechains proceeds sequentially from the tertiary amine to the corresponding secondary amine, then to the primary amine. Typically, the N-dealkylation rate is lower upon going from the secondary amine to the primary amine, than in going from the corresponding tertiary amine to the secondary amine. This is presumably because of the increased basicity of the nitrogen (20 vs 10 ) which, in turn, stabilizes the nitrogen to electron abstraction. This order of reactivity has been exemplified by comparative rate studies of diltiazem, and its N-alkyl metabolites as well as amlodipine and its N-alkylated congeners. Polarity may also be as important as basicity, as shown by studies on a series of dihydropyrimidine based calcium channel blockers [6 and references therein]. The mechanistic aspects considered above might account for the product selectivity of the enzymatic reaction, that is, the type of reaction which is catalyzed. However, the characteristic stereo- and regioselectivity that CYPs exhibit toward their substrates cannot be accounted for exclusively by the catalytic mechanism. It is believed that structure of the apoprotein and how the substrates fit precisely also contribute significantly to regio- and stereoselectivity, and even to some extent to the product selectivity of reaction as well [6]. With the aid of new computational tools, a significant effort has recently been spent developing structure–metabolism relationships for enzyme-catalyzed metabolism. Much of this work has centered on several of the more prominent human CYP isozymes. To date, there have been reports on CYPs 2D6 [83–85], 3A4 [86, 87], 2C9 [88], and 2B6 [89, 90]. Esterase and amidase catalyzed hydrolysis. A second kind of phase I metabolism is esterase-catalyzed hydrolysis of esters or amides. The carboxylesterases constitute a heterogeneous group of isozymes that can catalyze the hydrolysis of a wide range of esters, amides, and thioesters. Therefore, they play an important role in the metabolism of drugs and lipids [91]. Mechanistically, the ester or amide is first bound to the active site presumably by an electrostatic interaction with the enzyme. Next, a nucleophilic group contained on the enzyme, e.g., a serine hydroxyl, attacks Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 57/82

Drug Metabolism In Vitro and In Vivo Results

57

the electrophilic carbonyl carbon of the ester leading to a transient charged tetrahedral intermediate. Upon collapse of this intermediate, an alcohol (or amine or thiol) leaving group is expelled. Finally, the remnant of the substrate, the carboxylate moiety, is dissociated from the enzyme. Based on this mechanism, several general structure–activity relationships emerge [91]:  Electronic factors which diminish the electrophilic nature of the carbonyl carbon decrease the rate of hydrolysis  The carboxylates of a- and b-naphthol with short acyl groups exhibited the highest rate of hydrolysis by human, rat and mouse liver esterases  Lengthening or increasing the size of the side chain of the carbonates hindered the enzymatic hydrolysis of these compounds  A trend of generally decreasing enzyme specific activity with lipophilicity has been recorded for a- and b-naphthyl alkyl carbonates and thiocarbonates

As with the CYPs, esterases exist as a family of isozymes, each with its own characteristic selectivity. For example, marked substrate selectivities were observed between rat liver hydrolase A and rat liver hydrolase B, with most of these compounds being better substrates for hydrolase B. The esterase activities of human and mouse liver microsomes were about five orders of magnitude smaller than that of rat hydrolase B. The relationship between the specific activities of the enzymes and the lipophilicity of the a- and b-naphthyl carbonate series substrates indicates that the enzymes showed decreasing activity with increasing lipophilicity of the substrates. 2.4.1.3.2

Phase II metabolism

Another general pathway of metabolism is phase II metabolism, sometimes called conjugation. Generally, this is the final metabolic step in preparing a molecule for excretion either in bile or urine. It should be noted that, usually, conjugation is a secondary step following an initial phase I reaction and, thus, has no direct effect on metabolic clearance. However, when conjugation occurs directly on a hydrophilic moiety of the parent compound, it can have a quantitative effect on metabolic clearance. The major conjugation enzymes include methyl, amino acid, sulfate, and glucuronyl transferases. Of these, glucuronidation is arguably the most common for final metabolism of drugs, so it will be considered here. Mechanistically, glucuronidation involves the transfer of d-glucuronic acid from UDP–glucuronic acid to an acceptor compound such as an alcohol, amine or carboxylate. The reaction proceeds by nucleophilic SN2 substitution of the acceptor at the C-1 carbon of glucuronic acid, the product of these reactions undergoing inversion of configuration. While understanding the mechanism can play a part in the design of drugs, structure–metabolism relationships for glucuronidation have been much less studied than either of the reactions described above. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 58/82

Using Mass Spectrometry for Drug Metabolism Studies

58

To further complicate things, as was the case for both CYPs and esterases, UDP–glucuronyl transferases exist as a family of closely related isozymes [92]. Relatively little is known about the subtleties of substrate and active site interactions for each of the various isozymes. Consequently, it is difficult to predict which factors cause some compounds to be poor substrates for conjugation even though they may have a suitable handle for conjugation [6]. As a consequence, there are comparatively few rules to guide drug design other than to avoid putting an easily conjugated group on a molecule unless it is sterically shielded. 2.4.1.4

Experimental models for metabolism

There are multiple variations of the process for conducting metabolic stability studies. Recent reviews by Thompson [8, 11] and by Eddershaw and Dickins [21] summarizing many of the variables involved in the in vitro experiments for determining metabolic stability. Three recent examples of typical metabolic stability studies can be cited [93–95]. Many more such reports should appear in the near future as this approach becomes more common. It must be emphasized that the throughput of these studies remains much lower than high-throughput pharmacology screens. 2.4.2

Biliary excretion

Biliary excretion can occur by passive diffusion, which is governed by physicochemical properties, or by active transport [13]. Drugs that are actively transported tend to be ionized (either anionic or cationic) with molecular weights >400 and contain further polar (H-bonding) groups. Functionally, biliary excretion is considered to be a three-step process [96]:  Uptake of drugs from blood into the hepatocyte at the sinusoidal (basolateral) membrane by both passive diffusion and active transport  Transfer of drugs to metabolic sites and/or the biliary canalicular membrane, mediated by intracellular transfer proteins and passive diffusion  Excretion at the canalicular membrane of unchanged drug, metabolites or a combination of both parent drug and metabolites, mainly via active secretion

The transporter proteins with the greatest potential for hepatic drug uptake are OATP-B, C and 8 and for efflux are P-gp and MRP2, sometimes called cMOAT [65, 96]. The transporters involved in hepatic uptake [97–104] and efflux [98, 105–112] of drugs are listed in Tables 2.3 and 2.4, respectively, and depicted in Figure 2.7. 2.4.2.1

Hepatic uptake

Recent expression cloning approaches have revealed the presence of multiple members of the organic anion transporting polypeptide (OATP-1) family, Copyright © 2005 CRC Press, LLC

Substrate types

OATP-A (human)

Basic, zwitterionic and neutral compounds

OATP-B (human) OATP-C (human)

Basic, zwitterionic and neutral compounds Acidic compounds

OATP-8 (human)

Acidic compounds

OATP-1 (rat)

Basic, zwitterionic and neutral compounds Basic, zwitterionic and neutral compounds Small organic cations

OATP-2 (rat) OCT (rat)

Endogenous substrate

Exogenous substrate

Reference

UK-191,005, rocuronium, N-methylquinidine, fexofenadine, CRC 220 and digoxin Fexofenadine

97, 98, 99, 100

Bile acids, conjugated steroids (i.e. cdehydroepi-androsterone sulfate, estradiol-17b-glucuronide, estrone-3-sulfate), eicosanoids, thyroid hormones, bilirubin Dehydroepiandrosterone sulfate, estrone-3-sulfate, BSP, digoxin

Pravastatin, BSP, benzylpenicillin

101, 102

estradiol-17b-glucuronide, aldosterone, estrone-3-sulfate, cortisol

Fexofenadine

98

Fexofenadine

98, 101

TEA, MPPþ, and N-methylnicotinamide

103, 104

Estrone-3-sulfate

choline

98

Adapted from References 65 and 96. OATP, organic anion transporting peptide BSP, sulfobromophthalein TEA, triethylamine MPP, 1-methyl-4-phenylpyridinium. 59

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 59/82

Transporter

Drug Metabolism In Vitro and In Vivo Results

Table 2.3 Transporter proteins involved in hepatic uptake of drugs

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 60/82

Using Mass Spectrometry for Drug Metabolism Studies

60

Table 2.4 Transporter proteins involved in the efflux of drugs into bile Transporter

Substrate types

Endogenous substrate

P-gp

Amphiphilic cationic drugs

Hepatic phospholipids

MRP2/mrp2 (cMOAT)

Anionic drugs and drug conjugates

Bilirubin and bilirubin conjugates

Exogenous substrate

Reference

Cyclosporin A, verapamil, quinidine, erythromycin, terfenadine, fexofenadine and HIV-1 protease inhibitors Grepafloxacin, pravastatin, cefodizime, methotrexale, irinotecan, temocaprilat, SN-38, the active metabolite of irinotecan

98, 105, 106, 107

108, 109, 110, 111, 112, 113

Adapted from Reference 65 and 96.

Figure 2.7

Transporter proteins involved in hepatic uptake and biliary excretion [65].

involved in the hepatocellular uptake of endogenous compounds as well as a variety of structurally divergent drugs (Table 2.4). Most evidence for uptake of drugs comes from work with the rat homologs (OATP-1, 2, 3, and 4), although it is reasonable to assume similar findings will hold true for human OATPs B, C and 8 [65]. Another transport system shown to be expressed in the hepatocytes is the di/tripeptide transporter (PepT1). PepT1 functions as an Hþ/peptide co-transporter with affinity for di/tripeptides as well as b-lactam antibiotics such as cephalexin, cephradine, and cefadroxil [65, 96]. Enterohepatic recirculation of bile is important in the excretion of endogenous and exogenous compounds. This flow of bile is maintained by the continuous uptake of bile acids from the sinusoidal blood for subsequent excretion into the bile canaliculus. Such transport is predominantly mediated by Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 61/82

Drug Metabolism In Vitro and In Vivo Results

61

Naþ-dependent taurocholate cotransporting polypeptide (NTCP). So far, this transporter has not been implicated in the excretion of any drugs. However, given the recent findings which emphasize an important role of bile acids as ligands for a number of orphan nuclear hormone receptors involved in cholesterol metabolism (FXR) and CYP expression (PXR), NTCP is likely to be important in the regulation of other transporter(s) and CYP expression [65, 96]. 2.4.2.2

Hepatic efflux

P-glycoprotein (P-gp), the best known of efflux transporters, is a 170 kDa, ATP-dependent transmembrane efflux pump for a large range of amphipathic hydrophobic substrates. The human genes are MDR1 and MDR2, while the corresponding rodent (mouse) genes are termed mdr 1 (or mdr 1b), mdr 2 and mdr 3 (or mdr 1a). P-gp is also known to have significant substrate overlap with the drug metabolizing enzyme CYP 3A. This is an important consideration to drug disposition in man since both CYP 3A and P-gp are co-expressed in tissues such as the intestinal enterocytes and hepatocytes. However, it should be emphasized that not all CYP 3A substrates are P-gp substrates and vice versa [65]. Another transporter is the ATP-dependent canalicular multiple organic anion transporter (cMOAT), or more commonly known as multidrug resistance associated protein (MRP2). This transporter appears to be responsible for the biliary excretion of organic anions, glutathione conjugates, glutathione disulfide, and some b-lactam antibiotics.

2.4.2.3

Experimental models for biliary excretion

Prediction methods to describe the excretion kinetics quantitatively are at an early development stage, although it is likely that with the provision of appropriate biochemical and molecular tools or probes, structure–activity relationships for the major hepatobiliary uptake (e.g., OATPs) and efflux (P-gp, MRP2) proteins in different species will soon emerge [13]. However, for now, biliary excretion processes should be considered qualitative [13, 19]. Nevertheless, work on biliary excretion models is actively being pursued. For example, biliary excretion of selected compounds has been successfully predicted by using sandwich hepatocytes cultures [114], which seem to rebuild a bile canalicular network and maintain some of the biliary secretion capabilities [115]. Species differences in the transport activity mediated by cMOAT were examined for 2,4-dinitrophenyl-S-glutathione, a typical substrate for cMOAT, using bile duct canalicular membrane vesicles. The Km and Vmax values for ATP-dependent uptake of 2,4-dinitrophenyl-S-glutathione into canalicular membrane vesicles were determined and a close in vivo and in vitro correlation was observed among animal species for the transport clearance across the bile canalicular membrane. These results suggest that the uptake experiments with canalicular membrane vesicles can be used Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 62/82

Using Mass Spectrometry for Drug Metabolism Studies

62

to quantitatively predict in vivo excretion across the bile canalicular membrane [116]. Cvetkovic and co-workers utilized a heterologous expression system to determine that human OATP and rat OATPs 1 and 2, mediated the uptake of 14C
fexofenadine. Similarly, the same group used the LLC-PK1 cell, a polarized epithelial cell line lacking P-gp, and the derivative cell line (LMDR1), which overexpresses P-gp to establish that P-gp was a fexofenadine efflux transporter [98]. Because identification of compounds that are P-gp substrates may predict biliary propensity towards biliary excretion, Polli and co-workers evaluated three assays used to determine whether compounds are P-gp substrates [70]. As stated earlier, 66 compounds were tested in MDCK monolayer efflux, ATPase, and calcein AM assays. All assays detected substrates across a broad range of Papp but the efflux assay was more prone to fail at high Papp whereas the calcein AM and ATPase assays were more prone to fail at low Papp. When Papp is low, efflux is a greater factor in the disposition of P-gp substrates. The MDCK efflux assay is more reliable at low-to-moderate Papp and is the method of choice for evaluating drug candidates despite low throughput and reliance on liquid chromatography with tandem mass spectrometry [70].

2.4.3 2.4.3.1

Renal excretion Mechanism of renal excretion

Drugs not dependent on metabolism or biliary excretion for clearance will, in most cases, be renally cleared. Lipophilicity is an important parameter in governing the relative proportion of metabolic versus renal clearance. Increasing lipophilicity affects the binding of xenobiotics to the active site of many of the enzymes of drug metabolism, particularly the CYPs. As a result, increasing lipophilicity to log D7.4>0 will increase metabolic clearance, while at the same time, it will likely decrease renal clearance and vice versa [6]. As a general rule, passive renal filtration usually occurs with water-soluble compounds with log D7.4<0, whereas reabsorption of a drug will be near complete at log D7.4 above 0 [2, 6, 13]. Renal clearance can be often be predicted by using glomerular filtration rate (GFR) and the fraction unbound ( fu) across species [13]: CLr ¼ GFR  fu :

ð2:16Þ

However, this relation does not always hold true. Sometimes CLr exceeds GFR, which is attributed to the presence of active secretion [2]. In fact, both active secretion and reuptake are now known to be mediated by transporter proteins [96]. In that case, the above relationship should be modified such that: CLr ¼ ðGFR  fu Þ þ CLsecretion
CLreabsorption :

Copyright © 2005 CRC Press, LLC

ð2:17Þ

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 63/82

Drug Metabolism In Vitro and In Vivo Results

63

For example, OAT proteins are involved in active renal secretion of substrates such as cimetidine, methotrexate, cidofovir, and adefovir. Other drugs, such as probenecid, b-lactam antibiotics, and nonsteroidal antiinflammatory drugs, are also known to interact with this transporter [96]. For drugs excreted primarily by active renal secretion, species differences are known to occur, although they tend to be less prominent than with hepatic clearance, with only up to two-fold overestimation of renal clearance from animals to humans. One possible explanation for such species differences in pharmacokinetics is that transport proteins are not well conserved across species [96]. 2.4.3.2

Models for renal excretion

The prediction of renal clearance for humans has been quite successful using interspecies allometric scaling approaches, although the limitation is that it requires experiments in four to five species. A simpler approach for predicting human renal clearance is based on the observation that the ratio of GFR between rats and humans is proportional to the ratio of renal clearances. Thus, in vivo urinary excretion data in rats and other species has been used to estimate renal clearance of drugs in humans [117].

2.5

Distribution of Drugs

The distribution of a drug to specific tissues is determined, in part, by drugindependent physiological factors such as blood flow to the tissue and the volume of the tissue. However, distribution is also determined by the unique physicochemical properties of each drug which control its affinity for blood components (usually plasma proteins) relative to its affinity for tissues [6, 13]. Furthermore, it is now understood that the presence of active transporters in certain tissues such as liver [65, 96] and brain [96, 118] also play an important role in determining tissue distribution. 2.5.1

Active transporters

Most of the relevant drug transporters have now been identified, and increasing evidence supports an important role of a few key transporters in the hepatic uptake of most drugs, rather than a large number of transporters with narrow substrate specificities. Transporters with the greatest potential for drug uptake are OATP-B, C and 8 and for efflux are P-gp and MRP2 (cMOAT) [65]. In particular, P-gp is perhaps the best known and studied. Although first studied by virtue of being expressed at high levels in some cancers, it is now known that normal tissues also express P-gp. For example, the canalicular domain of hepatocytes, kidney (proximal tubule), small intestine (brush border), colon, adrenal glands, and the capillary endothelium of the brain and testes all express Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 64/82

Using Mass Spectrometry for Drug Metabolism Studies

64

P-gp. In fact, because of its ubiquitous nature, it has been suggested P-gp plays an important role in limiting entry of xenobiotics into specific anatomic sites such as the brain and gastrointestinal tract and in facilitating their systemic removal by secretory mechanisms in liver and kidney [65]. The latter aspects were covered in more detail under biliary and renal clearance. 2.5.2

Plasma protein binding

Most drugs are reversibly bound to plasma proteins such as plasma albumin, lipoproteins and glycoproteins [2]. This is significant for distribution because it is only the free drug in plasma that is in equilibrium with the free drug in the tissues. Thus, the relative equilibrium between free and protein bound drug in both plasma and tissues will affect the extent of tissue distribution [2, 6]. Therefore, plasma protein binding is equally important to tissue binding as factors affecting the drug disposition and potency of drugs [15]. 2.5.2.1

Relationship of protein binding to structure

Binding on albumin can occur at two distinct sites [2]:  Site I, also called the warfarin site, binds bulky heterocyclic molecules with a negative charge centered in a largely lipophilic structure  Site II, the indole or benzodiazepine binding site, binds drugs with an extended structure carrying a negative charge away from the nonpolar region

Specific binding interactions will depend on the chemical class of the drug. For neutral compounds, hydrophobic interactions can occur with plasma proteins and many studies report a log–linear relationship between binding and lipophilicity [2]. As log D increases, plasma protein binding increases and free fraction decreases [6]. Acidic drugs (pKa<7.4) are predominantly negatively charged at physiological pH. Albumin, the predominant protein in the plasma, is a basic protein. Therefore, organic acids are highly bound to plasma proteins via ion-pair and lipophilic interactions with albumin [6]. Bases are positively charged at physiological pH and hence can bind by both ion pair and hydrophobic interactions to albumin, as well as al-acid glycoprotein and membrane phospholipids. Within the log D range of
1 to 4, bases tend to have similar plasma protein binding to neutrals [6]. 2.5.2.2

Experimental models for determining plasma protein binding

Because of the importance of plasma protein binding in drug disposition and potency, the determination of in vitro plasma protein binding is important during the lead optimization phase of drug discovery [15]. Equilibrium dialysis is the preferred method for determining the free drug fraction, because it is less susceptible to experimental artifacts. However, even low-volume standard Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 65/82

Drug Metabolism In Vitro and In Vivo Results

65

equilibrium dialysis is currently not amenable to the HTS format. Kariv and co-workers developed a 96-well equilibrium dialysis plate and validated their model with three drugs of low, intermediate, and high binding properties (propranolol, paroxetine, and losartan, respectively) [119]. The apparent free fraction obtained by this method correlates with the published values determined by the traditional equilibrium dialysis techniques. This technology was further extended with the introduction of a commercially available 96-well equilibrium dialysis block designed to be compatible with most standard 96-well format laboratory supplies and instruments [120]. Another high-throughput method of note is that described by Wring and colleagues which utilized 96-well ultrafiltration that was automated with a Tecan Genesis robot. Samples were analyzed by dual LC–MS/MS bioanalysis with fast-gradient chromatography [121]. Gu et al. described a method to measure binding of drugs to human serum albumin using pulsed ultrafiltration [122]. The throughput of pulsed ultrafiltration analyses was tripled compared to previous pulsed ultrafiltration measurements by reducing the volume of the chamber. In addition, the use of LC–MS with pulsed ultrafiltration permitted the simultaneous comparison and rank ordering of ligand mixtures for binding to serum albumin. The throughput of these pulsed ultrafiltration measurements was tripled again by analyzing three ligands as a mixture [122]. The spectrofluorometric method of Parikh et al. shows some promise as a high-throughput method [123]. Measurements can be carried out with small samples in multiwell plates and no separation of bound and unbound species is required since the method relies on the quenching of the intrinsic tryptophan fluorescence of serum albumin and a1-acid glycoprotein on binding of the drug [123]. 2.5.3

Tissue binding and volume of distribution

Distribution of a drug to tissues is difficult to measure directly. Consequently, a convenient measure of distribution is the apparent volume of distribution (Vd), which is obtained indirectly by analyzing the plasma concentration/time profile following intravenous administration. This term is indicative of the general distribution properties of a drug but provides no information on distribution into specific tissues [6, 13]. Factors summarizing passive diffusion into tissues are summarized in Equations 2.18 and 2.19. Vd ¼ Vp þ ðVt Kp Þ, Vd ¼ Vp þ ðVt fu =fut Þ,

ð2:18Þ ð2:19Þ

where Vp is the volume of plasma, VT is the volume of tissues, Kp is the tissueto-plasma concentration ratio and fu and fut are the free fractions in plasma and tissue, respectively [124]. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 66/82

Using Mass Spectrometry for Drug Metabolism Studies

66

Thus, it can be clearly seen that charge, lipophilicity, and plasma protein binding are important determinants for the volume of distribution of a drug [6]. As the above equation demonstrates, it is important to remember that it is only free (unbound) drug that is available to distribute in and out of tissues and that it is distribution and clearance of unbound drug that determines free drug concentrations at steady state [13].

2.5.3.1

Relationship of tissue binding and Vd to structure

As shown earlier, the half-life of a drug is related to both its clearance (CL) and its volume of distribution (Vd). In simple terms, the higher the Vd, the smaller the proportion of the dose of drug in the circulation and the less, therefore, available for clearance [6]. It would seem that both parameters could be modified by chemists in order to affect the duration of action. While clearance can be manipulated by structural changes for desired effects, as a practical matter, the structural requirements for binding to a pharmacophore can often define the physicochemical properties that predetermine distribution characteristics [13]. Apart from blood flow to the tissue and volume of the tissue, tissue to plasma concentration ration (Kp) is dependent on certain molecular properties such as pKa and lipophilicity. As might be expected, tissue distribution patterns are dependent on whether molecules are neutral, acidic or basic at physiological pH [6, 13]. For neutral compounds, the distribution of is governed by hydrophobic interactions with plasma proteins and tissue membranes. Since charge is not a factor, the value of log D determines distribution:  As log D increases, plasma protein binding increases and free fraction decreases  Also as log D increases, tissue affinity increases and fraction unbound in tissues decreases  For compounds with drug-like values of log D between
1 and 4 [35], Vd tends to be confined in the range 0.5–5 L/kg

Acidic drugs (pKa<7.4) are predominantly negatively charged at physiological pH, and thus can exhibit both ion pair and hydrophobic interactions resulting in the following distribution patterns:  Acids tend to be highly bound to plasma proteins, particularly albumin.  Because of unfavorable charge–charge interactions with negatively charged phospholipids of tissue membranes, acids tend to have very low tissue affinity.  Hence, because the value of Kp is very small, the Vd of acidic compounds tends to be very low, typically 0.5 L/kg or less.

Bases are positively charged at physiological pH and hence can bind by both ion pair and hydrophobic interactions to albumin, al-acid glycoprotein and

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 67/82

Drug Metabolism In Vitro and In Vivo Results

67

membrane phospholipids:  Within the log D range of
1 to 4, bases tend to have similar plasma protein binding to neutrals.  Because of favorable charge–charge interaction with membrane phospholipids, bases have higher tissue affinity and lower fut than acids or neutrals.  As a result, bases can have much higher volumes of distribution than are observed for either acids or neutrals.

2.5.3.2

Experimental methods for determining Vd

Prediction of human PK remains a central goal of the drug discovery process. Given the importance of distribution to efficacy and duration of drug action, much effort has gone into predicting distribution. Among the various models used to predict drug distribution some have been purely theoretical, some have been experimental, or a hybrid of both. Most models center around three main approaches: (1) QSAR-type models, (2) in vitro dialysis or (3) allometric scaling. As an example of the first approach, Lombardo et al. described a method for the prediction of volume of distribution in humans based on two experimentally determined physicochemical parameters, E log D7.4 [39] and the fraction of compound ionized at pH 7.4 (derived from pKa), and on the fraction of free drug in plasma ( fu) determined from protein binding data [125]. The fraction unbound in tissues ( fut), was determined via a regression analysis from 64 compounds using the parameters described, and was then used to predict Vd via the Oie–Tozer equation [126]: Vd ¼ Vp ð1 þ REI Þ þ fu Vp ðVE =Vp
REI Þ þ VR fu =fut ,

ð2:20Þ

where the parameters Vp, VE, and R EI are taken to be the plasma and extracellular fluid volumes and the ratio of extravascular to intravascular proteins, respectively, with corresponding values in human of 0.0436 and 0.151 L/kg body weight for Vp and VE, respectively and approximately 1.4 for R EI. Accuracy of this method was determined using a test set of 14 compounds, and it was demonstrated that human Vd values could be predicted to within about two-fold of the actual value. It has been proposed that distribution of unbound drug is similar across species and that species differences in Vd can be explained by differences in plasma protein binding, giving rise to estimation of Vd by allometric models. Such approaches are typified by the report of Obach et al. who estimated Vd in humans from Vd determined in dog corrected for the differences in plasma protein binding in man and dog [81]: Vd,man ¼ Vd,dog fu,man =fu,dog :

Copyright © 2005 CRC Press, LLC

ð2:21Þ

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 68/82

Using Mass Spectrometry for Drug Metabolism Studies

68

2.5.4.

CNS penetration

Combinatorial synthesis and high-throughput pharmacology screening have greatly increased compound throughput in modern drug discovery programs. For central nervous system (CNS) drugs, there is an additional requirement of determining permeability to the blood–brain barrier (BBB). 2.5.4.1

The blood–brain barrier

The BBB is comprised of three cell types: cerebromicrovascular endothelial cells connected by tight junctions, astrocytes, and the supporting pericytes [96, 118]. Brain microvascular endothelial cells lack fenestrations, have few pinocytotic vesicles and express a variety of metabolic enzymes and efflux transporters such as P-gp [96]. These features make the BBB a formidable barrier the drugs must overcome to reach the brain parenchyma [127]. Passage across the BBB is determined by physicochemical properties described below or by being actively transported into or out of the CNS. 2.5.4.2

Relationship of structure to CNS permeability

Chemists have worked diligently to either increase or limit the permeability of drugs to the brain depending on the therapeutic goal. By now, a number of factors are recognized that distinguish CNS drugs from non-CNS drugs [127]:  Analysis of 18 physicochemical properties revealed that the CNS drug set had several properties associated with enhanced membrane permeability, including fewer hydrogen bond donors, fewer positive charges, greater lipophilicity, lower polar surface area, and reduced flexibility compared with the non-CNS group (P<0.05).  To enhance CNS penetration, a compound should have a MW<450, and total polar surface area (PSA) <90 A˚ [128].  For delivery to the CNS, a drug should ideally have an in vitro passive permeability>150 nm/s.  The CNS drug set should not be a good P-gp substrate [96], defined as a B ! A/A!B ratio <2.5 [127].

2.5.4.3

Role of active transport in CNS permeability

The inverse relation between permeability to the CNS and affinity for P-gp highlights the important role played by P-gp and other active transporters. In particular, P-gp has come to be recognized as an important contributor to the BBB because a number of highly lipophilic compounds which should have ideal properties to cross the BBB have been found to have poor CNS permeability. This unexpected poor permeability is presumably because they are good substrates for P-gp, as demonstrated convincingly by experiments with P-gp null mice [96 and references therein]. The role of drug transporters in determining distribution to the CNS has been reviewed [65, 129]. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 69/82

Drug Metabolism In Vitro and In Vivo Results

2.5.4.4

69

Experimental models for determining CNS permeability

A variety of theoretical or experimentally determined physicochemical descriptors have been investigated as predictors of in vivo BBB permeability [130, 131]. In general, such descriptors correlate well with in vivo brain penetration for drugs that undergo passive transcellular diffusion. However, physicochemical descriptors do not account for the role of cerebromicrovascular endothelial cell metabolism or active transport or efflux in the overall BBB permeability of a drug. In particular, major drug efflux mechanisms such as the P-gp transporter contribute significantly to prevention of drug permeability, although its substrate specificity is clearly very broad and not yet well defined [118]. To account for active transport or efflux, a variety of cell-based models have been employed. However, these cell-based models are not without their own limitations. While cultures of brain capillary endothelial cells retain many morphological and biochemical properties (including transporters such as P-gp) similar to the BBB in vivo, they generally do not form sufficiently tight cell junctions. To some extent, co-culturing with astrocytes and using astrocyte-conditioned media can help [15]. It is clear that any in vitro BBB cell model utilized for the screening of potential CNS drugs must display reproducible substrate permeability. The precision of such systems, is improved by comparison of the permeability data for the test molecules to permeability data for low (e.g., sucrose) and high (e.g., diazepam or propranolol) brain-penetrating solutes used as internal controls within the experiment. Beyond this, a number of other general criteria for model appropriateness may be defined [118]:  The cell model must display a restrictive paracellular pathway.  The model should possess a physiologically realistic cell architecture.  The model should display functional expression of transporter mechanisms.  The cell model should allow for ease of culture to facilitate high throughput screening.

For any model to be validated as an acceptable discriminatory screen, these criteria should be taken into account. The bovine brain microendothelial cell (BBMEC) model was one of the first cell-based methods, which permitted study of the BBB [132]. This model had the advantages of being an in vitro technique that exhibited many of the characteristics of the BBB. Using this technique, morphologically intact endothelial cells can be cultured that maintain physiologically relevant characteristics such as (1) no fenestra, (2) few pinocytic vesicles, (3) tight intercellular junctions, and (4) an abundance of mitochondria. Secondly, this model maintains the biochemical characteristics of brain microvessel endothelial cells, including active enzymes such as (1) alkaline phosphatase, (2) gammaglutamyl transpeptidase, and (3) angiotensin-converting enzyme. Finally, this model also expresses transporter proteins such as P-gp, a protein thought to be an important component of the overall integrity of the BBB. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 70/82

Using Mass Spectrometry for Drug Metabolism Studies

70

Otis et al. [133] describe modifications to the method of Audis and Borchardt [132], in the (1) isolation and culture of the microvessel endothelial cells themselves, (2) experimental design, and (3) analysis of the samples by LC–MS. They reported improved throughput and cycle time while preserving the predictive value of the original method. The result was a robust, facile screen for determination of CNS permeability of multiple compounds. BBMEC data has not always correlated well with in vivo data. Among the possible reasons for this are (1) different levels of P-gp expression or metabolic properties in these two barriers, (2) the dynamic equilibrium with brain clearance factors that occurs in vivo, or (3) the aforementioned lack of intracellular junctions that are not as tight as in vivo. Cell lines derived from other tissues also have been examined. For example, the ECV304 bladder carcinoma cell line will achieve very low paracellular permeability and have much tighter BBB-like cell junctions if pretreated with the differentiating agent butyric acid, or compounds which elevate cAMP, but such cell lines still lack P-gp expression. Caco-2 cultures have also been proposed as a model for CNS permeability. However, even though Caco-2 cultures possess P-gp and have tight cell junctions, a comparison of Caco-2 data with in vitro and in vivo BBB data revealed a poor correlation [118]. Another cell line that has been studied to overcome some of the limitations of the bovine brain epithelial cell model is the epithelial MDCK cell line. These cells usually possess tighter junctions than BBMEC or Caco-2, but unfortunately still have little P-gp. However, an MDCK cell line (derived from wild-type MDCK-II cells) has been stably transfected with the human MDR-I gene leading to the polarized overexpression of P-gp to solve this issue [15, 118, 127]. In their 2001 review, Gumbleton and Audis have concluded that because immortalized cell lines universally fail to generate a sufficiently restrictive paracellular barrier for use in transendothelial permeability investigations, a number of in vitro techniques should be exploited. This includes not only permeability data derived from in vitro cell models, but also transfer across artificial membranes, and physicochemical predictors derived from a drug’s molecular structure [118].

2.6

Integration of DMPK data

Optimizing permeability, metabolic stability, solubility and other DMPK properties through structure modification while still maintaining potency can be quite daunting. This is primarily due to the opposing requirements of the properties for intestinal permeability, distribution, metabolism, and biliary or renal clearance. For example, increasing a compound’s lipophilicity generally increases membrane permeability and receptor binding affinity, but at the same time, also may make the compound a better substrate for CYPs, thus resulting in more rapid metabolism [6]. Conversely, increasing a compound’s polarity makes it more water soluble, but also less membrane permeable. Thus, design Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 71/82

Drug Metabolism In Vitro and In Vivo Results

71

of drugs with both optimal potency and PK properties is very challenging given the opposing requirements for absorption and metabolism and the general lack of sufficient in vitro and in vivo data sets for a large diversity of compounds in guiding this process. Recently, several attempts have been made to integrate in vitro intestinal permeability and metabolic stability data in parallel with the in vivo pharmacology and PK studies during the lead candidate selection and optimization process [134–137]. While good correlations between in vitro and in vivo data were made, these studies were limited to relatively small series of compounds, and included only a limited number of species such as rats or guinea pigs, but not humans. These limitations were addressed in a retrospective study of Pfizer compounds by Obach et al. [81]. In this study, the authors proposed a model to predict human bioavailability, clearance and other PK parameters from in vitro metabolism and in vivo animal PK data. Although this model did not rely on integration of permeability and metabolic clearance in estimating oral bioavailability, it did yield acceptable predictions (within a factor of 2) for the compounds in this dataset. However, this model and others like it predominantly rely on in vivo animal PK data for interspecies scaling needed to predict human PK, which limits suitability for support discovery projects where higher throughput ADME screening is needed. At the early stage of drug discovery, the goal of integrative DMPK models should not to make precise, quantitative predictions, but rather, to forecast whether a given compound will have satisfactory pharmacokinetic properties in animals or humans. The intent should be to use a predictive model in conjunction with a high throughput in vitro ADME screens rational lead selection. Then, as the compounds proceed along the discovery–development continuum, more detailed DMPK models can be applied as needed. As an example of such an approach, Mandagere et al. [138] have described an intuitive, graphical model for estimating oral bioavailability in humans or any other species from in vitro data, without the need for in vivo interspecies scaling. They demonstrated the predictive capacity and the utility of this model with 20 structurally diverse compounds from 10 different therapeutic areas with a wide range of %F values (Figure 2.8). The main utility of this graphical model was its ability to rapidly classify compounds into groups of acceptable and unacceptable bioavailability in humans and any other species. By use of such a model, unacceptable compounds can be eliminated early, allowing focus on the promising compounds for further in vivo evaluations.

2.7

Summary

It was reported as early as 1988 that one of the major reasons that drugs fail in the clinics was due to poor pharmacokinetic properties [23]. In response, the past two decades have witnessed the widespread incorporation of in vitro ADME approaches into drug development by drug companies. The current Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 72/82

72

Using Mass Spectrometry for Drug Metabolism Studies

Figure 2.8 Graphical depiction of the relation of metabolic stability and permeability to oral bioavailability [138].

philosophy of drug development is moving to a fail ‘early–fail cheaply’ paradigm [28]. Currently, ADME approaches, especially in vitro ADME methods, are being applied to drug candidates earlier in the discovery– development continuum [8, 11, 16]. These trends notwithstanding, there are still two intransigent problems that still persist. First, in a recent review, Smith and colleagues have maintained that the alignment of DMPK departments with drug discovery has not produced a radical improvement in the pharmacokinetic properties of new chemical entities entering development as was expected [139]. At best, molecules with adequate, rather than optimal, pharmacokinetic properties have been developed. If anything, the greatest success of drug metabolism has been to contribute to the development of compounds with suboptimal PK properties which otherwise might have failed in the clinic [139]. Second, despite significant efforts by drug metabolism scientists in both academia and industry, the ability to model or predict pharmacokinetic properties from preclinical experimental data so far has been an elusive goal. Again, what successes have been achieved in modeling reflect the ability to provide qualitative rather than quantitative prediction of properties [139]. In fact, it is becoming increasingly evident that optimal pharmacokinetic properties may be not be achievable within a given discovery program. The reasons for the first point are complex, reflecting in part the difficulty of combining potency, selectivity, water solubility, metabolic stability, and membrane permeability into a single molecule [138–140]. Chemists are finding that to achieve novel drug targets, drug design is being forced into areas of chemical space where pharmacokinetic issues are more frequent [140]. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 73/82

Drug Metabolism In Vitro and In Vivo Results

73

Because of this limitation, precise prediction of DMPK properties not only be unnecessary, but perhaps even futile. Regarding this point, Lipinski has stated that ADME properties exist in simpler chemistry space than activity and that simple rules and filters work reasonably well. Ironically, structure–activity relationships for large ADME data sets are less robust than for small data sets because most ADME properties are multi-mechanism. In contrast to models for single mechanism assays, models for multi-mechanism assays (e.g., solubility or metabolic stability) typically get worse as more data is accumulated [140]. In light of the above facts, one of the more important developments of the future may be to finally realize our limitations when it comes to drug design and ADME properties. As Smith has said, the most valuable contribution of drug metabolism and pharmacokinetics to drug discovery may, in fact, be to enable the design of pharmacokinetically acceptable rather than ideal molecules [139]. If that postulate is accepted, then the goals for DMPK departments become more modest, but achievable. Depending on the stage of the discovery–development continuum, there are three goals [139]:  Educate and facilitate drug design such that disposition properties are considered equally to those of pure, particularly in vitro, pharmacological properties as early as possible in the drug discovery process.  Ensure that disposition properties within development candidate molecules are consistent with or superior to those of marketed drugs (in terms of, for example, dose size and frequency or interaction potential).  Ensure that patterns evolving from the study of drugs in clinical pharmacokinetics are used to form the basis of more predictive preclinical models that can then be used for education and facilitation of drug design.

Regarding the failure of ADME models to adequately predict in vivo PK properties, Lipinksi has suggested that the solution to this dilemma is to carry out single mechanism ADME experimental assays and to construct single mechanism ADME computational models. This would permit the assays to be at once high-throughput, less expensive, and more predictive. In that regard, DMPK is at least 5 or more years behind the biology therapeutic target area [140]. Ekins et al. concur with such a trend and raise the ante [16]. According to these authors, we are entering the computational ADME age. While some of the most intense efforts have been in computational methods for CYP catalyzed reactions, they speculate that, in fact, our broad growth of knowledge of CYPs may slow down and be followed by a shift in focus towards phase II enzymes or phase III transporters for excretion [16]. These authors have further questioned the need for the massive quantities of ADME data that have come to be considered essential. In their opinion, discovery chemists are ‘‘drowning in data.’’ Our ability to generate and compile data has far outstripped our ability to understand and use the data in a meaningful way. They propose a more rational use of the in vitro metabolism methods preceded by computational filtration using either simple rules, Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 74/82

74

Using Mass Spectrometry for Drug Metabolism Studies

pharmacophore-, or descriptor-based approaches. They advocate a first tier of computationally predicted properties to identify a smaller subset of molecules. On this more limited subset, in vitro approaches would be applied to confirm that acceptable DMPK properties were achieved, thus promoting a higher probability of success. Better yet, validated in vivo clinical surrogates may be developed in parallel. If so, whole-cell information could be combined with more reductionist in vitro data, to provide a broader picture of metabolism, potential for drug–drug interactions and toxicity [16]. In conclusion, even though the prospects for designing drugs with optimal PK properties may be remote, the central role that DMPK departments have come to play in drug discovery is still essential. One could argue that it may even be considered liberating to realize that optimum PK properties will not be achieved. Instead, DM efforts in drug discovery should shift to developing faster, less expensive yet still reliable screens and to better integrate the data that it is acquired. The appropriate data at the appropriate time will make the biggest impact of all.

References 1. Ariens, E.J. and Simonis, A.M., Optimalization of pharmacokinetics —an essential aspect of drug development by ‘‘metabolic stabilization,’’ in Strategy in Drug Research, Keverling Buisman, J.A., Ed., Elsevier Scientific Publishing Company, Amsterdam, 1982, 165. 2. Testa, B. and Mayer, J.M., Drug metabolism and pharmacokinetics: implications for drug design, Acta. Pharm. Jugosl., 40, 315, 1990. 3. Humphrey, M.J. and Smith, D.A., Role of metabolism and pharmacokinetic studies in the discovery of new drugs—present and future perspectives, Xenobiotica, 22, 743, 1992. 4. Chiu, S-H.L., The use of in vitro metabolism studies in the understanding of new drugs, J. Pharmacol. Toxicol. Meth., 29, 77, 1993. 5. Smith, D.A., Design of drugs through a consideration of drug metabolism and pharmacokinetics, Eur. J. Drug Metab. Pharmacokin., 19, 193, 1994. 6. Smith, D.A., Jones, B.C., and Walker, D.K., Design of drugs involving the concepts and theories of drug metabolism and pharmacokinetics, Med. Res. Rev., 16, 243, 1996. 7. Lin, J.H. and Lu, A.Y.H., Role of pharmacokinetics and metabolism in drug discovery and development, Pharmacol. Rev., 49, 403, 1997. 8. Thompson, T.N., Early ADME in support of drug discovery: The role of metabolic stability studies, Curr. Drug Metab., 1, 215, 2000. 9. White, R.E., High-throughput screening in drug metabolism and pharmacokinetic support of drug discovery, Annu. Rev. Pharmacol. Toxicol., 40, 133, 2000. 10. Navia, M.A. and Chaturvedi, P.R., Design principles for orally bioavailable drugs, Drug Discov. Today, 1, 179, 1996. 11. Thompson, T.N., Optimization of metabolic stability as a goal of modern drug design, Med. Res. Rev., 21, 412, 2001.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 75/82

Drug Metabolism In Vitro and In Vivo Results

75

12. Chaturvedi, P.R., Decker, C.J., and Odinecs, A., Prediction of pharmacokinetic properties using experimental approaches during early drug discovery, Curr. Opin. Chem. Biol., 5, 452, 2001. 13. Riley, R.J., Martin, I.J., and Cooper, A.E., The influence of DMPK as an integrated partner in modern drug discovery, Curr. Drug Metab., 3, 527, 2002. 14. Roberts, S.A., Drug metabolism and pharmacokinetics in drug discovery, Curr. Opin. Drug Discov. Dev., 6, 66, 2003. 15. Roberts, S.A., High-throughput screening approaches for investigating drug metabolism and pharmacokinetics, Xenobiotica, 31, 557, 2001. 16. Ekins, S. et al. Present and future in vitro approaches for drug metabolism, J. Pharmacol. Toxicol. Meth., 44, 313, 2000. 17. Caldwell, G.W. et al. The new pre-preclinical paradigm: compound optimization in early and late phase drug discovery, Curr. Topics Med. Chem., 1, 353, 2001. 18. Bertrand, M., Jackson, P., and Walther, B., Rapid assessment of drug metabolism in the drug discovery process, Eur. J. Pharm. Sci., 11 (Suppl 2), S61, 2000. 19. Theil, F.P. et al. Utility of physiologically based pharmacokinetic models to drug development and rational drug discovery candidate selection, Toxicol. Lett., 138, 29, 2003. 20. van de Waterbeemd, H., High-throughput and in silico techniques in drug metabolism and pharmacokinetics, Curr. Opin. Drug Discov. Dev., 5, 33, 2002. 21. Eddershaw, P.J. and Dickins, M., Advances in in vitro drug metabolism screening, Pharm. Sci. Tech. Today, 2, 13, 1999. 22. Bjornsson, T.D. et al. The conduct of in vitro and in vivo drug–drug interaction studies: a Pharmaceutical Research and Manufacturers of America (PHRMA) perspective, Drug Metab. Disp., 31, 815, 2003. 23. Prentis, R.A, Lis, Y., and Walker, S.R., Pharmaceutical innovation by the seven UK-owned pharmaceutical companies, Br. J. Clin. Pharmacol., 25, 387, 1988. 24. Cashman, J.R., Drug discovery and drug metabolism, Drug Discov. Today, 1, 209, 1996. 25. Peet, N.P., Selecting leads with pharmacokinetic data, Mod. Drug Discov., July/ August, 21, 1999. 26. Rodrigues, A.D., Preclinical drug metabolism in the age of high-throughput screening: an industrial perspective, Pharm. Res., 14, 1504, 1997. 27. Rodrigues, A.D., Rational high-throughput screening in preclinical drug metabolism, Med. Chem. Res., 8, 422, 1998. 28. Tarbit, M.H. and Berman, J., High-throughput approaches for evaluating absorption distribution, metabolism and excretion properties of lead compounds, Curr. Opin. Chem. Biol., 2, 411, 1998. 29. Wrighton, S.A., Ring, B.J., and Vandenbranden, M., The use of in vitro metabolism techniques in the planning and interpretation of drug safety studies, Toxicol. Pathol., 23, 199, 1995. 30. Parkinson, A., An overview of current cytochrome P450 technology for assessing the safety and efficacy of new molecules, Toxicol. Pathol., 24, 45, 1996. 31. Smith, D.A. and Jones, B.C., Speculations on the substrate structure–activity relationship (SSAR) of cytochrome P450 enzymes, Biochem. Pharmacol., 44, 2089, 1992. 32. Smith, D.A., Ackland, M.J., and Jones, B.C., Properties of cytochrome P450 isoenzymes and their substrates Part 1: active site characteristics, Drug Discov. Today, 2, 406, 1997.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 76/82

76

Using Mass Spectrometry for Drug Metabolism Studies

33. Smith, D.A., Ackland, M.J., and Jones, B.C., Properties of cytochrome P450 isoenzymes and their substrates Part 2: properties of cytochrome P450 substrates, Drug Disccv. Today, 2, 479, 1997. 34. Pelkonen, O., Boobis, A.R., and Gundert-Remy, U., In vitro prediction of gastrointestinal absorption and bioavailability: an experts’ meeting report, Eur. J. Clin. Pharmacol., 57, 621, 2001. 35. Lipinski, C.A. et al. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings, Adv. Drug Deliv. Rev., 23, 3, 1997. 36. Kerns, E.H., High throughput physicochemical profiling for drug discovery, J. Pharm. Sci., 90, 1838, 2001. 37. Bergstrom, C.A. et al. Experimental and computational screening models for prediction of aqueous drug solubility, Pharm. Res., 19, 182, 2002. 38. Bevan, C. and Lloyd, R.S., A high-throughput screening method for the determination of aqueous drug solubility using laser nephelometry in microtiter plates, Anal. Chem., 72, 1781, 2000. 39. Lombardo, F. et al. ElogD(oct): a tool for lipophilicity determination in drug discovery. 2. Basic and neutral compounds, J. Med. Chem., 44, 2490, 2001. 40. Tsuji, A. and Tamai, I. Carrier-mediated intestinal transport of drugs, Pharm. Res., 13, 963, 1996. 41. Stewart B.H. et al. Saturable transport mechanism in the intestinal absorption of gabapentin is the underlying cause of the lack of proportionality between increasing dose and drug levels in plasma, Pharm. Res., 10, 276, 1993. 42. Amidon, G.L., Merfeld, A.E., and Dressman, J.B., Concentration and pH dependency of a-methyldopa absorption in rat intestine, J. Pharm. Pharmacol., 38, 363, 1986. 43. Hu, M. and Borchardt, R.T., Mechanism of l-a-methyldopa transport through a monolayer of polarized human intestinal epithelial cells (Caco-2), Pharm. Res., 7, 1313, 1990. 44. Shindo, H., Komai, T., and Kawai, K., Studies on the metabolism of d- and l-isomers of 3,4-dihydroxyphenylalanine (DOPA). V. Mechanism of intestinal absorption of d- and l-DOPA-14C in rats, Chem. Pharm. Bull.,(Tokyo) 21, 2031, 1973. 45. Cercos-Fortea, T. et al. Influence of leucine on intestinal baclofen absorption as a model compound of neutral a-amino acids, Biopharm. Drug Dispos., 16, 563, 1995. 46. Thwaites, D.T. et al. d-cycloserine transport in human intestinal epithelial (Caco-2) cells mediated by a H-coupled amino acid transporter, Br. J. Pharmacol., 115, 761, 1995. 47. Okano, K. et al. Hþ coupled uphill transport of aminocephalosporins via the dipeptide transport system in rabbit intestinal brush-border membranes, J. Biol. Chem., 261, 14130, 1986. 48. Inui, K., Miyamoto, M., and Saito, H., Transepithelial transport of oral cephalosporins by monolayers of intestinal epithelial cell line Caco-2: Specific transport systems in apical and basolateral membranes, J. Pharmacol. Exp. Therap., 261, 195, 1992. 49. Tamai, I. et al. Functional expression of intestinal depeptide/b-lactam antibiotic transporter in Xenopus laevis oocytes, Biochem. Pharmacol., 48, 881, 1994. 50. Tamai, I. et al. Functional expression of transporter for b-lactam antibiotics and dipeptides in Xenopus laevis oocytes injected with messenger RNA from human, rat and rabbit small intestines, J. Pharmacol. Exp. Therap., 273, 26, 1995.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 77/82

Drug Metabolism In Vitro and In Vivo Results

77

51. Boll, M. et al. Expression cloning of a cDNA from rabbit small intestine related to proton-coupled transport of peptides, b-lactam antibiotics and ACE-inhibitors, Pflugers-Arch., 429, 146, 1994. 52. Amidon, G.L. and Lee, H.J., Absorption of peptide and peptidomimetic drugs, Annu. Rev. Pharmcol. Toxicol., 34, 321, 1994. 53. Yee, S. and Amidon, G.L., Oral absorption of angiotensin-converting enzyme inhibitors and peptide prodrugs’ in Peptide-based Drug Design, Taylor, M.D and Amidon, G.L, Eds., American Chemical Society, Washington, D.C., 1995, 299. 54. Kramer, W. et al. Interaction of renin inhibitors with the intestinal uptake system for oligopeptides and b-lactam antibiotics, Biochim. Biophys. Acta, 1027, 25, 1990. 55. Hashimoto, N. et al. Renin inhibitor: transport mechanism in rat small intestinal brush-border membrane vesicles, Pharm. Res., 11, 1448, 1994. 56. Takano, M. et al. Bestatine transport in rabbit intestinal brush-border membrane vesicles, Biochem. Pharmacol., 47, 1089, 1994. 57. Walter, E. et al. Transepithelial properties of peptidomimetic thrombin inhibitors in monolayers of a human intestinal cell line (Caco-2) and their correlation to in vivo data, Pharm. Res., 12, 360, 1995. 58. Mizuma T. et al. Intestinal active absorption of sugar-conjugated compounds by glucose transport system: implication of improvement of poorly absorbable drugs, Biochem. Pharmcol., 43, 2037, 1992. 59. Osiecka, I. et al. In vitro drug absorption models. I. Brush border membrane vesicles, isolated mucosal cells and everted intestinal rings: Characterization and salicylate accumulation, Pharm. Res., 2, 284, 1985. 60. Takanaga, H., Tamai, I., and Tsuji, A., pH-Dependent and carrier-mediated transport of salicylic acid across Caco-2 cells, J. Pharm. Pharmacol., 46, 567, 1994. 61. Tsuji, A. et al. Transcellular transport of benzoic acid across Caco-2 cells by a pH-dependent and carrier-mediated transport mechanism, Pharm. Res., 11, 30, 1994. 62. Tamai, I. et al. Proton-cotransport of pravastatin across intestinal brush-border membrane, Pharm. Res., 12, 1727, 1995. 63. Tsuji, A. and Tamai, I., Naþ and pH dependent transport of foscarnet via the phosphate carrier system across intestinal brush-border membrane, Biochem. Pharmacol., 38, 1019, 1989. 64. Swaan, P.W. and Tukker J.J., Carrier-mediated transport mechanism of foscarnet (trisodium phosphonoformate hexahydrate) in rat intestinal tissue, J. Pharmacol. Exp. Therap., 272, 242, 1994. 65. Kim R.B., Transporters and xenobiotic disposition, Toxicology, 181–182, 291, 2002. 66. Kim, R.B. et al. Interrelationship between substrates and inhibitors of human CYP3A and P-glycoprotein, Pharm. Res., 16, 408, 1999. 67. Cvetkovic, M. et al. OATP and P-glycoprotein transporters mediate the cellular uptake and excretion of fexofenadine, Drug Metab. Dispos., 27, 866, 1999. 68. Fromm, M.F. et al. Inhibition of P-glycoprotein-mediated drug transport: a unifying mechanism to explain the interaction between digoxin and quinidine, Circulation, 99, 552, 1999. 69. Kim, R.B. et al. The drug transporter P-glycoprotein limits oral absorption and brain entry of HIV-1 protease inhibitors, J. Clin. Invest., 101, 289, 1998. 70. Polli, J.W. et al. Rational use of in vitro P-glycoprotein assays in drug discovery, J. Pharmacol. Exp. Therap., 299, 620, 2001.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 78/82

78

Using Mass Spectrometry for Drug Metabolism Studies

71. Kansy, M., Senner, F., and Gubernator, K., Physicochemical high throughput screening: parallel artificial membrane permeation assay in the description of passive absorption processes, J. Med. Chem., 41, 1007, 1998. 72. Audus K.L. et al. The use of cultured epithelial and endothelial cells for drug transport and metabolism studies, Pharm. Res., 7, 435, 1990. 73. Artursson, P. and Karlsson, J., Correlation between oral drug absorption in humans and apparent drug permeability coefficients in human intestinal epithelial (Caco-2) cells, Biochem. Biophys. Res. Comm., 175, 880, 1991. 74. Irvine, J.D. et al. MDCK (Madin–Darby canine kidney) cells: A tool for membrane permeability screening, J. Pharm. Sci., 88, 28, 1999. 75. Rane, A., Wilkinson, G.R., and Shand, D.G., Prediction of hepatic extraction ratio from in vitro measurements of intrinsic clearance, J. Pharmacol. Exp. Therap., 200, 420, 1977. 76. Houston, J.B., Utility of in vitro drug metabolism data in predicting in vivo metabolic clearance, Biochem. Pharmacol., 47, 1469, 1994. 77. Houston, J.B. and Carlile, D.J., Prediction of hepatic clearance from microsomes, hepatocytes, and liver slices, Drug Metab. Rev., 29, 891, 1997. 78. Ito, K. et al. Quantitative prediction of in vivo drug clearance and drug interactions from in vitro data on metabolism, together with binding and transport, Annu. Rev. Pharmacol. Toxicol., 38, 461, 1998. 79. Iwatsubo, T. et al. Prediction of in vivo drug metabolism in the human liver from in vitro metabolism data, Pharmacol. Therap., 73, 147, 1997. 80. Lave, T. et al. The use of human hepatocytes to select compounds based on their expected hepatic extraction ratios in humans, Clin. Pharmacokinet., 36, 211, 1999. 81. Obach R.S. et al. The prediction of human pharmacokinetic parameters from preclinical and in vitro metabolism data, J. Pharmacol. Exp. Therap., 283, 46, 1997. 82. Guengerich, F.P. and Macdonald, T.L., Mechanisms of cytochrome P450 catalysis, FASEB J., 4, 2453, 1990. 83. Halliday, R.C. et al. Synthetic strategies to lower affinity for CYP2D6, Eur. J. Drug Metab. Pharmacokin., 22, 291, 1997. 84. de Groot, M.J. et al. Novel approach to predicting P450-mediated drug metabolism: development of a combined protein and pharmacophore model for CYP2D6, J. Med. Chem., 42, 1515, 1999. 85. de Groot, M.J. et al. A novel approach to predicting P450 mediated drug metabolism. CYP2D6 catalyzed N-dealkylation reactions and qualitative metabolite predictions using a combined protein and pharmacophore model for CYP2D6, J. Med. Chem., 42, 4062, 1999. 86. Ekins, S. et al. Three- and four-dimensional quantitative structure activity relationship analyses of cytochrome P-4503A4 inhibitors, J. Pharmacol. Exp. Therap., 290, 429, 1999. 87. Ekins, S. et al. Three-dimensional-quantitative structure activity relationship analysis of cytochrome P-450 3A4 substrates, J. Pharmacol. Exp. Therap., 291, 424, 1999. 88. Jones, B.C. et al. Putative active site template model for cytochrome P4502C9 (tolbutamide hydroxylase), Drug Metab. Disp., 24, 260, 1996. 89. Ekins, S. et al. Three-dimensional quantitative structure activity relationship analyses of substrates for CYP2B6, J. Pharmacol. Exp. Therap., 288, 21, 1999. 90. Lewis, D.F.V. et al. Molecular modeling of CYP2B6, the human CYP2B isoform, by homology with the substrate-bound CYP102 crystal structure: evaluation of

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 79/82

Drug Metabolism In Vitro and In Vivo Results

91.

92.

93.

94.

95.

96. 97.

98. 99.

100.

101. 102. 103. 104.

105. 106.

107. 108.

79

CYP2B6 substrate characteristics, the cytochrome b5 binding site and comparisons with CYP2B1 and CYP2B4, Xenobiotica, 29, 361, 1999. Huang, T.L. et al. Hydrolysis of carbonates, thiocarbonates, carbamates, and carboxylic esters of a-naphthol, b-naphthol, and p-nitrophenol by human, rat, and mouse liver carboxylesterases, Pharm. Res., 10, 639, 1993. Parkinson, A., Biotransformation of xenobiotics, in Casserett and Doull’s Toxicology, 5th edition, Klaassen, C.D., Ed., McGraw Hill, New York, 1996, 113. Ackerman, B.L. et al. Increasing the throughput of microsomal stability screening using fast gradient elution LC/MS. Proceedings of the 46th ASMS Conference on Mass Spectrometry and Allied Topics, Orlando, FL, May 31–June 4, 1998. Ho, J. et al. A strategy for achieving higher throughput in screening for metabolic stability, Abstracts of the 1999 annual meeting of the American Association of Pharmaceutical Scientists, New Orleans, LA, November, 1999. Korfmacher, W.A. et al. Development of an automated mass spectrometry system for the quantitative analysis of liver microsomal incubation samples: a tool for rapid screening of new compounds for metabolic stability, Rapid Commun. Mass Spectrom., 13, 901, 1999. Ayrton, A. and Morgan, P., Role of transport proteins in drug absorption, distribution and excretion, Xenobiotica, 31, 469, 2001. Eckhardt, U. et al. First-pass elimination of a peptidomimetic thrombin inhibitor is due to carrier-mediated uptake by the liver, Biochem. Pharmocol., 52, 85, 1996. Cvetkovic, M. et al. OATP and P-glycoprotein transporters mediate the cellular uptake and excretion of fexofenadine, Drug Metab. Dispos., 27, 866, 1999. Morgan, P. et al. Identification of OATP-mediated uptake of a series of lipophilic bases, Abstracts of the 9th North American ISSX meeting, Nashville, TN, October 25–29, 1999. van Montfoort, J.E. et al. Polyspecific organic anion transporting polypeptidss mediate hepatic uptake of amphipathic type H organic cations, J. Pharmacol. Exp. Therap., 291, 147, 1999. Hsiang, B. et al. A novel human hepatic organic anion transporting polypeptide (OATP2), J. Biol. Chem., 274, 37161, 1999. Ko¨nig, J. et al. Localization and genomic organization of a new hepatocellular organic anion transporting polypeptide, J. Biol. Chem., 275, 23161, 2000. Nagel, G. et al. A reevaluation of substrate specificity of the rat cation transporter rOCT1, J. Biol. Chem., 272, 31953, 1997. Zhang, L., Schaner, M.E., and Giacomini, K.M., Functional characterization of an organic transporter (hOCT1) in a transiently transfected human cell line, J. Pharmacol. Exp. Therap., 286, 354, 1998. Kim, R.B. et al. Interrelationship between substrates and inhibitors of human CYP3A and P-glycoprotein, Pharm. Res., 16, 408, 1999. Fromm, M.F. et al. Inhibition of P-glycoprotein-mediated drug transport: a unifying mechanism to explain the interaction between digoxin and quinidine, Circulation, 99, 552, 1999. Kim, R.B. et al. The drug transporter P-glycoprotein limits oral absorption and brain entry of HIV-1 protease inhibitors, J. Clin. Invest., 101, 289, 1998. Sasabe, H., Tsuji, A., and Sugiyama, Y., Carrier-mediated mechanism for the biliary excretion of the quinolone antibiotic grepafloxacin and its glucuronide in rats, J. Pharmacol. Exp. Therap., 284, 1033, 1998.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 80/82

80

Using Mass Spectrometry for Drug Metabolism Studies

109. Yamazaki, M. et al. Biliary excretion of pravastatin in rats: contribution of the excretion pathways mediated by the canalicular multispecific organic anion transporter, Drug Metab. Disp., 25, 1123, 1997. 110. Sathirakul, K. et al. Multiple transporter systems for organic anions across the bile canalicular membrane, J. Pharmacol. Exp. Therap., 284, 1033, 1994. 111. Hooijberg, J.H. et al. Antifolate resistance mediated by the multidrug resistance proteins MRP1 and MRP2, Cancer Res., 59, 2532, 1999. 112. Chu, X.Y., Kato, Y., and Sugiyama, Y., Multiplicity of biliary excretion mechanisms for irinotecan, CPT-11, and its metabolites in rat, Cancer Res., 57, 1934, 1997. 113. Ishizuka, H. et al. Temocaprilat, a novel antiotensin-converting enzyme inhibitor, is exrected in bile via an ATP-dependent active transporter (cMOAT) that is deficient in Eisai hyperbilirubinemic mutant rats (EHBR), J. Pharmacol. Exp. Therap., 280, 1304, 1997. 114. Liu, X. et al. Correlation of biliary excretion in sandwich cultured rat hepatocytes and in vivo in rats, Drug Metab. Dispos., 27, 637, 1999. 115. LeCluyse, E.L., Audus, K.L., and Hochman, J.H., Formation of extensive canalicular networks by rat hepatocytes cultured in collagen/sandwich configuration, Am. J. Physiol., 266, 1764, 1994. 116. Ishizuka, H., et al. Species differences in the transport activity for organic anions across the bile canalicular membrane, J. Pharmacol. Exp. Therap., 290, 1324, 1999. 117. Lin J.H., Applications and limitations of interspecies scaling and in vitro extrapolation in pharmacokinetics, Drug Metab. Disp., 26, 1202, 1998. 118. Gumbleton, M. and Audus, K.L., Progress and limitation in the use of in vitro cell cultures to serve as permeability screens for the blood brain barrier, J. Pharm. Sci., 90, 1681, 2001. 119. Kariv, I., Cao, H., and Oldenburg, K.R., Development of a high throughput equilibrium dialysis method, J. Pharm. Sci., 90, 580, 2001. 120. Banker, M.J., Clark, T.H., and Williams, J.A., Development and validation of a 96-well equilibrium dialysis apparatus for measuring plasma protein binding, J. Pharm. Sci., 92, 967, 2003. 121. Wring, S.A. et al. Automated plasma protein binding screen: rapid, robust and timely for drug discovery, Abstracts of the 10th North American ISSX meeting, Indianapolis, IN, October, 2000, #85. 122. Gu, C. et al. Assays of ligand–human serum albumin binding using pulsed ultrafiltration and liquid chromatography–mass spectrometry, Combi. Chem. High Thr. Scr., 2, 353, 1999. 123. Parikh, H.H. et al. A rapid spectrofluorimetric technique for determining drug– serum protein binding suitable for high-throughput screening, Pharm. Res., 17, 632, 2000. 124. Lin, J.H., Species similarities and differences in pharmacokinetics, Drug Metab. Disp., 23, 1008, 1995. 125. Lombardo, F. et al. Prediction of volume of distribution values in humans for neutral and basic drugs using physicochemical measurements and plasma protein binding data, J. Med. Chem., 45, 2867, 2002. 126. Oie, S. and Tozer, T.N., Effect of altered plasma protein binding on apparent volume of distribution, J. Pharm. Sci., 68, 1203, 1979. 127. Doan, K.M.H. et al. Passive permeability and P-glycoprotein-mediated efflux differentiate central nervous system (CNS) and non-CNS marketed drugs, J. Pharmacol. Exp. Ther., 303, 1029, 2002.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-02.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 81/82

Drug Metabolism In Vitro and In Vivo Results

81

128. van de Waterbeemd, H. et al. Estimation of blood–brain barrier crossing of drugs using molecular size and shape, and H-bonding descriptors, J. Drug Targeting, 6, 151, 1998. 129. Lee, G. et al. Drug transporters in the central nervous system: brain barriers and brain parenchyma considerations, Pharmacol. Rev., 53, 569, 2001. 130. Clark, D.E., Rapid calculation of polar molecular surface area and its application to the prediction of transport phenomena. 2. Prediction of blood brain barrier penetration, J. Pharm. Sci., 88, 815, 1999. 131. Gratton, J.A. et al. Molecular factors influencing drug transfer across the blood– brain barrier, J. Pharm. Pharmacol., 49, 1211, 1997. 132. Audus, K.L. and Borchardt, R.T., Characterization of an in vitro blood–brain barrier model system for studying drug transport and metabolism, Pharm. Res., 3, 81, 1986. 133. Otis, K.W. et al. Evaluation of the BBMEC model for screening the CNS permeability of drugs, J. Pharmacol. Toxicol. Method, 45, 71, 2001. 134. Janusz, M.J. et al. Pharmacological evaluation of selected, orally active peptidyl inhibitors of human neutrophil elastase, J. Pharmacol. Exp. Therap., 275, 1233, 1995. 135. Thompson, T.N. et al. Selection of an elastase inhibitor with improved bioavailability from a series of structurally related analogs. Abstracts of the 4th International ISSX meeting, Seattle, WA, August, 1995, #315. 136. Burkholder, T.P. et al. Chemical synthesis and structure activity relationships for a series of substituted pyrrolidine NK1/NK2 receptor antagonists, Bioorg. Med. Chem. Lett., 7, 2531, 1997. 137. Stratford, R.E. et al. Application of oral bioavailability surrogates in the design of orally active inhibitors of rhinovirus replication, J. Pharm. Sci., 88, 747, 1999. 138. Mandagere, A.K., Thompson, T.N., and Hwang, K-K., A graphical method for estimating oral bioavailability of drugs in humans and other species from their caco-2 permeability and in vitro liver enzyme metabolic stability rates, J. Med. Chem., 45, 304, 2002. 139. Smith, D., Schmid, E., and Jones, B. Do drug metabolism and pharmacokinetic departments make any contribution to drug discovery?, Clin. Pharmacokin., 41, 1005, 2002. 140. Lipinski, CA., Drug-like properties and the causes of poor solubility and poor permeability, J. Pharmacol. Toxicol. Meth., 44, 235, 2000.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-03.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 83/102

Chapter 3 High Throughput Strategies for In Vitro ADME Assays: How Fast Can We Go? Daniel B. Kassel

3.1

Introduction

The continuing need for novel and improved drugs has led to the introduction of myriad new technologies within the pharmaceutical industry. Notably, advances in genomics, high-throughput screening, combinatorial chemistry, parallel synthesis, automation, and miniaturization have enabled large numbers of potent (active) and selective compounds to be identified at early stages of drug discovery. However, the fact that a compound is active and selective does not necessarily make it an attractive drug development candidate. To convert these ‘‘actives’’ into qualified clinical candidates has proved to be challenging. It has been reported that a significant number of compounds nominated for clinical development fail due to poor pharmacokinetics and toxicological properties (63% of all pre-clinical compounds) as shown in Table 3.1 [1]. Rodrigues [2] provides an excellent review on desirable absorption, distribution, metabolism, and elimination (ADME) properties (see Table 3.2) and offers examples of how early access to ADME information greatly enhances development success. It is generally agreed that the ‘‘ideal’’ development candidate should contain the majority if not all of these biopharmaceutical properties prior to candidate selection for development. 0-8493-1963-3/05/$0.00+$1.50 ß 2005 by CRC Press

Copyright © 2005 CRC Press, LLC

83

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-03.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 84/102

Using Mass Spectrometry for Drug Metabolism Studies

84

Table 3.1 Why compounds fail and slow down in development Reasons for failure
Toxicity, 22%
Lack of efficacy, 31%
Market reasons, 6%
Poor biopharmaceutical properties, 41%

Reasons for slowdown
Synthetic complexity
Low potency
Ambiguous toxicity finding
Inherently time-intensive target indication
Poor biopharmaceutical properties

Table 3.2 Characteristics of a developable drug










Good aqueous solubility Good pharmacokinetic profile for the intended route/frequency of dosing Balanced clearance Metabolized by several P450s (as opposed to a single isoform) No chemically reactive metabolites Minimal P450 or P-gp inhibition Minimal P450 induction Not highly plasma protein bound (<99%) Good safety margin

In order to identify chemotypes and lead compounds that contain these desirable properties, it has been recognized that studies that assess absorption, distribution, metabolism, and elimination should be initiated as early as possible in the discovery process [3–5]. By doing so, it is posited that the likelihood of development success will be maximized and development time reduced. This shift from late stage optimization of ADME properties to a strategy of identifying potential liabilities early in the discovery process has taken hold within the pharmaceutical community. Traditionally, the discovery phase focused primarily on generating structure–activity relationships. This new paradigm adds the dimension of structure–ADME relationships in parallel to structure–activity relationships as an integral part of the iterative drug discovery process, as shown in Figure 3.1 [6–9]. The properties of absorption and metabolism have received perhaps the greatest amount of attention at early stages of discovery for a variety of reasons, including the fact that oral dosing is by far the preferred route of administration to treat chronic illnesses and diseases (with the obvious exception of lifethreatening diseases such as cancer and other diseases affecting the immune system). As compounds are administered orally, they are transferred across the intestinal lumen (the process of oral absorption) into the portal vein. Subsequently, these compounds are exposed to the liver (a major organ of xenobiotic transformation) prior to entering systemic circulation. The compound may be either a substrate for or an inhibitor of the cytochrome P450 metabolizing enzymes (i.e., the monooxidases primarily responsible for metabolizing xenobiotics). The extent to which a compound is metabolized by these enzymes impacts directly the duration of action of the compound. Knowledge of the inhibitory effect of a drug molecule on any one of the key cytochrome P450 metabolizing enzymes is crucial to preventing undesirable drug–drug interactions when drugs are co-administered (a more and more Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-03.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 85/102

High Throughput Strategies for In Vitro ADME Assays

85

Figure 3.1 Iterative drug discovery now combines structure–activity with structure-ADME relationships as well as incorporating protein structural information to facilitate the compound design and synthesis.

Figure 3.2 Optimization of solubility, chemical and plasma stability, cell permeability and metabolic stability are key to ensuring successful oral delivery of compounds. Source: Lipper, R.A., [1]. With permission.

common occurrence in the clinic). Figure 3.2 highlights some of the hurdles that a compound must overcome in order to become an effective orally administered drug. Another, perhaps more pragmatic reason that absorption and metabolism have been identified as key properties to profile for at earlier stages of discovery is that they are the most well-established (experimentally) and most well-validated in vitro assays. In particular, the in vitro microsomal stability assay has been employed early in drug discovery as a precursor to in vivo pharmacokinetic profiling for the specific purpose of rank ordering compounds based on their intrinsic clearance (calculated) values and to predict in vivo clearance [10, 11]. Microsomes are readily available, the assay is relatively cheap to employ and easy to run. However, the ability to predict in vivo clearance from in vitro metabolic stability data has proved challenging. This is due in part, to the fact that metabolic stability screens incorporating microsomes typically allow for assessment of phase 1 metabolism only (e.g., oxidation, N-dealkylation). Alternatives to microsomes that enable assessment of both phase 1 and phase 2 metabolism (e.g., glucuronidation, sulfonylation) include S9 fractions, cryopreserved and fresh hepatocytes, Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-03.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 86/102

Using Mass Spectrometry for Drug Metabolism Studies

86

although the ability to predict in vivo clearance from these in vitro systems has proved to be challenging as well, principally because these in vitro assays do not take into account other processes that affect clearance, such as plasma protein binding. Importantly though, in vitro metabolic stability assays have proved extremely useful in the following ways: (1) to aid in the selection of the most attractive scaffold (starting points) to minimize the number of iterations required to produce a suitable drug candidate; (2) to prioritize/rank order compounds for in vivo profiling; and (3) to weed out compounds that are metabolized rapidly in vitro (t12<10 min). Because of the large number of hits that are now routinely identified from screening compound collections and gene family compound libraries, the industry has recognized the need for high throughput ADME assays. Fortunately, a large proportion of ADME assays can now be run in a high throughput fashion, due principally to the widespread incorporation of liquid chromatography/mass spectrometry (LC–MS) and liquid chromatography/ tandem mass spectrometry (LC–MS/MS) [12, 13]. LC–MS and LC–MS/MS have become the preferred techniques for in vitro ADME analyses due principally to enhanced sensitivity, selectivity, and ease of automation relative to traditional analytical methods. The selectivity advantages of LC–MS have made possible the ability to analyze endogenous and non-fluorescent probe substrates in cytochrome inhibition assays [14], enabled rapid permeability assessment (e.g., Caco-2 assay) [15], provided faster methods for assessing lipophilicity and solubility of drug leads, and provided much more facile assessment of liver metabolism [16, 17] for which many examples are highlighted below. To achieve high throughput, it is critical that these assays be brought forward into the discovery process as early as possible. A streamlined approach to doing this, is to initiate ADME assays at the time of biological screening. As compounds are registered and requested for biological screening, they are generally plated and arrayed in 96-well microtiter plates at a concentration of 10 mM in DMSO. Many in vitro ADME screens are readily performed in microititer plate format and it is at the time of biological screening that a number of daughter plates may also be generated for high throughput ADME, as shown in Figure 3.3. In addition to the metabolic stability assays, plasma protein binding can be performed in microtiter plate format using both the ultrafiltration method [18] and equilibirium dialysis method [19]. Furthermore, both solubility and log P screens have been performed in microtiter plate format [20, 21].

3.2

3.2.1

Fast Serial ADME Analyses Incorporating LC–MS and LC–MS/MS Fast chromatography

Recently, analysis throughput has been improved significantly and rather simply by shortening the HPLC run time. Samples can be analyzed one at a Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-03.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 87/102

High Throughput Strategies for In Vitro ADME Assays

87

Figure 3.3 By coordinating plating for ADME analyses at the same time as biological screening, ADME analyses are streamlined.

Figure 3.4 Fast chromatographic SIM analyses, [M þ H]þ ions, of multiple probe substrates for the cytochrome P450 metabolizing enzymes in under 1 min using a generic gradient of 5–95% acetonitrile following incubation of mixture with human liver microsomes. (Courtesy of B.A. Ackermann, Eli Lilly, Inc. (personal communication).)

time or as mixtures in as little as 30 s to 1 min per sample by applying fast gradients compatible with mass spectrometric detection to assess ADME properties [22, 23]. Figure 3.4 shows a nice example of how fast chromatography is applied to characterizing probe substrates for cytochrome P450 Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-03.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 88/102

Using Mass Spectrometry for Drug Metabolism Studies

88

metabolizing enzymes. These fast analyses are achieved using short chromatographic columns (e.g., 2.1  20 mm; 3- or 5-mm particle size). Generic gradients are typically employed (e.g., 5% to 95% organic in from 1 to 2 min) using mobile phases containing trifluoroacetic acid (0.035–0.05%), formic acid (0.1%) or ammonium acetate (10 mM). Flow rates are typically in the range of 1 to 5 mL/min. Compounds generally afford peaks that are symmetrical with peak widths less than 0.05 min at baseline. Monolithic columns have been evaluated more recently to reduce analysis times further. Monolithic columns are attractive in that they tend to operate at very low back pressures and are hence capable of being operated at very high flow rates. Chromatographic integrity is generally not compromised because peak capacity and resolution on monoliths is ostensibly independent of flow rate. Typically, a 4.6  50 mm monolith column operates at a flow rate of 4 to 6 mL/min. Performance is similar to that obtained using 3 mm packed columns but with flow rates much greater than those normally employed. Thus, the theoretical advantage is that chromatographic run times can be reduced by a factor of 3 to 5 times without loss in performance. Van de Merbal et al. described the use of monoliths in quantitative bioanalysis, showing the advantage of these columns over conventional C18 supports for the determination of estradiol in plasma [24]. 3.2.2

Automated data processing is instrumental to achieving high throughput ADME

Although great strides have been made in reducing chromatographic analysis times by the introduction of short, ballistic columns, a bottleneck to providing rapid turn-around of in vitro ADME information to project teams is data processing and reporting. The generation of analytical data using automated instrumentation has produced a bottleneck since data can be generated faster than it can be analyzed. Automated data acquisition software and hardware has fueled the proliferation of mass spectrometry (MS)-based computer software applications to facilitate capture and analysis of mass spectral data and provide the information necessary for decision making. The automated postdata acquisition analysis strategy is to extract the most appropriate information required for decision-making in as streamlined a manner as possible. As an example, a time-course assessment of metabolic stability (e.g., four time points and analyses in triplicate) generates 1152 samples for every plate of compounds submitted. Manual processing of so many samples would clearly render the data processing and data reporting rate limiting. To address this, numerous groups have combined the power of vendor software programs that automate peak area determinations with visual basic programming to provide simple, yet elegant methods for data processing and data reporting [25–27]. Most often, project teams are interested in both graphical and tabular presentation of data following in vitro ADME profiling. Shown in Figure 3.5 is a partial summary report of a plate of eight reference compounds and 88 test compounds received from a drug discovery project. The percent remaining Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-03.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 89/102

High Throughput Strategies for In Vitro ADME Assays

89

Figure 3.5 Time-course human liver microsomal incubations of a number of positive and negative controls as well as project compounds for which the metabolic stability profiles are represented in both tabular format and graphically above.

values of the parent compounds are color coded for easy visualization: green, >80%; orange, 80–40%; red, <40%. The project chemist receives both the summary report which helps ‘‘bin’’ the compounds into distinct classes of microsomal stability and the time course stability plots for all compounds submitted for high throughput (HT) microsomal stability analysis. This information helps the chemists prioritize compounds for further consideration as potential drug candidates. 3.2.3

Enhancing throughput by incorporating pooling strategies

Another approach is to profile multiple compounds simultaneously, known as cassette (or N-in-1) dosing. In essence, cassette dosing is a compound pooling strategy whereby compounds are profiled as mixtures so as to increase throughput, reduce the total number of samples to be analyzed and hence reduce overall analysis times. Cassette dosing strategies have been used principally for rapid pharmacokinetic profiling of drug leads. Shaffer et al. were the first to describe the application of cassette (N-in-one) dosing to Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-03.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 90/102

Using Mass Spectrometry for Drug Metabolism Studies

90

Table 3.3 Pooling strategies for pharmacokinetic evaluation of drug candidates Pooling strategies
Cassette (N-in-1) dosing
Multi-analysis (pool after individual dosing)
Single sample screens (pooled or single Cmax sample collected)

Disadvantages
Drug–drug interaction potential
Reduced sensitivity and increased complexity
Loss of information on shape of plasma concentration-time curve

facilitate rapid pharmacokinetic screening [28]. Olah et al. [29] pushed the limits of the method to an N ¼ 22 in a dog PK study, Stevenson et al. [30] demonstrated the power of this approach for the in vitro cell permeability screening of compound libraries. The number of compounds to pool is governed typically by sensitivity and solubility limits. As the number of compounds included in the pool increases, the concentration of each individual component is lowered and the greater the potential for synergistic or antagonistic effects. Additional methods for streamlining in vivo PK analysis are summarized in Table 3.3. Although analysis times may be reduced by these methods, it comes at a price. The one principal drawback with the cassette dosing strategy is that the risk for drug–drug interactions is exacerbated, which can lead to both false positives and false negatives [31]. Korfmacher effectively addressed this issue by implementing a variant of the cassette dosing technique, in essence a cassette planning strategy and coined the technique cassette accelerated rapid rat screen (CARRS) as a means of increasing in vivo pharmacokinetic throughput [32]. Ostensibly, this approach can be described as one in which drug candidates are dosed individually (n ¼ 2 rats per compound) in batches of six compounds per set, and then samples are pooled across the two rats to provide a smaller number (six per compound) of test samples for analysis.

3.2.4

Staggered (‘‘semi-parallel’’) injection and analysis

Another way to reduce cycle time further is to implement the method of staggered/segmented injections. In this method, multiple (most often two) autosamplers and columns are used in combination to eliminate common delays associated with sample loading and equilibration times. Staggered injection and elution techniques use two columns in parallel and acquire data in what is considered the useful part of chromatograms and can reduce overall analysis time as well. Wu applied this method to enhance metabolic screening analysis throughput [33]. The staggered injection and elution method, although well suited to pharmacokinetic studies, has proven subtly more challenging for diverse compound sets, where each member of the library has a unique structure and a unique chromatographic retention time. Recently, Janiszewski et al. applied this approach to streamlining metabolic stability assessment of compound libraries, with the capacity for up to 2000 DMPK samples Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-03.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 91/102

High Throughput Strategies for In Vitro ADME Assays

91

Figure 3.6 (A) Serial analysis, and (B) staggered parallel analysis, showing that four analyses can be achieved in nearly the equivalent time it takes to perform two analyses sequentially.

per day per instrument reported [34]. A comprehensive review of this higher throughput technology is described in a recent publication by Bro¨nstrup [35]. Additionally, Hiller and co-workers [36] presented a truer parallel approach by modifying a commercially available electrospray interface to support simultaneous detection of two HPLC flow streams simultaneously and applied this technique to applications in ADME as well.

3.3 3.3.1

Parallel Approaches to Speeding ADME Analyses Non-indexed parallel mass spectrometry

True parallel approaches have shown great promise for high throughput ADME screening. The parallel LC–MS methods allow multiple samples to be analyzed in parallel by injecting discrete compounds onto multiple columns and detecting them simultaneously in a single mass spectrometer ion source. Numerous groups have developed and implemented parallel LC–MS methods to support HT ADME studies [37–41]. Some systems have been designed with easy implementation in mind so that an existing LC–MS system may be converted conveniently into a parallel LC–MS system with minimal modification, as shown in Figure 3.6. Successful parallel analytical ADME analyses have been achieved using a simple Valco manifold to split the flow from a binary HPLC system evenly between eight analytical columns. The generic high throughput parallel LC–MS system, as shown in Figure 3.7, consists of a high pressure binary solvent delivery pumping system, a multiple probe autosampler (generically, either a 8-channel Gilson or 4-channel Leap), a Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-03.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 92/102

92

Using Mass Spectrometry for Drug Metabolism Studies

Figure 3.7 Generic eight-channel parallel LC–MS system consisting of a binary HPLC system, a multiprobe autosampler, a single quadrupole mass spectrometer equipped with a multiplexed (MUX) electrospray ion source, eight microbore HPLC columns (10 mm  1 mm i.d., 3 micron) and a switching value. Total mobile phase flow rate is 2.0 mL/min (0.25 mL/min for each column). The 8-channel LC–MS system allows up to four plates of compounds (or 4  1152 samples) to be run in a single day. (Source: Sage et al. Drug Discovery, 19, 49–54, 2000. With permission.)

switching valve and a single quadrupole mass spectrometer equipped with a electrospray ionization (with or without MUX). Eight samples are injected into the eight injection ports simultaneously and onto eight separate microbore columns. The pump flow rate is split into eight equivalent streams using a Valco manifold before entering the multiple probe autosampler. Eight microbore columns (dimensions obviously can vary but as an example, 10 mm  1 mm i.d., 3 mm, HQ-C18, Peeke Scientific, Redwood City, CA, USA) are connected to eight injection valves of the autosampler. For non-indexed mass spectrometric detection, the outlets of the columns are recombined using a second Valco manifold just prior to the ion source. The flow is then passed through a flow divert valve before entering the mass spectrometer. The in-line flow divert valve is used to ensure that undesirable materials eluted at the solvent front are diverted to waste to keep the ion source from becoming contaminated. When the valve is in the sampling position, the mobile phase is passed directly into the ion source without splitting. Xu et al. [37] reported that over 100,000 samples were analyzed for early ADME assessment successfully incorporating this parallel configuration. According to the authors, the system was used for assessing the time course metabolic stability (four time points in triplicate) for hits identified from screening of lead generation libraries. For each compound, a total of 12 samples are generated (four time points in triplicate) and a single plate of compounds Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-03.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 93/102

High Throughput Strategies for In Vitro ADME Assays

93

therefore yields a total of 1152 samples requiring analysis. Single column systems operated in the sequential sampling mode are capable of analyzing roughly one plate in a single day (assuming a 1-min cycle time). On the other hand, a parallel array of eight columns enables up to eight plates to be analyzed in a single day on a single instrument (theoretical maximum throughput). In practice, Xu et al. [37] reported that their maximum throughput was four plates of compounds in a single day, approaching 5000 samples analyzed for metabolic stability in a single day, the highest sample throughput yet to be reported for the metabolic stability assay to date. Similar to what was described earlier, in the absence of automated data processing tools, the post-analysis data reduction and validation processes would be exceedingly tedious. To address this data management problem, a StabilityReport macro was developed by the authors to automate these tasks. The macro imports the integration result files, deconvolutes the eight-channel results, and generates stability plots for each compound as well as a summary report for the whole plate. The macro then further analyzes and validates the results of each compound, generating a flag for any compound that has incorrect stability trend, low MS signal, or broad chromatographic peak. With this intelligent validation tool, the post-analysis data processing time is automatically reduced from about 1 day per plate (manually) to literally minutes per plate. 3.3.2

Indexed (MUX) parallel mass spectrometry

The commercialized multiplexed (MUX) electrospray interface, which introduces multiple LC flows directly into a multiplexed (indexed) electrospray ion source, has also been applied successfully for high throughput ADME applications as well [40, 41]. Yang et al. [41] identified the two main advantages of parallel LC–MS/MS using a Micromass Ultima with MUX interface to be (1) parallel analysis and (2) four-times the throughput relative to single column systems. However, disadvantages were reported as (1) cross-talk between the sprayers (negligible at concentrations <100 ng/mL but as high as 0.08% at 1000 ng/mL), (2) sensitivity less than that of a single sprayer interface (about 3 lower than the single sprayer interface) and (3) total cycle time longer than that of a single sprayer interface (hence not compatible with ultra-fast chromatography). The MUX technique was validated for rabbit, rat, mouse, and dog plasma and the authors concluded that the technique is well suited for simultaneous method validations and early discovery studies. 3.3.2.1

Higher throughput parallel technologies on the horizon?

Recently, even more massively parallel nano-LC systems have been commercialized and offer the potential for yet higher throughput ADME applications. In particular, Nanostream, Inc. recently introduced a 24-channel microfluidic HPLC system for high throughput analysis, chromatography hydrophobicity index (CHI) and solubility determinations. The technology is still in its infancy Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-03.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 94/102

Using Mass Spectrometry for Drug Metabolism Studies

94

Figure 3.8 Purity assessment of a compound library incorporating a 24-channel parallel microfluidic device. Courtesy of Nanostream, Inc.

but shows early promise. Figure 3.8 shows a parallel chromatographic separation and purity assessment of a 24 compounds from a screening library using their technology. Unfortunately, innovations in mass spectrometric detection to support this multi-parallel device have not been concomitant and may hinder its application to assays involving more complex biological matrices (e.g., metabolic stability assay, protein binding assay). 3.3.3

Automated sample preparation and analysis

While a vast amount of analytical development has been focused on addressing methods to speed analysis times, more recent efforts have been directed towards eliminating the sample preparation bottleneck. In response to sample preparation limitations and the need to meet the throughput demands of parallel synthesis, core robotics system have been implemented for automated sample preparation, data analysis, and management of results generated from in vitro ADME assays. Automating sample preparation enhances throughput, improves reproducibility and frees up valuable human resources. The principal approach taken by a number of groups involves the implementation of a core robotics system, which can be configured to either a single assay or an array of assays. Two ADME assays published recently that have been fully automated on a core robotics platform are the cytochrome P450 inhibition and metabolic stability assays [37, 42]. Jenkins et al. [42] successfully implemented a SAGIANTM core robotics system for the automated sample preparation of in vitro human liver microsomal (HLM) stability and cytochrome P450 Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-03.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 95/102

High Throughput Strategies for In Vitro ADME Assays

95

Figure 3.9 SAGIANTM core robotics system supporting in vitro metabolic stability and inhibition assays.

(CYP450) inhibition. A photo of the robotics system utilized in their laboratory is shown in Figure 3.9. Because the recombinant CYP enzymes are finicky (i.e., their stability at room temperature is poor and they are sensitive to organic solvents (>0.1% acetonitrile or DMSO)), there was concern about the ability to generate data reproducibly in a fully automated environment. Exquisitely tight software scheduling of the addition of reagents and quench solutions was paramount to successful implementation of these assays on the Sagian robot. The authors showed that a very tight correlation could be made between the automated and manual assays. A correlation of >0.92 was observed for the metabolic stability, as shown in Figure 3.10. One of the most important advantages of automating sample preparation is a reduction in the potential for human error. Jenkins et al. [42] reported that automated CYP inhibition assays have seen a reduction in coefficients of variation between replicate samples from greater than 20% for manual assays to less than 5% for the automated methods. Similarly, a qualitative and quantitative improvement was observed in the HLM stability assay as a result of automation and robotics [37]. A crucial improvement that comes from the implementation of automation and robotics is throughput. In many cases, the automation is simply better suited to tracking samples and thus the experiment time can be shortened. This is particularly true of processes that can be done in parallel. While simply improving throughput is often considered one of the most important reasons for implementing robotics, the authors noted importantly that automation eliminated much of the sample preparation burden for the Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-03.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 96/102

Using Mass Spectrometry for Drug Metabolism Studies

96

Figure 3.10 Reproducibility of the automated HLM stability method determined for 88 library compounds tested at a concentration of 4 mM. Data points represent the percent remaining at T ¼ 5 min (most variable data point) for a pair of automated assays run on the same 88 compounds. Assay is highly reproducible as evidenced by the correlation coefficient of 0.92.

scientist and nearly 50% of their time could be redirected. This resulted in some, what one might consider, less obvious advantages, including employee retention, liberation of resources for other tasks and reduced training requirements for new employees. As the authors rightly point out, these enhancements, while less quantitative and measurable, should not be overlooked as they contribute to the success of an organization.

3.4

Automated ‘‘Intelligent’’ Metabolic Stability and Metabolite Identification

In vitro HLM stability assays are a very useful first-pass assessment of potential metabolic liabilities. However, detailed information about the location of metabolic soft spots is particularly useful in understanding whether the observed liabilities are specific to a molecule’s core or introduced as part of a side chain in the lead optimization process. Whether the metabolic liability is associated with the core or side chain has clear implications for the degree to which the liability can be engineered out of a chemical series. Until very recently, metabolic stability screening and metabolite identification (metabolite ID) have been decoupled processes, that is, the metabolic stability assays are typically performed at a physiologically relevant concentration (e.g., 0.5–1 mM) and follow up metabolite ID studies involve a second incubation at a higher substrate concentration to ensure generation of Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-03.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 97/102

High Throughput Strategies for In Vitro ADME Assays

97

sufficiently high quality MS/MS information to support structure elucidation. Sensitivity enhancements in mass spectrometry instrumentation have enabled metabolite ID information to be garnered from the same incubates used to assess metabolic stability, as recently reported by Kantharaj and co-workers [43]. In particular, the authors showed for a number of cytochrome P450 substrates (verapimil, propanolol, cisapride, and flunariazine) that they were able to not only estimate metabolic turnover from a single run, but they were able to identify major metabolites, as well. To perform detailed metabolism studies on candidate compounds has been a laborious, time-consuming task. Tuning, method setup, assessing rates of metabolism by either selected ion monitoring (SIM) or selected reaction monitoring (SRM) and obtaining precursor information dependent acquisition (IDA) for metabolite ID, have all typically been distinct manual and independent processes requiring significant time by the investigator. In an effort to automate this process, prototype software was recently conceived and evaluated to automate metabolic stability assays by both Xu et al. [44] and Detlefsen et al. [45]. These software programs have been developed to provide full automation of the following: (1) on-line quantification to determine the rate of parent loss as a function of incubation time; (2) ‘‘intelligent’’ selection (i.e., qualitative trigger) of compounds for detailed metabolite ID (based on percent loss of parent at a fixed time point); (3) selection of a suitable product ion for metabolite determination using precursor ion scanning; (4) creation of a custom optimized MS1 and precursor IDA; (5) analysis of both sample and control; and (6) metabolite data analysis by Metabolite ID software. A schematic representation of the ‘‘intelligent’’ metabolic stability/metabolite ID process is shown in Scheme 3.1.

Scheme 3.1 Intelligent macro for automating metabolic stability screens and metabolite ID.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-03.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 98/102

98

Using Mass Spectrometry for Drug Metabolism Studies

Figure 3.11 A user-defined threshold for percent parent stability is pre-set in the custom software. Compounds dropping below this pre-defined threshold are automatically selected for detailed metabolite identification by LC–MS/MS incorporating data dependent acquisition, parent, and precursor ion scans.

Figure 3.12 The software intelligently ‘‘flags’’ compounds falling below the pre-set stability threshold, automatically reinjects the compounds and analyzes them in the MS/MS mode. Base peak chromatograms extracted from the precursor ion survey IDA experiment show a number of metabolites detected for (a) glyburide (seven metabolites), (b) verapamil (seven metabolites), and (c) imipramine (four metabolites).

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-03.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 99/102

High Throughput Strategies for In Vitro ADME Assays

99

The software determines metabolically labile compounds by comparing the percent parent remaining at a specific time-point (e.g., 15 min or 30 min) with user-defined criteria for triggering follow-up IDA acquisitions. The IDA data acquired allows the user to extract useful metabolite information using associated Metabolite ID software. Base peak chromatograms extracted from the precursor ion survey IDA experiment show a number of metabolites detected for the target compound. The analyst is then well-positioned to use this information to narrow down the search of peaks and retrieve IDA MS/MS data for structural information. As an example, Figure 3.11 shows the metabolic stability plots for a plate of compounds incubated with microsomes over a 30-min time course. Following data acquisition, the software automatically determined the peak areas at each time point and identified compounds that dropped below the present parent stability threshold (set to 30% in this example). Immediately following the microsomal stability assessment, flagged samples were reinjected and precursor ion IDA survey scans were automatically generated (see Figure 3.12). The precursor ion IDA scans for the cytochrome P450 probe substrates, verapimil, glyburide, and imipramine are shown. MS/MS spectra of each of these candidate metabolites provide useful information for pinpointing sites of metabolism. As this software technology enters the mainstream, it should indeed be possible to achieve significantly enhanced metabolite ID throughput. 3.5

Conclusions

Early ADME assessment of compounds is occurring at nearly every stage of the discovery process, from lead generation through lead optimization. This has occurred for two principal reasons, the first being an enlightened view of medicinal chemists as to the importance of optimizing on drug-like properties in addition to potency and selectivity. Second, and perhaps more importantly, early ADME assessment is occurring due to innovations in analytical chemistry and the wide spread proliferation of LC–MS technology. Automated sample preparation, data acquisition, and data processing have enabled ADME profiling studies to move into the high throughput realm. Only a few years ago it was suggested that high throughput ADME (unlike high throughput analysis and purification to support combinatorial chemistry and parallel synthesis) would be difficult to achieve due the fact that ‘‘with most in vitro systems, it is the analytical requirements that are usually rate limiting, relying heavily on liquid chromatography coupled with mass spectrometry . . .’’ [46]. Continued innovations in fast chromatography, parallel analysis, and automated, ‘‘intelligent’’ data processing and reporting are rapidly challenging this view. References 1. Lipper, R.A., How can we optimize selection of drug development candidates from many compounds at the discovery stage?, Modern Drug Discovery, 2(1), 55, 1999.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-03.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 100/102

100

Using Mass Spectrometry for Drug Metabolism Studies

2. Rodrigues, A.D., New technologies and approaches for increasing drug candidate survivability: lead identification to lead optimization, in CPSA, Princeton, NJ, 2001, Lee, M., Ed., CPSA. 3. Thompson, T.N., Optimization of metabolic stability as a goal of modern drug design, Med. Res. Rev., 21(5), 412, 2001. 4. Smith, D.A. and van de Waterbeemd, H., Pharmacokinetics and metabolism in early drug discovery, Curr. Opin. Chem. Biol., 3(4), 373, 1999. 5. Kerns, E.H., High throughput physicochemical profiling for drug discovery, J. Pharm. Sci., 90(11), 1838, 2001. 6. Frenette, R. et al. Substituted 4-(2,2-diphenylethyl)pyridine-N-oxides as phosphodiesterase-4 inhibitors: SAR study directed toward the improvement of pharmacokinetic parameters, Bioorg. Med. Chem. Lett., 12(20), 3009, 2002. 7. Wyatt, P.G. et al. structure–activity relationship investigations of a potent and selective benzodiazepine oxytocin antagonist, Bioorg. Med. Chem. Lett., 11(10), 1301, 2001. 8. Caldwell, G.W., Compound optimization in early- and late-phase drug discovery: acceptable pharmacokinetic properties utilizing combined physicochemical, in vitro and in vivo screens, Curr. Opin. Drug Discov., 3(1), 30, 2000. 9. Sinko, P.J., Drug selection in early drug development: screening for acceptable pharmacokinetic properties using combined in vitro and computational approaches, Curr. Opin. Drug Discov. Devel., 2(1), 42, 1999. 10. Obach, R.S., Prediction of human clearance of twenty-nine drugs from hepatic microsomal intrinsic clearance data: An examination of in vitro half-life approach and nonspecific binding to microsomes, Drug Metab. Dispos., 27(11), 1350, 1999. 11. Thompson, T.N., Early ADME in support of drug discovery: the role of metabolic stability studies, Curr. Drug Metab., 1(3), 215, 2000. 12. Rossi, D.T. and Sinz, M., Mass Spectrometry in Drug Discovery. Marcel Dekker, Inc., New York, 2002. 13. Ackermann, B.L., Berna, M.J., and Murphy, A.T., Recent advances in use of LC/ MS/MS for quantitative high-throughput bioanalytical support of drug discovery, Curr. Top. Med. Chem., 2(1), 53, 2002. 14. Rodrigues, A.D. and Lin, J.H., Screening of drug candidates for their drug–drug interaction potential, Curr. Opin. Chem. Biol., 5(4), 396, 2001. 15. Li, Y. et al. Increasing the throughput and productivity of Caco-2 cell permeability assays using liquid chromatography–mass spectrometry: application to resveratrol absorption and metabolism, Comb. Chem. High Throughput Screen., 6(8), 757, 2003. 16. Korfmacher, W.A. et al. HPLC-API/MS/MS: a powerful tool for integrating drug metabolism into the drug discovery process, Drug Discov. Today, 2, 532, 1997. 17. Eddershaw, P.J. and Dickins, M., Advances in drug metabolism screening, Pharm. Sci. Technol. Today., 2(1), 13, 1999. 18. Weiss, A.J., Performing ADME earlier—a way to gain speed and productivity. Business Briefing: Future Drug Discovery 2003. http://www.bbriefings.com/pdf/16/ fdd031_t_Millipor.pdf. 19. Kariv, I., Cao, H., and Oldenburg, K.R., Development of a high throughput equilibrium dialysis method, J. Pharm. Sci., 90(5), 580, 2001. 20. Qian, M.J. et al. A fast screening method to measure equilibrium solubility in early drug discovery process, in AAPS Annual Meeting and Exposition, Denver, CO, 2001, AAPS.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-03.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 101/102

High Throughput Strategies for In Vitro ADME Assays

101

21. Wilson, D.M. et al. High throughput log D determination using liquid chromatography–mass spectrometry, Comb. Chem. High Throughput Screen., 4(6), 511, 2001. 22. Ayrton, J. et al. Optimisation and routine use of generic ultra-high flow-rate liquid chromatography with mass spectrometric detection for the direct on-line analysis of pharmaceuticals in plasma, J. Chromatogr. A, 828(1–2), 199, 1998. 23. Scott, R.J. et al. Determination of a ‘GW cocktail’ of cytochrome P450 probe substrates and their metabolites in plasma and urine using automated solid phase extraction and fast gradient liquid chromatography tandem mass spectrometry, Rapid Commun. Mass Spectrom., 13(23), 2305, 1999. 24. van de Merbel, N.C. and Poelman, H., Experiences with monolithic LC phases in quantitative bioanalysis, J. Pharm. Biomed. Anal., 33(3), 495, 2003. 25. Whitney, J.L., Hail, M.E., and Detlefsen, D.J., Automated metabolite confirmation using data-dependent LC/MS and intelligent chemometrics, in 50th ASMS Conference on Mass Spectrometry and Allied Topics, Orlando, FL, 2002, ASMS. 26. Williams, A., Applications of computer software for the interpretation and management of mass spectrometry data in pharmaceutical science, Curr. Topics Med. Chem., 2(1), 99, 2002. 27. Korfmacher, W.A. et al. Development of an automated mass spectrometry system for the quantitative analysis of liver microsomal incubation samples: a tool for rapid screening of new compounds for metabolic stability, Rapid Commun. Mass Spectrom., 13(10), 901, 1999. 28. Shaffer, J.E. et al. Use of ‘‘N-in-one’’ dosing to create an in vivo pharmacokinetics database for use in developing structure–pharmacokinetic relationships, J. Pharm. Sci., 88(3), 313, 1999. 29. Olah, T.V., McLoughlin, D.A., and Gilbert, J.D., The simultaneous determination of mixtures of drug candidates by liquid chromatography/atmospheric pressure chemical ionization mass spectrometry as an in vivo drug screening procedure, Rapid Commun. Mass Spectrom., 11(1), 17, 1997. 30. Stevenson, C.L., Augustijns, P.F., and Hendren, R.W., Use of Caco-2 cells and LC/ MS/MS to screen a peptide combinatorial library for permeable structures, Int. J. Pharm., 177(1), 103, 1999. 31. White, R.E. and Manitpisitkul, P., Pharmacokinetic theory of cassette dosing in drug discovery screening, Drug Metab. Dispos., 29(7), 957, 2001. 32. Korfmacher, W.A. et al. Cassette-accelerated rapid rat screen: a systematic procedure for the dosing and liquid chromatography/atmospheric pressure ionization tandem mass spectrometric analysis of new chemical entities as part of new drug discovery, Rapid Commun. Mass Spectrom., 15(5), 335, 2001. 33. Wu, J.T., The development of a staggered parallel separation liquid chromatography/tandem mass spectrometry system with on-line extraction for highthroughout screening of drug candidates in biological fluids, Rapid Commun. Mass Spectrom., 15(2), 73, 2001. 34. Janiszewski, J.S. et al. A high-capacity LC/MS system for the bioanalysis of samples generated from plate-based metabolic screening, Anal. Chem., 73(7), 1495, 2001. 35. Bro¨nstrup, M., High-throughput mass spectrometry for compound characterization in drug discovery, Topics in Curr. Chem., 225, 283, 2003. 36. Hiller, D.L. et al. Application of a non-indexed dual sprayer pneumatically assisted electrospray source to the high throughput quantitation of target compounds in biological fluids, Rapid Commun. Mass Spectrom., 14(21), 2034, 2000.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-03.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:31pm Page: 102/102

102

Using Mass Spectrometry for Drug Metabolism Studies

37. Xu, R. et al. Application of parallel liquid chromatography/mass spectrometry for high throughput microsomal stability screening of compound libraries, J. Am. Soc. Mass Spectrom., 13(2), 155, 2002. 38. Korfmacher, W.A. et al. Demonstration of the capabilities of a parallel high performance liquid chromatography tandem mass spectrometry system for use in the analysis of drug discovery plasma samples, Rapid Commun. Mass Spectrom., 13(20), 1991, 1999. 39. Hiller, D.L. et al. High throughput quantitation using indexed multiprobe electrospray technology in support of drug discovery, in 48th ASMS Conference on Mass Spectrometry and Allied Topics, Long Beach, CA, 2000, ASMS. 40. Bayliss, M.K. et al. Parallel ultra-high flow rate liquid chromatography with mass spectrometric detection using a multiplex electrospray source for direct, sensitive determination of pharmaceuticals in plasma at extremely high throughput, Rapid Commun. Mass Spectrom., 14(21), 2039, 2000. 41. Yang, L. et al. Evaluation of a four-channel multiplexed electrospray triple quadrupole mass spectrometer for the simultaneous validation of LC/MS/MS methods in four different preclinical matrixes, Anal. Chem., 73(8), 1740, 2001. 42. Jenkins, K.M. et al. High throughput cytochrome P450 inhibition assays using parallel LC/MS technologies. In: 48th ASMS Conference on Mass Spectrometry and Allied Topics, Long Beach, CA, 2000. ASMS. 43. Kantharaj, E. et al. Simultaneous measurement of drug metabolic stability and identification of metabolites using ion-trap mass spectrometry, Rapid Commun. Mass Spectrom., 17(23), 2661, 2003. 44. Xu, R. et al. A fully automated system for metabolic stability and metabolite ID measurements, in 51st ASMS Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, 2003, ASMS. 45. Detlefsen, D.J. et al. A total analysis solution for metabolic stability and detailed metabolite profiling, in 51st ASMS Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, 2003, ASMS. 46. Eddershaw, P.J., Beresford, A.P., and Bayliss, M.K., ADME/PK as part of a rational approach to drug discovery, Drug Discov. Today., 5(9), 409, 2000.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 103/150

Chapter 4 Matrix Effects: Causes and Solutions Hong Mei

4.1

Introduction

Due to the inherent selectivity and sensitivity of tandem mass spectrometry combined with the separation power of a liquid chromatographic system, liquid chromatography–tandem mass spectrometry (LC–MS/MS) has become the method of choice for quantitative analysis for both drug discovery and drug development studies in most pharmaceutical companies. When LC–MS/ MS was first introduced, it was generally assumed that the high specificity and selectivity of LC–MS would eliminate extensive sample preparation and reduce time required for the chromatographic analysis, thus making LC–MS/MS a much better method than the classical HPLC/UV methods.1 The fast turnaround time of bioanalytical analysis with the use of LC–MS/MS has greatly accelerated pharmaceutical research. However, in more recent years, matrix ionization suppression issues in LC–MS/MS assays have been reported2–4 and these matrix effects have become one of the most important causes for failures and errors in bioanalysis.5 The existence of different matrix components in study samples as compared with calibration samples can cause many fold errors in accuracy, which can invalidate the analytical results and the calculation of pharmacokinetic parameters based on these data. Matrix ion suppression (the most common matrix effect) not only affects quantitative analysis in pharmacokinetic studies, but can also hamper qualitative analysis in metabolite identification studies. 0-8493-1963-3/05/$0.00+$1.50 ß 2005 by CRC Press

Copyright © 2005 CRC Press, LLC

103

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 104/150

Using Mass Spectrometry for Drug Metabolism Studies

104

For example, the severe ion suppression caused by nonvolatile salts in bile and urine can make even major metabolites undetectable.6 With the increasing number of LC–MS/MS assays that are applied to more complex matrices, such as cell cultures, plasma, bile, urine, feces, and tissue samples, the issue of matrix effects has gained more and more attention. Extensive studies have been conducted to obtain a better understanding of the mechanism of electrospray ionization and the factors that contribute to ionization suppression. At the same time, different approaches for the evaluation of matrix effects have been introduced, and various strategies for overcoming matrix effects have been proposed. 4.1.1

What are matrix effects

In the FDA guidelines for bioanalytical validation, matrix effects are defined as ‘‘interference from matrix components that are unrelated to the analyte.’’7 This broad definition includes both ion enhancement and ion suppression; these effects can be caused by ionization competition of co-eluting components, ‘‘cross-talk’’ from metabolites or internal standards, signal enhancement caused by in-source fragmentation of metabolites, and low or variable analyte recovery due to strong binding of analytes to biological matrices. For bioanalytical LC–MS/MS assays, matrix effects usually refer to signal reduction or enhancement enused by co-eluting components that are not related to the analytes. Matrix effects can cause significant errors in precision and accuracy, thereby invalidating the assessment of pharmacokinetic results based on these LC–MS/MS assays. Compared to ion enhancement, ion suppression is more problematic in that it will reduce the sensitivity of the assay. If one cannot control the variability caused by matrix effects, both ion enhancement and ion suppression can be challenging, because both will result in poor reproducibility of results. When matrix effects cause differential suppression or enhancement between calibration samples and study samples, the accuracy of the assay results will be significant affected. Based on our limited understanding of LC–MS/MS matrix effects, the following common perception of matrix effects have been widely accepted: (1) atmospheric pressure chemical ionization (APCI) is less sensitive than electrospray ionization (ESI) in regard to matrix effects, and (2) extensive sample preparation may be required due to the need to separate the analyte from co-eluting endogenous matrix components. Recently, studies have shown that APCI can also exhibit severe matrix effects and that exogenous material can also be a major cause of ionization suppression. Therefore, a thorough understanding of the mechanisms of matrix effects can help one to avoid the problem of matrix effects. The aim of this chapter is to discuss the possible mechanisms of LC–MS/ MS matrix effects, to provide the guidelines for evaluating matrix effects and to propose strategies for overcoming matrix effects. By using this information, researchers should be able to develop faster and more reliable LC–MS–MS assays that are devoid of matrix effect problems. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 105/150

Matrix Effects: Causes and Solutions

4.2

105

Recent Literature Review

4.2.1

Mechanistic studies of matrix effects

The mechanism of matrix induced ion suppression or ion enhancement is still not fully understood, this is in part due to the fact that the mechanism of electrospray ionization has proven to be very difficult to establish. However, extensive investigations have been conducted to gain a better understanding of the electrospray ionization process and the causes of matrix induced ion suppression. Some investigations have focused on each individual step involved in the production of ions from solution phase to gas phase, while others have tried to identify the source of the interfering matrices. 4.2.1.1

Ionization process for analyte and matrix components in ESI

There are a number of papers that have described details of how ions are first generated in the solution phase and then converted to gas phase ions in the electrospray ionization (ESI) process.3,8–12 Basically, there are four critical steps in ESI that are important to mass response: (1) excess charge generation in the Taylor cone and ESI droplets; (2) uneven fission of parent droplets to very small, highly charged offspring droplets that readily transform to gas phase ions; (3) formation and transformation of gas phase ions and (4) separation of neutrals from charged ions. In ESI, the liquid is an electrolyte solution that is continuously flowing into a high voltage capillary tip where primary droplets are formed in the Taylor cone that is generated at the capillary tip. Due to the charge separation that is caused by the voltage gradient, these droplets have excess charge that exists on the surface of the droplet while solvated paired ions or neutrals are present in the inner part of the droplet (inner phase). The concentration of excess charge is determined by the flow rate and applied voltage, and its production rate is equal to the maximum rate of production of vapor phase ions. With applied heating and desolvation gas, continuous solvent evaporation at constant charge leads to droplet shrinkage and uneven fission to form offspring droplets from the surface phase of parent droplets, thus with significantly higher mass-to-charge ratio on the offspring droplets. The inner phase of large parent droplets contains ion pairs that will be less possible to be detected by the mass spectrometer. The repeated evaporation and uneven droplet fission leads ultimately to gas phase ions by one of two model mechanisms: evaporation from droplet surfaces during the fission process (the charged residue model),13 or formation of final droplets containing only one ion at the end of fission process (ion evaporation model).14 Gas phase ions would undergo gas phase ion reactions in the atmospheric ion sampling regions. Finally, the ultimate gas phase ions in the sampling region will be sampled through an orifice, into the differentially pumped regions of the mass spectrometer, while the neutrals, solids and liquids will be blocked by various means, e.g., an interface metal plate (skimmer) and curtain gas. Any matrix components that interfere with Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 106/150

Using Mass Spectrometry for Drug Metabolism Studies

106

any of the above-mentioned process could affect the ionization efficiency of an analyte. Many studies have already proven that for ESI, the intensity of ion signal is dependent on the chemical nature of the analyte, as well as many other factors, including the presence and concentration of electrolytes in the liquid,15 volatility of the solvent,11,16 surface activity of the droplet9,12,17,18 presence of nonvolatile components,15,19 flow rate of electrosprayed solution,20 concentrations of other ionizable species9,12 and competition of gas phase ion-transfer reaction between analytes and other ionized ions.11,16,22,23 4.2.1.2

Property of analyte and ESI response

In addition to instrumental parameters, the most important factor that determines ESI responses is the physical and chemical nature of the analyte and co-eluting components. There are two models, the ion-evaporation model and the equilibrium-partitioning model, that have been developed to predict the ESI response of an analyte based on the properties and concentrations of the analyte and co-eluting components. 4.2.1.2.1

Evaporation rate and ion-evaporation model

Based on the ion evaporation model (IEM) of gas phase ion formation described by Irbarne & Thomson, Tang and Kebarle proposed an equation to predict ESI response of analyte A in the presence of electrolytes (E) and other components (M) using the evaporation rates and the concentrations.14,21,24 The typical equations are listed below. Two components: IA ¼ fp

Three components:

ka ½A
I: ka ½A
þ ke ½E


IA ¼ fp

ka ½A
I: ka ½A
þ km ½M
þ ke ½E


ð4:1Þ

ð4:2Þ

As described by Tang and Kebarle, the product fp is a factor that was assumed to be independent of the chemical nature of the ions, f is the fraction of charges on the droplets that are converted to gas phase ions (desolvation efficiency) and p is the ion-sampling efficiency of the system. The bracketed ions are the concentrations of the analyte (A), a matrix component (M) and electrolyte species (E) and the k’s are the rate constants of ion evaporation.21 The rate constant for each ion can be calculated experimentally from the free energy of activation (
G).3 The value of
G depends on the number of the charges (N) and the radius of the droplet (R), and the distance of ion charges from the surface of the droplet (D). D reflects the extent of solvation. Strongly solvated ions, such as Liþ, hold on strongly to a large number of solvent molecules and have larger D, thus need more energy to evaporate. Generally, the ion Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 107/150

Matrix Effects: Causes and Solutions

107

evaporation rate constant k increases with N, decreases with R and decreases with D.3,11 Basically, this model predicts that the ions with higher charge density and lower desolvation will have higher ESI responses. This was the first mathematical model that established the dependence of ion intensity on its concentration. It also successfully modeled the ion suppression effect of NH4Cl on a series of analytes.11 Furthermore, it also explained the saturation of calibration curve by suggesting that competition occurs when the sum of electrolyte species (IE) and analyte ion (IA) exceeds the total fixed available current (I). It demonstrated that the ion intensity, IA, depends only on the ratio of ka/kb, but not on the individual ka, as illustrated by Kebarle and Peschke in the following relationship developed using Equation 4.1:11 Ia ka ½A
¼ Ib kb ½B


or

Ia ka ¼ Ib kb

when ½A
¼ ½B
:

ð4:3Þ

However, this model was built using data generated by a variety of metal cations that have different ion evaporation rates but no surface activity. Furthermore, this model of ion evaporation failed to predict the ESI responses for more complex organic molecules where surface activity plays an important role. The factor of surface activity had to be accounted for in the explanation of the analyte response at the high concentration range; however, surface activity was not included in the mathematical equation.21 Due to this reason, this model can only predict the response within a narrow range of analyte concentration. Furthermore, due to the exponential relationship between k and
G, a small experimental deviation in
G will cause a significant difference in k. As a result, the calculated theoretically generated rate constant (k) based on an experimentally obtained
G for the same ion exhibited a large range of values.11 4.2.1.2.2

Surface activity and partitioning-equilibrium model

With the consideration of the importance of surface activity, Enke developed the partitioning-equilibrium model to predict the ESI response of an analyte with a single charge in the presence of matrix components based on the surface activity of the analyte and co-eluting components as well as the competition for the limited number of excess charge sites on the surface of the initial droplet without invoking the effect of ion evaporation.9 Excess charge on the surface of the Taylor cone and the droplets is generated by the intense electric field at the ESI capillary tip. The concentration of excess charge [Q] is equal to the circuit current (I ) divided by the product of the Faraday constant (F ) and flow rate (G). In other words, [Q] is determined by the applied voltage and flow rate. Therefore, the rate of production of surface excess charge is a constant at a fixed experimental condition. Thus, [Q] is also the upper limit for the concentration of observable ions generated by the electrospray process and Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 108/150

108

Using Mass Spectrometry for Drug Metabolism Studies

equal to the sum of the concentrations of all the charged species on the surface, e.g., [Aþ]s, and [Eþ]s.9 Therefore, [Q] can be described by the following equation: ½Q
¼ IF=G ¼ ½Aþ
s þ ½Eþ
s :

ð4:4Þ

As described previously, ESI droplets can be divided into two parts: the charged surface phase and the neutral interior phase. In all proposed mechanisms of gas ion formation, gas phase ions that are freed from the liquid phase are those charged ions at the droplet surface, even though ions are free to partition between the surface and interior phases. Therefore, ions that are better able to partition into and stay inside the surface phase would expect to have higher ESI responses than ions trapped in the interior phase. Surface affinity or surface activity is closely related to the nonpolarity of a molecule. Usually, higher hydrophobicity will lead to higher surface activity. An equilibrium-partitioning coefficient (K) was used in this model and defined for each analyte as the ratio of its concentration on the droplet surface phase to that in the interior phase. For the analyte ion Aþ and the necessary electrolyte ion Eþ, the equilibrium partition reactions and their partition coefficient can be described as follows: ðAþ X Þi , ðAþ Þs þ ðX Þi , KA ¼ ½Aþ
s ½X
i =½Aþ X
i ,

ð4:5Þ

when [AþX]  [Aþ]s, and CA ¼ [AþX] þ [Aþ]s, KA ¼ ½Aþ
s ½X
i =CA : ðEþ X Þi , ðEþ Þs þ ðX Þi ,

ð4:6Þ

KE ¼ ½Eþ
s ½X
i =½Eþ X
i ,

ð4:7Þ

when [EþX]  [Eþ]s, and CE ¼ [EþX] þ [Eþ]s, KE ¼ ½Eþ
s ½X
i =CE :

ð4:8Þ

Where X denotes the counter ions, CA and CE are the total analyte concentration and the total electrolyte concentration, respectively. The two components Aþ and Eþ are both competing for the supply of a fixed number of surface charges. Therefore, this equation and equilibrium constant for this competition can be expressed as ðAþ X Þi þ ðEþ Þs , ðAþ Þs þ ðEþ X Þi , KA =KE ¼ ½Aþ
s ½Eþ X
i =½Aþ X
i ½Eþ
s ,

ð4:9Þ

when [AþX]  [Aþ]s, and [EþX]  [Eþ]s, KA =KE ¼ ½Aþ
s CE =½Eþ
s CA :

Copyright © 2005 CRC Press, LLC

ð4:10Þ

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 109/150

Matrix Effects: Causes and Solutions

109

[Aþ]s can be expressed as follows, if we combine Equations 4.10 and 4.4, as demonstrated by Enke.9 ½Aþ
s ¼

CA KA ½Q
CA KA þ CE KE

ð4:11Þ

If we agree to the assumption that the mass response of a certain ion is proportional to the concentration of that ion in the surface phase of droplet, then the ESI response of analyte A (RA) can be expressed as follows: RA ¼ pf

CA KA ½Q
: CA KA þ CE KE

ð4:12Þ

Following the convention of Kebarle, p and f are the efficiency of and sampling efficiency of the system, respectively. As pointed out by Enke, this equation has exactly the same form as Equation 4.1, except the values of k in Equation 4.1 are the evaporation rate constants while the values of K in Equation 4.12 are the equilibrium-partitioning coefficients.9 Equilibrium-partitioning coefficients (the values of K) reflect the basicity, charge density and nonpolarity of charged molecules. The basicity guarantees that molecules carry protons, while their charge density and nonpolarity determine how likely they are to stay on the droplet surface.25 High surface activity also has a sequential enriching effect on ESI response through uneven fission. For the uneven fission process, it was believed that the offspring droplet was generated from the surface phase of its parent, and thus attained the significantly enhanced mass-to-charge ratio on the offspring droplets.25 As illustrated in Figure 4.1, with this uneven fission process, the concentration of surface active ions can be much higher in the ultimate offspring droplets, while the concentration of a non surface-active compound will be reduced. In order to theoretically model this effect, Cech and Enke extended the partitioning-equilibrium process from initial ESI droplets to the offspring droplets and created the charge overlap model.12 The modeling results demonstrated that the effect of uneven fissioning of mass and charge compounded the effect of partitioning within an ESI droplet and make the issue of droplet surface affinity even more important in determining ESI response.12 Low solvation energy usually correlates to high surface activity. Therefore, compounds with high surface activity will have high evaporation rate constants. As a result, both the ion evoporation model (IEM) and the charged residue model (CRM) predict the similar dependence of the ion intensities observed in ESI. But this does not mean that the role of ion evaporation can be ignored. With the partitioning-equilibrium model, ions that have no surface activity, such as alkali ions, Liþ, Naþ, Kþ, Csþ, are expected to exhibit approximately the same ion intensities as solutions containing the alkali salts (MþX) at the same concentration. However, increasing values of k were Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 110/150

Using Mass Spectrometry for Drug Metabolism Studies

110

Figure 4.1 compounds.

Schematic diagram of the enhancing effect of uneven fission for surface active

observed from Liþ to Csþ,26 therefore, both ion evaporation and surface activity play important roles in ESI.10 For compounds that have no surface activity, ion evaporation plays a major role. Most new pharmaceutical candidates have a hydrophobic region on the molecules,27 and the equilibriumpartitioning model is more appropriate for estimating their ESI responses. Since the response of ESI is highly dependent on the hydrophobicity of analytes, one could predict the MS response based on the retention time on reversed-phase HPLC.28 Unlike the ion-evaporation model, which can only predict the MS response within certain range using the same ka/ke, this model successfully predicted the MS response in a wide range of concentrations (109 to 103 M) with the same value of KA/KE.15 Furthermore, the effect of CA, the KA/KE ratio, CE and [Q] on the [Aþ]s can be simulated for a better understanding of the contribution of each component.15 As illustrated by Enke’s group, the analyte surface concentration [Aþ]s is a quadratic function of CA, CE, KA/KE and [Q].15 As shown in Figure 4.2, when [Aþ]s is plotted against CA, two portions of the whole curve, a linear portion at lower CA and a saturated portion at higher CA, are generally observed. At the low CA region, [Aþ]s is proportional to CA because there is plenty of extra charge for analyte ions (CA  [Q]), regardless of the value of KA/KE. With [Aþ]s approaching [Q], in another expression, when CA  [Q] þ CE/(KA/KE), saturation occurs. The start of this turning point and the curve shape at the saturated region is controlled by the value of KA/KE. Analytes with higher KA/KE values (e.g., analytes with higher surface activity) Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 111/150

Matrix Effects: Causes and Solutions

111

Figure 4.2 Effect of KA/KE on analyte surface concentration, [Aþ]s, predicted using the following equation: ½Aþ
2s ðKKAE  1Þ  ½Aþ
s ½½Q½ðKKAE  1Þ þ CA KKAE þ CE
þ CA ½Q
KKAE ¼ 0. CA ranges from 109 to 103 M, CE ¼ [Q] ¼ 105 M. (Source: Constanopoulos et al. J. Am. Soc. Mass Spectrom. 10, 625, 2001. With permission.)

had a wider linear range and a sharper response slope. On the other hand, analytes with lower KA/KE values (e.g., analytes with lower surface activity) had a narrower linear response range, with their response curve showing more curvature and gradually reaching [Q].15 This model also predicts that the analyte response will decrease as electrolyte concentration (CE) increases. However, this is contradicted by the observed data where the analyte response increases to a maximum as CE increases to 104 M and decreases with further increases of CE.15 It was explained that an increase of CE increases the conductivity of the solution and thus increases the spray current [I ] and the excess charge [Q]. With the increased of [Q], more analyte ions, but not electrolyte ions, can be ionized at the surface phase and transferred to gas phase due to its higher KA/KE ratio. However, further increase of CE causes a loss in ion transfer efficiency ( p) or desolvation efficiency ( f ), thus reducing the analyte response with a further increase of [Q].15 Overall, this model simplified the effect of salt and therefore can only be used to predict the analyte responses at salt concentrations less than 105 M. With the information provided by this model, we now learn that high surface-active ionic contaminants are undesirable, not only because their highintensity peaks may interfere with the analyte mass spectrum, but also because they will suppress the spectrum of the analyte by competing for the limited excess charge on the droplets. It is worth pointing out that the relative ion yields represented by the relative values of the coefficients KA, KB, KE etc., Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 112/150

Using Mass Spectrometry for Drug Metabolism Studies

112

depend on a complex sequence of events which require consideration not only of bulk to surface equilibriums and ion evaporation rate, but also droplet evolution schemes and other experimental settings.26,29 For example, the surface partitioning coefficient of a low surface-active analyte can be higher when smaller initial droplets are formed with less fission steps required before gas phase ion formation begins, such as in nanospray techniques.6,30 4.2.1.2.3

pKa and solvent pH

Since ESI requires protonation or deprotonation, it was believed, initially, that pKa and pH of solution would play an important role in ESI response. However, protonated ions of basic analytes can be observed when the pH is higher than the analyte pKa.31,32 One possible explanation for this phenomenon is that the fixed amount of surface excess charge is dictated by the solution flow, and the applied voltage, not the solution pH.9 In other words, the analyte or other components that stay on the surface phase of the ESI droplet can be protonated even if their pKa values are below the solution pH. Besides, uneven fission process will enrich the signal of the surface-active components but not those ion pairs that stayed inside the droplet. Furthermore, gas phase ion reactions can also generate charged ions from neutrals.32,33 Therefore, pKa and solvent pH are not as important as the surface activity in producing an ESI response. 4.2.1.3

Possible mechanisms for ion suppression in ESI

The understanding of how the ESI response is controlled by instrument settings, properties of the analyte and co-eluting components have brought us closer to understanding the mechanisms of ion suppression. The following section will focus on the possible mechanisms involved in both the solution phase and the gas phase, as shown schematically in Figure 4.3. 4.2.1.3.1

Competing for limited surface excess charge

Even though there are different mechanisms (IEM and CRM) for gas phase ion formation, both theories agree that initial gas ions are generated from the surface phase of ESI droplets. Both the ion-evaporation model (Equation 4.1) and the partitioning-equilibrium model (Equation 4.12) are used to predict that the ESI response in the presence of other components is based on competition for a fixed amount of ESI current (I ) or excess charge (Q) which is controlled by the applied voltage and the flow rate. Since I is proportionally correlated to Q as expressed by Equation 4.4, the competition for I and for Q are equivalent. Furthermore, since the excess charges all reside on the surface of the droplets, competition for the limited charge or competition for the limited surface space are both possible. Based on Equation 4.12, it is clear that when total ion concentration in the droplet exceeds [Q], there will be a competition among the ions for the excess surface charge. Matrix induced ion suppression can be Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 113/150

Matrix Effects: Causes and Solutions

Figure 4.3 ionization.

113

Schematic diagram of possible mechanisms of ionization suppression for electrospray

explained in part as the competition for the limited excess surface charge. The matrix components with higher K are more surface active, therefore they would be expected to out-compete the low K analytes for the limited excess charge or limited space on the initial droplet surface. The uneven fission process will produce an even more profound ion suppression effect when surface-active matrices are present. The high surface-active matrices will out-compete the low surface-active analyte in each uneven fission process and occupy the droplet surface in each subsequent offspring droplet. In this case, analytes, would be preferentially left in the interior neutral phase of each preceding droplet and therefore became undetectable. Surfactants are molecules with both polar and hydrophobic regions and known to prefer the air–liquid interface. Due to their high affinity to the droplet surface, surfactants are expected to have high ESI responses. Many experiments have shown that surfactants significantly suppress the ESI response of other analytes.12,14 Therefore, it is not hard to understand that surfactants, such as Tween 80, that are used as dosing excipients to improve the solubility of drug candidates, could cause significant ESI ion suppression for co-eluting analytes in LC–MS/MS assays.34–36 Polymers that are used as co-solvents to improve the solubility of hydrophobic compounds usually have both hydrophilic and hydrophobic Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 114/150

Using Mass Spectrometry for Drug Metabolism Studies

114

parts in the same molecule, therefore these polymers also have high surface activity. The attainment of improved solubility using PEG400 is through the bridging effect of this polymer between the hydrophobic analyte and water. The backbone of polyethelene ( CH2CH2 )n of PEG400 will associate with the nonpolar part of hydrophobic compounds via hydrophobic interaction while the terminal hydroxyl group ( OH) will hydrogen bond with water. At the same time, this hydrophobic backbone of polyethelene also provides for sufficient surface activity of PEG400. Therefore, if PEG400 is contained in the plasma sample and cannot be separated from analytes, matrix effects will often be observed. Several reports have described severe matrix effects from plasma samples obtained from laboratory animals dosed with formulations containing PEG400.34–37 Lipophilic components such as long-chain (C12–C16) fatty acids, glycerophosphocholine lipids, phosphatidylethanolamine, sphyngomylein, and triacylglycerols in plasma and tissue sample all have high surface activity, therefore these components can be part of the cause of ion suppression effects. It was demonstrated that lyso-phosphatidylcholine (C16:0, C18:0, C18:2) present in serum contributed to the matrix effects observed in an assay for verapamil.38 In our laboratory, we have observed that hydrophobic matrix effects are more often observed in tissue samples, especially in brain samples; part of the reason for this effect might be that brain tissue contains more lipid components that are surface active than those found in plasma samples. 4.2.1.3.2

Incomplete evaporation

It is a well-known fact that the presence of nonvolatile salts such as phosphate and sulfate in the mobile phase is deleterious for ion sources of LC–MS/MS systems due to the deposition of solid material onto surfaces of the source. Nonvolatile components in biological sample can also cause significant ion suppression for early-eluting compounds. Ions that are generated in droplets can only be detected after they are emitted into the gas phase, therefore evaporation is a critical process for the ultimate gas phase ion generation. The efficiency of gas phase ion generation depends on the evaporation efficiency or desolvation efficiency ( f ), size and charge of the initial ESI droplets. Nonvolatile material in the biological sample can change the volatility, viscosity, and conductivity of the sprayed solution, causing incomplete evaporation and weak Taylor cone emission, hindering the process of uneven fission, and decreasing the efficiency of gas phase ion generation; this effect results in a reduction of the number of analytes that are converted to the gas phase and then detected by the mass spectrometer system.15 In order to test these hypotheses, King and colleagues designed a set of experiments comparing the amount of analyte and nonvolatile components depositing on the interface plate with or without nonvolatile material present in the sprayed solution.19 If the nonvolatile components cause incomplete evaporation, then both the analyte and the nonvolatile components would stay in the solution phase and be sprayed onto the interface plate. The tested nonvolatile samples were Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 115/150

Matrix Effects: Causes and Solutions

115

ammonium sulfate and extracted plasma samples prepared by protein precipitation, liquid–liquid extraction and solid phase extraction, respectively. It was shown that the samples prepared by protein precipitation contained the most nonvolatile material. Furthermore, it was demonstrated that the amount of nonvolatile matrix components was correlated to the extent of ion suppression. With more nonvolatile material present, more analytes were deposited on the interface plate than were transferred to the gas phase.19 Instrument interface designs with inefficiency in the heating and desolvation processes are more prone to matrix effects due to the cause of incomplete evaporation when analytes are eluted with nonvolatile components. For example, it has been shown that one design of the APCI probe made by Micromass had issues in terms of low sensitivity39 and was more prone to matrix effects than other vendors’ designs for APCI probes.40,41 It was also demonstrated that decreasing the interface chamber pressure by attaching a roughing pump would improve the APCI response of this one design;39 these findings indicated that desolvation or ion transmission characteristics of the unmodified Micromass APCI interface were not optimized. This might be one of the reasons that this APCI probe design was more prone to matrix effects than other vendors’ APCI probes. A new Micromass APCI probe (IonsSabreÕ , Micromass, UK) has been introduced and its design includes an increased heating capacity and efficiency by using an optimized ceramic heater with gradient heating distribution, so that the efficiency of desolvation is improved therefore the ionization efficiency and sensitivity of this new design should be better than the previous design. Currently, the most recent generation of APCI probes of tandem mass spectrometers by different manufactures are all made with enhanced heating capacity and efficiency, some with even improved gas dynamics. The advanced Turbo VÕ source for the Sciex API 4000 MS/MS system is equipped with dual ceramic heaters and improved gas dynamics which maximize the desolvation efficiency, thus providing greater efficiency in ionization and increased sensitivity and reduced peak tailing caused by crosscontamination at the same time. In a recent report, it was demonstrated that fewer matrix effects were observed with the same set of samples prepared by protein precipitation using the Sciex API 4000 as compared with the Sciex API 3000.42 It has been demonstrated that polar matrices cause matrix effects mostly due to incomplete evaporation as opposed to neutral evaporation.19 If this type of ion suppression was caused by the competition of charge from matrix components, then analytes could exist as neutrals in the gas phase in ESI, but would be ionized by APCI. King and colleagues built a combined ESI–APCI source, expecting to see an improved signal when using the corona discharge for neutrals in gas phase.19 However, no improvement was observed under these conditions for rat plasma samples prepared by protein precipitation; these data indicated that the amount of neutral analytes existing in the gas phase was negligible. Therefore, the nondetectable analytes in this sample set must have existed as either liquid or solids in the ESI source. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 116/150

Using Mass Spectrometry for Drug Metabolism Studies

116

4.2.1.3.3

Ion pairing

Ion suppression caused by strong acids, like trifluoroacetic acid (TFA), has been a problem for ESI applications in proteomics. This type of ion suppression was originally believed to be primarily due to the high surface tension and the high conductivity of the solution which resulted in unstable spray effects.43,44 However, further studies have shown that the ion suppression caused by TFA is also due to its strong ion-pairing effect with basic analytes.30 The strong ion-pairing of TFA with basic analytes keeps analytes in the interior neutral phase of ESI droplets and prevents the analytes from partitioning to the surface phase. Based on this mechanism, a solution of TFA fix was successfully proposed and tested. The TFA fix is a method to reduce the ion suppression caused by TFA using a post-column addition of a solution containing a high concentration of propionic acid in 2-propanol at the flow rate half that of the mobile phase flow rate.30 As proposed by Apffel and colleagues, when TFA ion-pairs with a basic analyte, both TFA and the analyte are restricted in the interior neutral phase and therefore cannot be released to the gas phase, even though TFA is a volatile acid. When a weak and less volatile acid, such as propionic acid, is added at high concentration, its mass effect will compete with TFA for ion pairing with the basic analyte and in turn releases TFA into the surface phase of droplets that go into the gas phase. At the same time the weaker association between weak acid and basic analyte will make more analytes partition into the surface phase as droplets that are released to the gas phase. This ion-pairing mechanism was further corroborated by the observation of ion enhancement of ‘‘almost neutral’’ compounds, such as diphenylthiourea, in the presence of 0.2% TFA. As a strong acid, TFA cannot pair with the analyte in this situation; however, it does improve the protonation of the analyte.45 4.2.1.3.4

Competition for protons in gas phase

ESI is a soft ionization technique that involves transferring the ions from solution phase to gas phase. The detected gas ions are initially generated from solution phase, and only those very stable singly charged alkali ions will stay in the gas phase without any chemical reactions. Since the gas phase environment is different than the solution phase, many ions can be modified in the gas phase after they are initially generated in the solution phase. These gas phase chemical reactions, such as charge neutralization, charge stripping and charge transfer, can also have a significant effect on ESI response. The proton transfer reaction is a fundamental chemical reaction that has been investigated in both solution and gas phases. Several studies have demonstrated that gas phase proton transfer reactions occur in ESI.11,22,23 The order of basicity in the solution phase can differ from that in the gas phase, thus a proton transfer to a strong gas phase base can enhance the formation of some ions while suppressing the formation of others. A special study was conducted to study the impact of gas phase proton affinities on the Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 117/150

Matrix Effects: Causes and Solutions

117

ESI responses.16 This study demonstrated that ions present in solution can be altered in the gas phase by the presence of molecules that are stronger gas phase ions. If matrix components are stronger gas phase ions, they will outcompete gas phase analyte ions for protons and suppress the response of analytes. It has been suggested that matrix effects caused by PEG400 are due to gas-phase proton competition.34 4.2.1.4

Matrix sensitivity: ESI or APCI?

In order to understand what ionization mode is more subjective to matrix effects, we first need to understand the differences in the two ionization modes. Even though there are several models that have been proposed to explain how gas phase ions are produced via charged droplets in electrospray, it was generally agreed that for ESI, most ions are generated in solution phase followed by transferring to the gas phase; while for APCI, molecules (not ions) are first vaporized into gas phase followed by being ionized by the corona discharge process. In other words, the ionization efficiency can be affected by matrix components in both solution phase and gas phase for ESI, while only in gas phase for APCI. The difference in ionization process in these two different modes has been utilized to determine whether the dominant impact of matrices is in solution phase or gas phase.19 It was found that ESI is more susceptible to plasma matrix effects than APCI, because these matrices usually contain large amounts of nonvolatile components and high concentrations of electrolytes: all these have been proven to have a dominant effect in the reduction of ionization efficiency in the solution phase, and thus reduce the amount of analytes being transferred to the gas phase.19 Compared to APCI, there are more steps involved in ESI that are susceptible to matrix effects. Matrix components can affect ionization efficiency at any of the steps of ion formation starting from the initial ESI droplet formation to the final gas phase ion reaction, therefore ESI is believed to be more susceptible to matrix effects than APCI. However, ionization in APCI could also be affected to a significant degree if the matrices were dominated by a large amount of other ionizable species that can compete with analyte ions for gas phase protons.34 Generally speaking, for the matrix components that will affect solution phase ion formation, such as the droplet evaporation process, charged droplet formation and uneven fission, ESI will be more sensitive than APCI. For matrix components that affect gas phase ion reactions, both ESI and APCI will be affected to a significant degree. However, there are also exceptions: when there are defects in the interface design, such as insufficient heating and desolvation capacity for the APCI interface, then APCI can be more susceptible to matrix effects. 4.2.1.5

Differences in interface design

It is generally believed that ESI is more subject to matrix effects than APCI. However, it was found that different instrument interface designs could also Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 118/150

Using Mass Spectrometry for Drug Metabolism Studies

118

affect the tolerance of matrix effects with different ionization modes. A comparative study using three different triple quadrupole mass spectrometers was performed to evaluate their sensitivity toward matrix effects; the three tandem MS systems were the following: PE Sciex (Concord, Ontario, Canada) API 3000, Micromass (UK) Quattro UltimaÕ and Thermo-Finnigan (USA) TSQ 7000 API-2.41 Identical sets of samples containing the same amount of several test compounds were prepared using protein precipitation. The matrices for these test samples were either HPLC grade water or rat plasma A or rat plasma B and they were analyzed using these three different tandem mass spectrometers. Identical mobile phases, gradient (one fast and one slow on each system), flow rate, column and HPLC systems were used to reduce the assay variation to only be the various ion sources. Assays were performed using both APCI and ESI on all the samples with all three mass spectrometers. Table 4.1 summarizes the observations with the fast gradient where both the analyte and the internal standard (ISTD) eluted at 1.9 min. Significant ion suppression of both the analyte and ISTD in rat plasma B was observed when using the Micromass Quattro Ultima system with both ionization modes and using the Finnigan TSQ system with ESI mode, while no ion suppression was observed using Sciex API 3000 with either APCI or ESI mode (Table 4.1). Table 4.2 summarizes the same comparison with the slow gradient where the analyte eluted at 4.0 min and the ISTD eluted at 3.9 min. Consistent analytical results were obtained using the Sciex API 3000 interfaced with both ionization modes and using the Finnigan TSQ instrument interfaced with the ESI source. However, weak ion suppression was observed in rat plasma A using the Finnigan TSQ with the APCI mode. It is interesting to note that for the same set of samples under the same slow gradient, the mass responses of the two compounds in plasma A and B showed more variation using the Micromass Quattro Ultima interfaced with the APCI mode, while mass responses obtained by ESI were quite consistent (Table 4.2). These compelling data suggest that the matrix effects in HPLC–MS/MS assays are not only ionization mode (APCI, ESI) dependent, but can also vary between different vendors’ source designs. It was found that under the same ionization mode, different instruments showed different sensitivity to the same matrix (Table 4.1), and that for the Micromass Quattro Ultima, the APCI mode was even more sensitive to the observed matrix effects than the ESI mode.41 4.2.1.6

Nature of matrices: hydrophilic versus hydrophobic

Identifying the nature of matrices will provide useful information for overcoming the matrix effects. Most drug candidates are small molecules with log P ranging from 1 to 5 and are retained on a reversed-phase HPLC column.27 By manipulating pH, the composition of the mobile phases and the gradient46 or selecting a mini-bore column,47 one can easily separate the drug candidates from those polar and nonvolatile matrices that are typically eluted at an earlier retention time on a reversed phase HPLC system. Thus, hydrophilic or polar matrices are not an assay problem for relatively Copyright © 2005 CRC Press, LLC

Technique APCI ESI

Sciex API 3000

Finnigan TSQ

Matrices

CMPD_8

ISTD

CMPD_8/ISTD

CMPD_8

ISTD

CMPD_8/ISTD

CMPD_8

ISTD

CMPD_8/ISTD

Rat plasma (A) Rat plasma (B) Rat plasma (A) Rat plasma (B)

99 53 87 87

94 50 81 72

105 107 107 122

113 125 125 115

112 116 119 106

100 108 105 109

83 104 101 62

91 116 103 74

92 90 98 85

Mobile phases A and B: 10 mM ammonium acetate and 0.005% acetic acid (v/v) in water/methanol (80/20, v/v) and 10 mM ammonium acetate and 0.005% acetic acid (v/v) in water/methanol (10/990, v/v). Flow rate: 0.8 mL/min. Column: Metachem Basic, 5 m, 4.6  50 mm. (Source: Mei et al. Rapid Commun. Mass Spectrom. 17(1), 97, 2003. With permission.) APCI, atmospheric pressure chemical ionization; ESI, electrospray ionization. Values in bold type indicate matrix effects.

119

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 119/150

Micromass Quattro Ultima

Matrix Effects: Causes and Solutions

Table 4.1 Relative mass responses (%) in two different batches of rat plasma obtained using different API sources with the following fast HPLC gradient (from 10%B to 100%B in 1 min, held for 1.9 min, and back to 10%B in 0.1 min) and a shallow gradient (from 40%B to 100%B in 4 min, held for 1.5 min, and back to 40%B in 0.1 min)

Micromass Quattro Ultima Technique

ESI

Finnigan TSQ

Matrices

CMPD_8

ISTD

CMPD_8/ISTD

CMPD_8

ISTD

CMPD_8/ISTD

CMPD_8

ISTD

CMPD_8/ISTD

Rat Plasma (A) Rat Plasma (B) Rat Plasma (A) Rat Plasma (B)

206 82 114 109

163 69 113 109

127 119 101 100

111 106 115 108

110 106 110 98

101 100 105 110

83 96 113 97

81 93 102 91

103 103 111 107

Mobile phases A and B: 10 mM ammonium acetate and 0.005% acetic acid (v/v) in water/methanol (80/20, v/v) and 10 mM ammonium acetate and 0.005% acetic acid (v/v) in water/methanol (10/990, v/v). Flow rate: 0.8 mL/min. Column: Metachem Basic, 5 m, 4.6  50 mm. (Source: Mei et al. Rapid Commun. Mass Spectrom. 17(1), 97, 2003. With permission.) Values in bold type indicate matrix effects.

Copyright © 2005 CRC Press, LLC

Using Mass Spectrometry for Drug Metabolism Studies

APCI

Sciex API 3000

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 120/150

120 Table 4.2 Relative mass responses (%) in two different batches of rat plasma obtained using different API sources with the following slow HPLC gradient: %B to 100%B in 4 min, held for 1.5 min, and back to 40%B in 0.1 min

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 121/150

Matrix Effects: Causes and Solutions

121

hydrophobic new chemical entities (NCEs). Using the post-column infusion technique, it has been found that the majority of the problem matrices in plasma samples are those polar components that elute at earlier retention times on a reversed-phase HPLC system.5,47 Hydrophobic matrices that usually exist in smaller amounts are often revealed as a narrow dip in the later retention time of a reversed-phase chromatogram when using the post-column infusion technique. For example, fatty acids and phosphatidylcholine with long carbon chains (C16–C18) are endogenous hydrophobic matrices, which have a high potential to co-elute with pharmaceutical compounds.38 While these types of matrix issues are relatively challenging, they are still manageable by carefully separating these components from analytes of interest using either various sample preparation techniques or HPLC adjustments. The most difficult matrix effect problems are those caused by hydrophobic components existing in relatively large amounts and with retention times that overlap the analytes.48–50 In this situation, the chromatographic system does not provide sufficient separation; in some cases, these matrices can also overload the column and carry over to next injection, causing huge assay variations from injection to injection.48 One good example of such situation is the matrix effect caused by a polymeric material that existed in one set of samples;41 it was demonstrated that the polymeric material was rather hydrophobic and eluted over a wide range that overlapped with the analytes, resulting in significant ion suppression for compounds that eluted in that part of the chromatogram. 4.2.1.7

Source of matrix effect

As opposed to the visible UV interferences, LC–MS/MS matrix effects are often described as unknown and nonvisible.51 This characterization mystified LC–MS/MS matrix effects and deterred our efforts in searching for their source. If matrix effects can be described as exogenous, known, or constant as opposed to endogenous, unknown, or variable, then they will become manageable obstacles. The separation of large amounts of hydrophobic matrices imposes special challenges to bioanalytical assays in the drug discovery environment where fast turn-around time is required regardless of whether the assay is easy or difficult. Therefore, identifying the source of matrices becomes crucial, especially for those difficult hydrophobic matrices. Intentionally avoiding matrices that exist in relatively large quantities is much easier than blindly finding a way to separate them from the analytes. Some exogenous materials such as plasticizers and anticoagulants can be present in relatively large amounts compared to the analyte of interest and some of the plasticizers are very strong gas phase ions. In addition, some anticoagulants, such as Li-heparin, are strong ionizing agents, which have a high potential to cause matrix effects. Thus, the following study was designed to identify the possible exogenous sources of matrix effects. Compounds with a significant hydrophobicity range which would elute at various retention times were employed as markers for ion suppression evaluation. Rat plasma obtained Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 122/150

122

Using Mass Spectrometry for Drug Metabolism Studies

Figure 4.4 Representative chromatograms of CMPD1 to CMPD8. Mobile phases A and B: 10 mM ammonium acetate and 0.005% acetic acid (v/v) in water/methanol (80/20, v/v) and 10 mM ammonium acetate and 0.005% acetic acid (v/v) in water/methanol (10/990, v/v). Gradient, from 35%B to 85%B in 6.5 min, to 90%B in 0.5 min, to 100%B in 0.1 min, held for 0.4 min back to 35%B in 0.1 min. Flow rate, 0.8 mL/min. Column, Metachem Basic, 5 m, 4.6  50 mm (Source: Mei et al. Rapid Commun. Mass Spectrom. 17(1), 97, 2003. With permission.)

from one source but stored in different plastic tubes was used for study samples. Aqueous solutions served as control samples to be assayed at the same time as study samples in order to identify the source of the matrix ion suppression as either the plasma or tube used to store the plasma. A typical chromatogram for these eight markers is presented in Figure 4.4 with retention times ranging from 1 to 7 min, representing majority of drug discovery compounds in terms of log P. The matrix effects observed with plasma or water in these test tubes are summarized in Table 4.3. Overall, there were 22 observations of matrix effects across most regions of the chromatographic gradient. Sixteen of these involved polar components that were restricted to the early-eluting Compound 1 and 2, and 12 of these examples involved exogenous components, which affected both early-eluting compounds and late-eluting compounds. The full mass scan data suggested that the matrix responsible for Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 123/150

Matrix Effects: Causes and Solutions

123

Table 4.3 Relative mass responses (%) for eight compounds in different test tubes containing either water or plasma. (Source: Mei et al. Rapid Commun. Mass Spectrom. 17(1), 97, 2003. With permission.) Test tube

CPMD1

CPMD2 CPMD3 CPMD4 CPMD5 CPMD6 CPMD7 CPMD8

Fisher Water Plasma

100 12

100 160

100 111

100 101

100 91

100 103

100 98

100 95

Li-heparin/Sarstedt Water 109 Plasma 9

97 39

103 44

103 67

108 101

81 84

92 86

104 100

K3-EDTA/Sarstedt Water 16 Plasma 11

155 127

110 100

107 97

86 93

82 101

83 90

95 100

159 160

117 107

92 99

96 96

91 94

88 94

97 97

111 164

109 110

98 97

101 96

98 99

90 105

98 98

Li-heparin/Microtainer Water 113 Plasma 13

149 146

110 98

95 85

84 82

60 65

47 46

59 57

Nunc Water Plasma

108 162

102 105

96 95

97 90

97 102

91 92

92 91

131 145

121 106

111 94

104 95

74 74

87 79

107 97

Na-heparin/Vacutaincer Water 130 Plasma 17 Corning Water 130 Plasma 14

104 11

USA/Scientific Plastics Water 100 Plasma 18

Caused by endogenous materials. Caused by exogenous materials. Caused by both.

the ionization suppression for late-eluting compounds in the Li-heparin/ Microtainer tube was some type of plasticizer (or release agent) used in this brand of tube (Figure 4.5). Typically, if the source is unknown, such severe matrix effects can result in a significant sample preparation effort to separate these matrices from the analytes of interest. With the cause identified, these matrix effects now can be simply avoided by using the proper brand of tubes for processing and storing both plasma samples and spiked plasma standards.41 Another study was designed to study the impact of different anticoagulants on LC–MS matrix effects using the same type of strategy. The markers were added to water and rat plasma containing different types and increasing amount of anticoagulants. No significant matrix effect was observed for all the test compounds with up to 29% of Na-heparin and Na2-EDTA in serum. However, an enhanced mass signal of CMPD 1 with increasing concentrations of Li-heparin in serum was observed, as shown in Figure 4.6. As shown in Table 4.4, the normalized mass responses of eight test compounds in serum are Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 124/150

124

Using Mass Spectrometry for Drug Metabolism Studies

Figure 4.5 Comparison of LC/MS chromatograms and mass spectra of pure water or plasma in Li-heparin/Microtainer tubes and blank plasma obtained from a contract research organization (CRO) (Source: Mei et al. Rapid Commun. Mass Spectrom. 17(1), 97, 2003. With permission.)

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 125/150

Matrix Effects: Causes and Solutions

125

Figure 4.6 Effect of Li-heparin on the mass signal intensity of CMPD1. (Source: Mei et al. Rapid Commun. Mass Spectrom. 17(1), 97, 2003. With permission.)

Table 4.4 Relative mass responses (%) of eight compounds in serum with increasing percentage of Li-heparin. (Source: Mei et al. Rapid Commun. Mass Spectrom. 17(1), 97, 2003. With permission.) Li-heparin% (v/v) 0 2 5 9 17 29 Control with 29% Na-heparin

CPMD1 CPMD2 CPMD3 CPMD4 CPMD5 CPMD6 CPMD7 CPMD8 100 139 139 142 163 197 98

100 100 120 113 100 134 106

100 92 100 95 97 105 94

100 96 96 97 96 97 89

100 95 100 100 104 105 100

100 91 104 89 106 106 104

100 96 116 124 121 109 98

100 99 103 104 100 97 92

Shaded area indicates ionization enhancement caused by Li-heparin.

listed with increasing concentrations of Li-heparin, the anticoagulant, Liheparin, could also affect the response of CMPD 2 at the higher concentration of Li-heparin. Liþ and some transition metal ions have been used as cationizing agents for characterizing many chemicals, such as polymers and lipids with mass spectrometric detection.52–55 It was demonstrated that the ionization efficiency of glycerophosphocholine lipids,52 phosphatidylethanolamine,54 triacylglycerols,53 and polyglycols55 were enhanced in the presence of Liþ ions by the formation of lithiated adducts, which can be further fragmented through low-energy collision-induced dissociation.55 On the other hand, the potential effect of ion enhancement from Li-heparin treated plasma has not been reported by bioanalytical mass spectrometrists. Our own data show that Li-heparin can produce ion enhancement for certain hydrophilic compounds. It is also possible to observe matrix effects for hydrophobic compounds when Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 126/150

Using Mass Spectrometry for Drug Metabolism Studies

126

Liþ is present in relatively larger amounts that can overload a column. Therefore, Li-heparin should be avoided as the anticoagulant for plasma samples when the samples are to be assayed by HPLC–MS/MS. Other exogenous materials that have potential matrix effects are dosing excipients. Multiple studies have demonstrated that excipients such as PEG400, propylene glycol, Tween 80 and even hydroxypropyl beta cyclodextrin (HPBCD) used for either intravenous or oral formulation, can cause significant matrix effects in both ESI and APCI modes.34,35 Another unique aspect of this type of matrix effect is that it is variable with time, since these dosing excipients will also undergo an absorption, distribution, and elimination process in animals which will be reflected in the plasma samples collected at different time points.34,35,56 Even though techniques such as appropriate sample purification or employing negative ionization mode can diminish the problem, avoiding such excipients is a safer alternative.34 If one cannot avoid these dosing excipients, then it is important to evaluate their effect, if any, on the LC–MS/MS system that is used for assaying samples that include these excipients. 4.2.2

Evaluation of matrix effect

As discussed above, LC–MS/MS matrices can be challenging, in part, due to their character of being unknown or unseen, as opposed to LC/UV assays where interferences can be seen. As a result, the separation of analytes from those unknown matrices in LC–MS/MS assays becomes more difficult. Thus, evaluation of matrix effects should be the first step in solving the problem. Several approaches have been developed to evaluate the matrix effects using different experimental techniques and each has its own advantages and disadvantages. 4.2.2.1

Post-column infusion

In order to directly observe the location of ionization suppression in an LC– MS/MS assay, Bonfiglio and colleagues51 developed a post-column infusion scheme that has been widely adopted by many laboratories. In this scheme, as presented in Figure 4.7, blank sample extracts are injected on the HPLC column under conditions chosen for the assay while a constant amount of analyte is infused into the HPLC stream before it enters the mass spectrometer. Ion suppression caused by matrices is shown as the variation of MS response of the infused analyte, as compared to the response from the injection of blank mobile phase. This approach was successfully employed to detect potential matrix inconsistencies between assay samples and standard samples in drug discovery studies,5 to demonstrate that a minibore column coupled with a fast gradient is very efficient for separating endogenous polar matrices from analytes,47 and to study matrix effects caused by dosing excipients.35 It has been recommended that one should run the same test two or three times to ensure that late eluting matrix components will not interfere with subsequent injections.5 Even though this method has the advantage of showing Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 127/150

Matrix Effects: Causes and Solutions

Figure 4.7 technique.

127

Schematic diagram of evaluation of matrix effects using the post-column infusion

the region in the chromatogram of ion suppression, it only provides a semiquantitative picture of matrix effects that is not easy to be tabulated or graphed for comparison when many different matrices with a large number of compounds are studied. Also, this approach is not suitable for more than ten samples, since it is hard to be automated. Furthermore, as pointed out by Weng’s group, this method is not so efficient in that after any change in the extraction or chromatographic elution procedures, the infusion experiment must be repeated. Finally, since the post-column infusion is usually performed at relatively high concentrations, it can contaminate the source, generating a high background signal and reducing sensitivity; when this happens, instrument cleaning must be conducted to solve the problem.57 A more efficient and practical approach was also proposed by Weng’s group. Following the identification of the matrix region using the post-column infusion method, one should conduct a full mass scan LC–MS experiment to identify the matrix ions in the region of matrix effects. These matrix ions, instead of a post-column infusion of a high concentration of analytes, can be used as matrix markers for developing better sample extraction or chromatographic separation.57 4.2.2.2

Direct comparison

When there are multiple compounds or multiple matrices that need to be evaluated, the most efficient and straightforward method to detect matrix effects and obtain the extent of matrix effects is to run a set of samples containing the same amount of analytes and internal standards in (1) matrix-free solvent, (2) blank matrix used to prepare calibration standards, and (3) blank matrices obtained from different sources or pre-dose blank sample plasma (plasma obtained from animals before dosing with an analyte). Figure 4.8(A) schematically presents this strategic procedure. Matrix effects can be determined if the difference of the MS responses in different matrices are greater than 25%. If the MS response in pre-dose blank sample plasma is within 25% of the MS response in standard plasma, then this method can be Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 128/150

128

Using Mass Spectrometry for Drug Metabolism Studies

Figure 4.8 (A) Schematic diagram of evaluation of matrix effects using direct comparison—prespiking approach. (B) Schematic diagram of evaluation of matrix effects using direct comparison— post-spiking approach.

used for quantitation in drug discovery studies. For example, this method was efficiently utilized to compare the matrix effects among three different tandem mass spectrometers and to investigate the endogenous and exogenous sources of matrix effects (vide supra).41 Another use for this method is to simultaneously compare the effectiveness of different internal standards in correcting matrix effects and to compare the efficiency of different sample cleaning procedures in removing matrices from plasma obtained from multiple lots and different species, thus speeding up method development.58 Large amounts of data can be easily graphed to facilitate the decision making process. This method can also be modified with Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 129/150

Matrix Effects: Causes and Solutions

129

the post-spiking method to separate the recovery factor from total matrix effects as illustrated in Figure 4.8(B).The detailed pre-spiking and post-spiking procedures are discussed in the following section. 4.2.2.3

Pre-spiking and post-spiking comparison

In order to separate the recovery loss from matrix suppression, one can use this pre-spiking and post-spiking approach, where pre-spiking refers to adding standards and internal standards before sample preparation and post-spiking refers to adding standards and internal standards after sample preparation.59,60 As demonstrated in Figure 4.9, response I was produced by the neat analyte solution, free of matrix effects and binding loss. Response II was obtained from pre-spiking procedure and reflected the loss from both analyte recovery and matrix effects. Response III, which was obtained from the post-spiking procedure only reflected the loss from matrix effects. Therefore, a matrix effect can be calculated as response III/response I, recovery equals response II/response III, and process efficiency equals response II/response I.60 This technique is especially helpful when complicated sample preparation procedures, such as solid phase extraction and liquid–liquid extraction, are used, since these procedures, unlike protein precipitation, are more subject to analyte loss.

Figure 4.9 Schematic diagram of evaluation of matrix effect using both pre-spiking and postspiking approaches. Recovery ¼ (response II/response III)  100%. Matrix effect ¼ (response III/ response I)  100%.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 130/150

Using Mass Spectrometry for Drug Metabolism Studies

130

4.2.2.4

Standard addition to incurred samples

For clinical samples, the evaluation of matrix effects should be performed using the appropriate biological matrix obtained from different sources. However, the most meaningful evaluation of matrix effects for discovery studies is to use samples obtained from the tested animals. Therefore, the pre-dose plasma sample is the most appropriate sample for matrix effect evaluation for pharmacokinetic studies. However, there are times when even this approach will not ensure that matrix effects will not be an issue; for example, pre-dose samples cannot provide any information if the dosing excipients are the cause of the matrix effects. Also, for drug disposition studies where the analyte level in individual tissues needs to be determined, it is impractical to obtain pre-dose samples from the same animal. In these situations, one can consider using the so-called standard addition method to evaluate matrix effects. In this method, the unknown tissue homogenate (X) and X with an added known amount of analyte (X þ A) are analyzed along with calibration standards; it is important that all the preparation and processing procedures are all the same for X, X þ A, and calibration standards. Using the calibration standards, one can obtain the observed concentration of X and X þ A. The expected X þ A can be obtained by adding the observed X and added A. The matrix effects can then be evaluated by comparing the observed X þ A with the expected X þ A. The added known amount of analyte should be at least 20 times the limit of quantitation (LOQ) and about equal to the amount of the unknown, as shown in Table 4.5, so that one can differentiate the matrix effects from the other variations. The matrix effect then can be evaluated as the difference of measured X þ A and expected X þ A, and if the difference is greater than 25% it can be considered to be due to matrix effects. Usually the volume of tissue homogenate is sufficient, so that different values of X þ A can be prepared, with A covering a range of three orders of magnitudes, such as X þ 25, X þ 250, and X þ 2500. Values of A that give a better evaluation can then be selected. Where sample volume is sparse, two assays can be taken for the evaluation. The unknown with calibration standards can be assayed first to obtain the observed unknown. The unknown sample with

Table 4.5 Evaluation of matrix effect using the method of standard addition Sample ID A B C D E F

Observed X (ng/g)

Added A (ng/g)

Expected X þA (ng/g)

Observed X þ A (ng/g)

Diff%*

Matrix effect

2500 1000 500 100 50 5

2500 1000 500 100 100 100

5000 2000 1000 200 150 105

3000 2000 1500 220 100 120

40 0 50 10 33 14

Suppression No Enhancement No Suppression No

*Diff% ¼ [(Observed  Expected)/Expected]  100.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 131/150

Matrix Effects: Causes and Solutions

131

added analyte can be assayed during a second run. Using this procedure, it is possible to not only evaluate the extent of the matrix effects, but also obtain the correct analytical results at the same time (see Section 4.3.10).

4.3 4.3.1

Current strategies for overcoming matrix effects Introducing the minimum amount of sample

The extent of the matrix effect is dependent on the amount of matrices in the injected sample. Specifically, the observed ion suppression is proportional to the amount of matrices in the sample that enters the ion source at the same time as the analyte. As shown in Figure 4.10, when the volume of the injected sample that is free of matrix interference is increased, an almost linear response was observed; however, with the increase in volume of a protein-precipitated plasma sample, the response did not increase, instead the response showed a saturation tendency. In other words, increasing the injection volume of processed biological samples does not necessarily guarantee an increase of analyte response. The increasing amount of interfering matrices might compete with the analytes for ionization, and limit the maximum response for the analyte. In one report, it was noted that at the sample injection volume of 5 mL, ion enhancement was observed while at an injection volume of 20 mL, ion suppression was observed.38. The same phenomenon has been observed in our laboratory for some compounds; one example of this is shown in Figure 4.10. One possible mechanism proposed by Enke’s group might explain this phenomenon; at a low injection volume, the electrolyte content of the matrices increased the ion conductivity and thus increased the amount of excess charge, resulting in ion enhancement. However, with the increased sample volume, a further increase of electrolyte would cause a loss in the ion transfer efficiency

Figure 4.10 of caffeine.

Effect of injection volume of protein precipitated plasma on the mass responses

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 132/150

Using Mass Spectrometry for Drug Metabolism Studies

132

( p) or desolvation efficiency ( f ) and the effect could be greater than the enhancement caused by the increased excess charge, resulting in a reduced or saturated analyte response.15 Therefore, we recommend introducing minimum amount of sample in order to avoid ion suppression problems. With the recent improvement in the sensitivity in the new generation of tandem mass spectrometers made by different vendors, introducing more diluted or lower volume of sample is an achievable approach, and this should be the first step to reduce the chance for having matrix ionization suppression problems. 4.3.2

Minimizing the build-up of nonvolatile material in the ionization source

As many studies have shown, ion suppression can be caused by nonvolatile components. The accumulation of nonvolatile material on the ion source interface plate will increase the electrical resistance and therefore will reduce the ion flow (I) at the applied voltage of same value and decrease the ESI signal intensity. At the worst, salt deposits on the metal surfaces can even result in a complete loss of ion transmission. Therefore, minimizing the build-up of nonvolatile materials will help to maintain the instrument’s sensitivity. Approaches such as employing a divert valve, which only delivers the portion that contains the analytes into the MS while diverting the unwanted eluate to waste, or using a splitting device, which splits an appropriate amount of eluate into mass spectrometer and sends the rest to waste, or injecting the minimum volume of sample and cleaning the interface plate on a regular basis can all be very effective techniques for maintaining the sensitivity of the instrument. 4.3.3

Avoiding exogenous matrices

Knowing the details about the collection of bioanalytical samples can be crucial for obtaining reliable bioanalytical results, as we have stated, exogenous material such as plasticizers, Li-heparin or dosing excipients can be the cause of significant matrix effects. Therefore, it is strongly recommended that detailed information about sample collection should be obtained in order to avoid potential exogenous matrix effects. The same brand of tubes should be used for processing and storing both spiked plasma standards and unknown plasma samples. The plastic tubes or 96-well plates should be pre-tested to determine their potential for matrix effects before adopting a brand for routine use in the laboratory. Li-heparin should be avoided for the samples to be quantified using an LC–MS-MS assay. If PEG400 has to be used as the dosing excipient, additional steps need be carried out to ensure that it does not cause any interference. Detailed methods for dealing with matrix effects, such as using good chromatographic separation, solid phase extraction, or liquid–liquid extraction have been described and compared in the studies by Tong et al.34 and Shou et al.35 Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 133/150

Matrix Effects: Causes and Solutions

4.3.4

133

Application of internal standards

The rationale for using an internal standard (IS) to correct for matrix effects is based on the assumption that it will experience the same extent of ion suppression or ion enhancement as the analyte. Therefore, under this rationale, even though the MS response of an analyte can be enhanced or suppressed, and the response ratio (response of analyte divided by the response of the IS) will stay the same. In many situations, especially when using an isotope-labeled analyte for the IS, this assumption is true. However, an isotope-labeled IS is usually unavailable for assays in the drug discovery stage. Often internal standards that we use are analogs of the analytes, but they can differ from the analytes in terms of their log P and pKa. Furthermore, recent studies have shown that the IS can sometimes interfere with the signal of analyte or vice versa via cross-talk or ionization competition.61,62 Even co-eluting compounds as the IS sometimes cannot correct for the matrix effect if they have a different pKa to the analyte. As shown in Table 4.6, phenylpropanolamine (PPA) and pseudoephedrine (PSE) were spiked into a rat plasma sample and they eluted at same time on the HPLC system when the extracted sample was injected, but only PSE experienced ion suppression. Therefore, the use of an IS cannot always guarantee the correction of matrix effects. Careful studies need to be carried out to select a good IS with a matched pKa and log P and appropriate concentration level, which sometimes is impractical for drug discovery studies. 4.3.5

Preparing standards or quality control samples using the pre-dose samples

By using blank plasma obtained from the same animal that was dosed by the test compounds or blank plasma from the same batch of animals to prepare calibration standards, the matrix difference between the calibration standards and the samples can almost be eliminated, except for the matrix effects caused by dosing excipients. If there is not enough pre-dose blank plasma for making the calibration curve, quality control (QC) samples from the pre-dose plasma can be prepared. Matrix effects can be corrected with the information provided by QC samples at different levels. For example, if consistent matrix effects were observed for QC samples at different levels, then a constant correction factor could be used to correct the matrix effects.

Table 4.6 Relative mass responses of pseudoephedrine (PSE) and phenylpropanolamine (PPA) at the same retention time of 0.7 min in pure water or protein precipitated plasma Drug

Water

Plasma

Plasma w/PEG400

PPA PSE

100 100

92 83

101 58

Shaded area indicates ionization suppresion.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 134/150

Using Mass Spectrometry for Drug Metabolism Studies

134

4.3.6

Diluting samples with blank standard plasma

When sensitivity is not an issue, the differences in the matrix between standards and samples can be reduced by diluting samples with blank standard plasma (plasma used to prepare calibration standards). Our laboratory has been using this method to analyze samples with high concentrations; this technique is well suited for rising dose pharmacokinetic studies. This approach was also found effective for overcoming the matrix effects that can be caused by PEG400 being used in the dosing formulation.37 4.3.7

Post-column addition of signal-enhancing agents

Ionization suppression caused by the high concentration of electrolytes can be reduced by the addition of so-called signal-enhancing agents. A high concentration of electrolytes can change surface tension and modify the volatility of the sprayed solution; this can lead to the formation of larger final droplets containing higher percentages of water and electrolytes. Furthermore, some electrolytes can form strong ion pairs with analytes, preventing analytes from partitioning to the droplet surface. Therefore, ionization suppression can be reduced by adding some modifying agents that either change the surface tension or volatility of the sprayed solution in favor of formation of analyte gas ions or reducing the ion pairing of analytes. If only lowering surface tension is needed, then post-column addition (PCA) of surface tension lowering agents, such as methanol, 2-propanol or acetonitrile can be very effective.2,43,63 The ratio of mobile phase flow rate to the flow rate of the PCA agents can be easily optimized. With these conventional surface tension lowering agents, the signal can be enhanced 3–16-fold depending on analytes and methods of sample preparation.2,62 However, these agents also have a higher volatility than water and most electrolytes and, therefore, they will evaporate earlier and leave more electrolytes in the final droplets, thus further reducing the ionization suppression caused by ion competitions requires additional properties of these agents, such as an optimized volatility and pKa value.30 The most famous solution for improving the signal of a strong base in a TFA-containing mobile phase is to employ a mixture containing both propionic acid and 2-propanol. Propionic acid is a weak acid with an optimum volatility. Propionic acid has a volatility lower than TFA which leads to the earlier evaporation of TFA from the droplets, thus replacing strong analyte/ TFA pairs with weak analyte/propionic acid pairs that release the analyte ion to the gas phase. If the weak acid is too volatile, such as acetic acid, then TFA will still strongly ion pair with the analyte causing ionization suppression. Unlike other weak acids, such as valeric acid, propionic acid still has sufficient volatility to prevent it from causing rapid desolvation of the droplets.30 For improving the signal of acids in negative ESI, 2-(2-methoxyethoxy)ethanol (2-MEE) is a good choice.64,65 One or two of the following additives: formic acid, ammonium formate, acetic acid, and ammonium acetate, is Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 135/150

Matrix Effects: Causes and Solutions

135

usually added to the mobile phases for improving the retention time and peak shape. The ion suppression in this condition is caused by high surface tension and ion competition between the analyte and co-eluting electrolytes, such as (AcO), in the mobile phase. The ionization suppression usually gets worse with the increase of these additives.66 Conventional surface tension lowering agents, such as methanol or acetonitrile, can only improve the part of the problem that is caused by high surface tension, while 2-MEE not only can improve the signal by lowering the surface tension, but can also improve the signal by reducing the AcO concentration in the final droplet. This is because 2-MEE is a surface tension lowering agent with optimal volatility properties; it has a boiling point of 193 C, higher than that of water (100 C) and acetic acid (118 C). Therefore, water and AcO will be evaporated earlier than 2-MEE in the ESI spray formation. In this way, the final droplet will be smaller and contain more 2-MEE and a lower percentage of water and AcO.64 Even though the post-column addition approach is quite effective in reducing the ionization suppression problem, it is mostly applicable for metabolite identification type studies where usually a small number of samples are to be analyzed. For quantification of a large number of samples, one can try to add these modifiers to the mobile phases as described in the following section. 4.3.8

Modifying the mobile phase

The ideal mobile phases for ESI are those with an optimum surface tension that facilitates the generation of a stable spray.67 For positive mode, the most popular mobile phases are methanol/water or acetonitrile/water or methanol/ acetonitrile/water with a weak acid (such as acetic or formic) added to the solution at the concentration range from 0.005% to 0.05%, or with a weak acid buffer (such as formic acid–ammonium formate or acetic acid–ammonium acetate). The low pH of such mobile phases can facilitate the protonation of analytes with basic functional groups. The neutral salts (ammonium formate or acetic acid–ammonium acetate) are useful for facilitating the ionization of polar or neutral analytes through adduct formation. However, some strong bases will have very short HPLC retention times or exhibit peak tailing and may need further additives for chromatographic improvement reasons. TFA is a commonly used additive in HPLC for reducing the peak tailing of basic compounds on silica-based columns. However, TFA is also notorious for its ionization suppression of the ESI signal for basic compounds. As stated above, post-column addition of propionic acid is an effective way to reduce the ion suppression caused by TFA. Based on the mechanism of reducing ionization suppression by adding propionic acid post-column, one can reasonably assume that adding propoinic acid directly to a mobile phase should also work. Propionic acid is a weaker acid than TFA; when they co-exist in mobile phase, it is a very weak competitor of TFA; for ion pairing Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 136/150

Using Mass Spectrometry for Drug Metabolism Studies

136

with the analyte, therefore it should not affect the chromatographic peak shape of the analyte. However, when the driving force for evaporation of TFA is introduced in the electrospray process, the mass action will make propionic acid a good competitor of TFA for ion pairing with the analyte. It has been shown that by adding propionic acid (0.1 to 0.5%) propionic acid directly to mobile phases containing either 0.025% or 0.05% TFA, ESI sensitivity improved by 2–5 fold for basic compounds such as sildenafil, fluconazole, nicotine, midazolam, and isoniazid.68 For negative ionization mode LC–ESI– MS assays, it is necessary to use a solvent that creates stable anions. The mixture of halogenated solvents with methanol is a very good system for analysis of oligonucleotides in the negative mode, due to the fact that halogenated solvents can form stable anions through electrochemical reduction processes.67 Examples of these mixtures that have been reported are hexafluoroisopropanol with methanol69,70 and 2,2,2-trifluoroethanol with methanol.67 4.3.9

Separation of matrices and analytes by sample preparation

The most common means of obtaining maximum sensitivity and signal reproducibility is through comprehensive sample clean-up and purification, even though sometimes it can be very time consuming. The commonly used procedures are protein precipitation (PPT), liquid–liquid phase extraction (LLE) and solid phase extraction (SPE). For drug discovery studies, where a large number of compounds need to be assayed with a relatively small number of samples per study, it is not practical to develop a unique sample preparation procedure for each compound using SPE or LLE. Thus, PPT has become the main methodology for plasma sample preparation due to its simplicity and universality for almost all small molecules. PPT can be easily automated or semi-automated using a robotic liquid handler and 96-well plates, and it has been implemented in many pharmaceutical companies for drug discovery bioanalytical applications.71–74 Studies were conducted to optimize the PPT procedure based on effectiveness of protein removal and matrix effects in LC–MS.75 It was found that the most efficient protein precipitants for protein removal were zinc sulfate, acetonitrile, and trichloroacetic acid. These precipitants all have excellent protein precipitation reproducibility.75 However, using either acids or zinc sulfate as precipitants may cause potential degradation of analytes or hydrolysis of some conjugates such as glucuronides and sulfates, while organic precipitants usually will not cause degradations and they are usually compatible with mobile phases. Furthermore, acetonitrile precipitation generally has the lowest ionization suppression potential.75 Due to all these reasons, acetonitrile has become the most common precipitant for LC–MS assays for small molecules. Even though the PPT approach only removes the protein and leaves behind other matrices from the sample, HPLC usually can provide a satisfactory separation of the analyte and most of the problematic matrices. It has been shown that through a wise selection of the HPLC column in terms of size and Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 137/150

Matrix Effects: Causes and Solutions

137

separation mode, HPLC can be very efficient and effective in removing the polar matrices.47 For drug development applications where high quality results are required for a small number of compounds with a large number of samples per study, developing a specific sample preparation method is more common; in this case, SPE and LLE are widely utilized techniques. SPE is probably the most popular technique owing to its ease of automation76 and to the availability of a wide variety of commercial sorbent materials.77,78 The advantages of sample preparation by SPE include the removal of nonvolatile salts and the attainment of a relatively clean extract with reduced amounts of potentially interfering matrix components. The selectivity of SPE is usually achieved by choosing or mixing appropriate sorbents and designing an effective washing and elution scheme. All these can be achieved at the expense of time and experience. Several papers have details on how to select sorbents and how to design elution schemes to achieve separation for various analytes with different properties.76–85 Automated SPE can be achieved by either using an on-line column switching format or an off-line 96-well format. Generally speaking, the parallel format (e.g., 96-well format) has a much higher throughput than the serial format and is more suitable for large studies; however, with the serial format, it may be easier to achieve complete automation without human intervention. The fastest parallel processing system can achieve speeds of up to 400 samples per hour.82 There are also various on-line extraction techniques using direct injection of plasma (for more on this topic, see Chapter 5); some examples include restricted access media (RAM),86 turbulent flow chromatography,87–89 molecularly imprinted polymer extraction,90 and on-line solid phase extraction. RAM columns are columns made of a hydrophilic external surface and a hydrophobic internal surface in silica particles with controlled pore sizes. The separation of small molecules from biological matrices is achieved by the combination of size-exclusion and partition chromatograph. A limitation associated with this approach is the relatively long run times (5–15 min) and the potential sample instability in biological fluids. Its effectiveness in removing the protein and other matrices is similar to using PTT coupled with HPLC.91 Turbulent flow chromatography is another direct-injection sample preparation technique. In this method, the separation of small molecules from large molecules and polar matrices is obtained by nonlaminar flow of the mobile phase through use of large particles (50 mm) for the stationary phase. Further separation of analytes from other components can be achieved with column switching to an analytical column. With the demand for higher throughput, generic turbulent flow chromatography was developed for routinely removing protein and polar matrices from biological samples;88,89 if the washing protocol, including both acidic and basic wash,85 is followed even more matrix components can be removed from the sample. By adding on-line dilution of the eluate, optimal usage of switching valves and dual extraction Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 138/150

138

Using Mass Spectrometry for Drug Metabolism Studies

column procedures, the problems of peak fronting or tailing, variable recovery, and high carryover can be dramatically reduced.89 Molecularly imprinted polymer (MIP) extraction is a very selective cleaning procedure for analytes. The custom made MIP will only retain the components with the same steric and chemical properties as the analytes, therefore the matrix components can be completely and efficiently removed. The key step of this approach is the preparation of steric and chemical molecular imprints by polymeriazation of functional and cross-linking monomer in the presence of a templating ligand, or imprint species.90 Even though there are reports of successful applications in bioanalysis,92,93 issues of template bleeding, peak broadening and tailing due to strong nonspecific adsorption to the polymer still need to be solved. Therefore, the wide application of this technique depends on its commercial availability and a better understanding of this technique by application scientists. One of the more popular on-line solid phase extraction apparatus is the ProspecktÕ system. Its popularity is due to its incorporation of single-time use solid phase extraction cartridges that elute directly into the HPLC system via three switching valves, which not only provide cleaner samples but also eliminate carry-over issues.76,94 The separation power of this system can be enhanced by coupling columns with different separation modes, resulting in the so-called two dimensional or multi-dimensional LC.48,50 The 96-well format solid phase extraction system is perhaps the most suitable method for processing a large number of samples.82,95 The recent development of a 96-well format with a small bed volume of the membrane features reduced back pressures, eliminated bed channeling, increased sample capacity, and improved repeatability and reproducibility; this system also provides mixed separation modes and a reduced eluate volume and has made SPE even more attractive for many users.96–98 The routine strategy for SPE is to retain the analyte and wash out the interfering compounds. Recently, a reversed approach was proposed to effectively remove basic matrices by retaining the matrices using strong cation exchange (SCX) while washing out analytes.99 This is most applicable for bioassays of multiple analytes, since in this situation the highly specific extraction is unlikely to be successful for all analytes. In this process, the plasma sample was first basified and deproteinated by using acetonitrile containing ammonium hydroxide followed by the separation using SCX. It was found that recovery for most compounds that have pKa<8 was satisfactory (>74%).99 Liquid–liquid extraction is believed to be a highly selective sample preparation method that provides extracts that show the least amount of ion suppression, thereby allowing for reproducible and accurate LC–MS/MS analysis. LLE gained popularity when semi-automated100–103 and automated LLE104 with 96-well format became commercially available. It has been reported that the extraction efficiency in these small tubes can be improved by using small inert particles with an average diameter of 1 mm to increase the extraction surface.104,105 Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 139/150

Matrix Effects: Causes and Solutions

4.3.10

139

Standard addition method

If finding an effective sample preparation method with appropriate internal standards is too time-consuming, the standard addition method to correct for matrix effects can be tried. This method requires at least two LC–MS/MS assays—the first with the unknown sample (X) and the second with the unknown sample spiked with a known amount of standard (X þ A). If the mass response is linear between unknown sample (RX) and spiked unknown sample (RX þ A), the following relationship can be established as shown in Figure 4.11, from which the concentration of analyte in unknown sample (X) can be calculated. X ðX þ AÞ  X AðRX Þ ¼ )X¼ : RX RXþA  RX RXþA  RX

ð4:13Þ

This method is extremely suitable for analyzing a small number of tissue samples, where sample volume is sufficient for preparation of multiple combinations of X þ A. In this situation, if linear response range could be established with all the XþAs, one might not need to prepare a calibration curve. As described in the section on matrix evaluation using standard addition, if one can prepare multiple combinations of X þ A, then only one run will be sufficient. The most appropriate A can be chosen; in other words, the X þ A that still has an MS response in the linear range, but has a sufficient difference from the response of X to allow for the calculation to be accurate. This method was successfully used to quantify toxins in scallops where the degree of signal suppression varied from scallop to scallop.106 Our laboratory has used this method to analyze brain tissue samples, where hydrophobic matrix effects are usually more severe than in plasma samples and can vary from animal to animal. With only limited sample preparation, the

Figure 4.11

Relationship between X and X þ A for the method of standard addition.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 140/150

Using Mass Spectrometry for Drug Metabolism Studies

140

Table 4.7 An example of using the standard addition method to correct matrix effects

Sample description Standards

(ng/g) 50 50 500 500 5000 5000

Unknown

X1 X2 Spiked unknown X1þ500 X2þ500 Unknown X1 after correction X2 after correction

Area of analyte

Area of IS

Response

3983 3908 44521 43801 470520 451638 4153 4857 99264 97180

906679 926293 938098 961710 822707 943048 857104 942016 967655 937134

0.0044 0.0042 0.0475 0.0455 0.5719 0.4789 0.0048 0.0052 0.1026 0.1037

Concentration based on calibration (ng/g) 51 49 503 484 5481 4623 56 60 1054 1065 25 26

Diff % 3 1 1 3 10 8 * * ** **

*Calculated using the calibration curve, where matrix effects are embedded. **Calculated using the method of standard addition (Equation 4.13), where matrix effects are corrected. Standards were used to confirm the linear response range.

matrix effects caused by different matrices in different animal brains can be easily corrected. As shown in Table 4.7, without the standard addition method, 56 and 60 ng/g as the brain levels for each rat would be reported; however, with the standard addition method, it is clearly shown that there was about a 50% signal enhancement for the samples compared to the standards; therefore, the correct concentration levels should be 25 and 26 ng/g, respectively, as calculated using Equation 4.13. 4.3.11

Using a nano-splitting device

It is well known that reducing the ESI flow rate to nanoliters per minute leads to increased desolvation, ionization and ion-transfer efficiency.107 Experiments have clearly demonstrated that the ESI signal can be dramatically enhanced with nanoflow ESI conditions for those low surface activity compounds, such as oligosaccharides and glycosides.108,109 It has been reported that nanoelectrospray is more tolerant of samples that contain nonvolatile salts because of its ability to generate smaller, more highly charged droplets.110 The advantage of nano-ESI in overcoming the matrix effects can be rationalized based on the fundamentals of the ESI process. The slower flow rate will reduce the size of the initial ESI droplets that in turn require fewer uneven fission processes and less solvent evaporation prior to ion release into the gas phase. The uneven fission process is known to be a cause of many ESI matrix effects. The uneven fission will enhance the surface-active components, such as surface-active matrices, to compete with less surface-active components, such as polar analytes, for the limited surface charge. Fewer uneven fission processes will minimize the competition between surface-active matrices and polar analytes, and thereby lead to a higher signal for polar analytes. In order to prove the effect of flow rate on the ESI responses of low surface-active compounds, Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 141/150

Matrix Effects: Causes and Solutions

141

Schmidt and colleagues designed an elegant experiment with a mixture of compounds that have differences in surface activity, a low surface activity compound (turanose) and a high surface activity compound (n-octylglycogyranoside).111 Because both turanose and n-octyl-glycogyranoside are uncharged in solution, the difference of ion signal intensity at different flow rate should only reflect the contribution of the difference in surface activity. The suppression of turanose by n-octyl-glycogyranoside can be completely eliminated at a flow rate of a few nL/min while the suppression increases to 5-fold at flow rates greater than 50 nL/min.111 While using a few nL/min might not be practical for routine LC–MS quantification, reducing the flow rate to 100–200 nL/min using a nanosplitting device is still a feasible approach. The same laboratory has tried to apply this system for both metabolite identification6 and bioanalytical quantitation.112 The advantage of this nanosplitting device as compared to using a capillary LC column is that samples still can be run with faster LC flow rates on conventional HPLC columns. Therefore, there is no need to be concerned about overloading the column with matrix or rapid deterioration of the column, as would be the case when using a capillary column. Furthermore, the chromatographic quality is not affected by this splitting device.112 With this splitting device, ionization suppression was dramatically reduced, so that more metabolites that had been suppressed in the faster flow rate (200 mL/min) were able to be detected.6 When it was applied to bioanalytical quantitation, one could still produce a calibration curve with a linear dynamic range similar to the standard interface, with an improved LOQ and chromatographic performance (for more on this topic, see Chapter 12).112 4.3.12

Switching instruments and ionization modes

As shown in a recent study, ionization of the analyte is a very complex phenomenon; it can be affected by many factors, including by co-eluting components and instrument settings.29 In an earlier section, we have also shown that matrix effects can be different with different ionization modes or a different brand of instruments. Matrix effects observed in one brand of instrument might not be seen in another brand. Therefore, if the source and cause of a matrix effect is unknown and another brand of instrument is available, it may be easier to switch to the second vendor’s system. In this case, attempts should be made to evaluate the matrix effects in the other instrument using both the ESI and the APCI modes, and then use the second instrument to analyze the samples if a satisfactory evaluation is obtained.

4.4

Conclusions

Matrix effects are one of the most important causes for failures and errors in bioanalytical LC–MS/MS assays. With increasing applications of LC–MS/MS Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 142/150

Using Mass Spectrometry for Drug Metabolism Studies

142

for pharmaceutical research, the issue of matrix effects has received more and more attention. We have discussed possible causes of matrix effects based on the mechanisms of electrospray ionization, summarized different approaches for evaluation of matrix effects and proposed the strategies for overcoming matrix effects in this chapter. Matrix effects can be caused by polar nonvolatile components as well as hydrophobic volatile components via different mechanisms. Polar nonvolatile components could cause ion enhancement at low concentrations when excess charge is increased by the increase of conductivity of spayed solution at optimum electrolyte levels. Polar nonvolatile components can also cause ion suppression at high concentrations when they change the physical property of sprayed solution that reduces the desolvation efficiency ( f ) or the ion transfer efficiency ( p). Nonpolar hydrophobic components can cause matrix effects by competition for the limited surface excess charge in the ESI process. Both polar and nonpolar matrix components can cause ion suppression by strong ionpairing with the analytes or by competing for gas phase protons. Ion enhancing agents that exist in biological samples, such as Liþ, can also induce matrix effects. Endogenous components as well as exogenous components, such as plasticizers, Li-heparin, and dosing excipients, can cause significant matrix effects. Matrix effect evaluation is the first step for solving the issues of matrix effects. Post-column infusion, direct comparison of mass response in different matrices using pre-spiking or post-spiking approaches are the most common procedures. The purpose of the evaluation is to locate the range, to know the relative hydrophobicity, to identify the source of matrix effects, to select appropriate internal standards, and to compare the effectiveness of separation procedures. Different strategies need to be used for solving matrix effects with different causes and sources. For the matrix effects caused by polar nonvolatile components, efficient separation from relatively hydrophobic analytes can be achieved using mini-bore reversed phase columns or turbulent flow chromatography. For polar nonvolatile analytes that are hard to separate from polar matrices, either the nano-spray technique with a concentric nano-splitting device or post-column addition of a signal-enhancing agent could be useful. For a small amount of endogenous hydrophobic matrices, modifications can be made to the chromatographic separation conditions, or other sample preparation procedures, such as off-line or on-line solid phase extraction or liquid–liquid extraction should be tried. For matrix effects caused by the ion pairing of TFA, a sufficient amount of propionic acid/2-propanol should be added to the mobile phase or these can be added to the post-column eluate. For extensive matrix effects caused by a relatively large amount of hydrophobic matrices in tissue samples, the method of standard addition should be tried. The following procedures should be adopted whenever possible: 1. Employ an appropriate internal standard. 2. Introduce the minimum amount of sample into the assay system.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 143/150

Matrix Effects: Causes and Solutions

3. 4. 5. 6.

143

Minimize the build-up of contaminants on the MS interface. Use pre-dose samples to prepare the calibration standards or QCs. Avoid exogenous matrices. When all else fails, try a different ionization mode or a different brand of instrument.

With a better understanding of the mechanisms of matrix effects, application scientists should be able to work with manufacturers to design better MS interfaces that not only increase the analyte sensitivity but also minimize or eliminate the problem of matrix effects. References 1. Gilbert, J.D., Olah, T.V., Barrish, A., and Greber, T.F., Determination of L-654,066, a new 5 alpha-reductase inhibitor in plasma by liquid chromatography/ atmospheric pressure chemical ionization mass spectrometry, Bio. Mass Spectrom., 21, 341, 1992. 2. Ikonomou, M.G., Naghipur, A., Lown, J.W., and Kebarle, P., Characterization of the reaction products of deoxyguanosine with the anticancer agent BFNU and BFNU-1,1,10 ,10 -d4 in different buffers by high-performance liquid chromatography/ atmospheric pressure ionization tandem mass spectrometry, Biomed. Environ. Mass Spectrom., 19(7), 434, 1990. 3. Kebarle, P. and Tang, L., From ions in solution to ions in the gas phase, Anal. Chem., 65, 972A, 1993. 4. Mirza, U.A. and Chait, B.T., Effects of anions on the positive ion electrospray ionization mass spectra of peptides and proteins, Anal. Chem., 66(18), 2898, 1994. 5. Miller-Stein, C., Bonfiglio, R., Olah, T., and King, R., Rapid method development of quantitative LC-MS/MS assays for drug discovery, Am. Pharm. Rev., 3, 54, 2000. 6. Gangl, E.T., Annan, M.M., Spooner, N., and Vouros, P., Reduction of signal suppression effects in ESI–MS using a nanosplitting device, Anal. Chem., 73(23), 5635, 2001. 7. Shah, V.P. et al. Bioanalytical method validation—a revisit with a decade of progress, Pharm. Res., 17(12), 1551, 2000. 8. Fenn, J.B., Ion formation from charged droplets: role of geometry, energy and time, J. Am. Soc. Mass Spectrom., 4, 524, 1993. 9. Enke, C.G., A predictive model for matrix and analyte effects in electrospray ionization of singly-charged ionic analytes, Anal. Chem., 69(23), 4885, 1997. 10. Kebarle, P., A brief overview of the present status of the mechanisms involved in electrospray mass spectrometry, J. Mass Spectrom., 35(7), 804, 2000. 11. Kebarle, P. and Peschke, M., On the mechanisms by which the charged droplets produced by electrospray lead to gas phase ions, Anal. Chem. Acta, 406, 11, 2000. 12. Cech, N.B. and Enke, C.G., Effect of affinity for droplet surfaces on the fraction of analyte molecules charged during electrospray droplet fission, Anal. Chem., 73(19), 4632, 2001. 13. Dole, M. et al. Molecular beams of macroions, J. Chem. Phys., 49, 2240, 1968. 14. Iribarne, J.V., Dziedzic, P., and Thomson, B.A., Atmospheric pressure ion evaporation–mass spectrometry, Int. J. Mass Spectrom. Ion Phys., 50, 331, 1983.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 144/150

144

Using Mass Spectrometry for Drug Metabolism Studies

15. Constantopoulos, T.L., Jackson, G.S., and Enke, C.G., Effects of salt concentration on analyte response using electrospray ionization mass spectrometry, J. Am. Soc. Mass Spectrom., 10(7), 625, 1999. 16. Amad, M.H., Cech, N.B., Jackson, G.S., and Enke, C.G., Importance of gas-phase proton affinities in determining the electrospray ionization response for analytes and solvents, J. Mass Spectrom., 35(7), 784, 2000. 17. Tang, K. and Smith, R.D., Physical/chemical separations in the break-up of highly charged droplets from electrosprays, J. Am. Soc. Mass Spectrom., 12(3), 343, 2001. 18. Zhou, S. and Cook, K.D., A mechanistic study of electrospray mass spectrometry: charge gradients within electrospray droplets and their influence on ion response, J. Am. Soc. Mass Spectrom., 12(2), 206, 2001. 19. King, R. et al. Mechanistic investigation of ionization suppression in electrospray ionization, J. Am. Soc. Mass Spectrom., 11(11), 942, 2000. 20. Asperger, A., Efer, J., Koal, T., and Engewald, W., On the signal response of various pesticides in electrospray and atmospheric pressure chemical ionization depending on the flow-rate of eluent applied in liquid chromatography–tandem mass spectrometry, J. Chromatogr. A, 937(1–2), 65, 2001. 21. Tang, L. and Kebarle, P., Dependence of ion intensity in electrospray mass spectrometry on the concentration of analytes in the electrosprayed solution, Anal. Chem., 65, 3654, 1993. 22. Stephenson, J.L., Jr. and McLuckey, S.A., Ion/ion proton transfer reactions for protein mixture analysis, Anal. Chem., 68(22), 4026, 1996. 23. Stephenson, J.L., Jr. and McLuckey, S.A., Counting basic sites in oligopeptides via gas-phase ion chemistry, Anal. Chem., 69(3), 281, 1997. 24. Tang, L. and Kebarle, P., Effect of the conductivity of the electrosprayed solution on the electrospray current. Factors determining analyte sensitivity in electrospray mass spectrometry, Anal. Chem., 63, 2709, 1991. 25. Cech, N.B. and Enke, C.G., Relating electrospray ionization response to nonpolar character of small peptides, Anal. Chem., 72(13), 2717, 2000. 26. Leize, E., Jaffrezic, A., and Dorsselaer, A.V., Correlation between solvation energies and electrospray mass spectrometric response factors. Study by electrospray mass spectrometry of supramolecular complexes in thermodynamic equilibrium in solution, J. Mass Spectrom., 31, 537, 1996. 27. Lipinski, C., Drug-like properties and the causes of poor solubility and poor permeability, J. Pharmacol. Toxicol. Methods, 44, 235, 2000. 28. Cech, N.B., Krone, J.R., and Enke, C.G., Predicting electrospray response from chromatographic retention time, Anal. Chem., 73(2), 208, 2001. 29. Sjoberg, P.J., Bokman, C.F., Bylund, D., and Markides, K.E., Factors influencing the determination of analyte ion surface partitioning coefficients in electrosprayed droplets, J. Am. Soc. Mass Spectrom., 12, 1002, 2001. 30. Apffel, A., Fisher, S., Goldberg, G., Goodley, P., and Kuhlmann, F., Signal enhancement for gradient reverse-phase high performance liquid-chromatography electrospray-ionization mass spectrometry analysis with trifluoroacetic and other strong acid modifiers by post column addition of propionic-acid and isopropanol, J. Am. Soc. Mass Spectrom., 6, 1221, 1995. 31. Wang, G. and Cole, R.B., Disparity between solution-phase equilibria and charge distribution in positive-ion electrospray mass spectrometry, Org. Mass Spectrom., 29, 419, 1994. 32. Zhou, S. and Cook, K.D., Protonation in electrospray mass spectrometry: wrongway-round or right-way-round?, J. Am. Soc. Mass Spectrom., 11(11), 961, 2000.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 145/150

Matrix Effects: Causes and Solutions

145

33. Wang, G. and Cole, R.B., Solution, Gas-phase, and Instrumental Parameter Influences on Charge-state Distribution in Electrospray Ionization Mass Spectrometry, Wiley, New York, 1997. 34. Tong, X.S. et al. Effect of signal interference from dosing excipients on pharmacokinetic screening of drug candidates by liquid chromatography/mass spectrometry, Anal. Chem., 74(24), 6305, 2002. 35. Shou, W.Z. and Naidong, W., Post-column infusion study of the ’dosing vehicle effect’ in the liquid chromatography/tandem mass spectrometric analysis of discovery pharmacokinetic samples, Rapid Commun. Mass Spectrom., 17(6), 589, 2003. 36. Larger, P.J., et al. Investigation of ion-suppression from a formulation agent in quantitative LC–MS/MS bioanalysis: a case study on Tween 80, in Proceedings of the 51st ASMS Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, 2003. 37. Schumacher, J., Zimmer, D., Tesche, F., and Pickard, V., Matrix effects during analysis of plasma samples by electrospray and atmospheric pressure chemical ionization mass spectrometry: practical approaches to their elimination, Rapid Commun. Mass Spectrom., 17, 1950, 2003. 38. Ahnoff, M., Wurzer, A., Lindmark, B., and Jussila, R., Characterisation of serum albumin and LysoPCs as major contributors to plasma sample matrix effects on electrospray ionisation efficiency, in Proceedings of the 51st ASMS Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, 2003. 39. Sullivan, M., Shen, J., and Bugge, C.J.L., Improved sensitivity and ruggedness in APCI mode for a Micromass Quattro Ultima LC-MS-MS System, in Proceedings of the 49th ASMS Conference on Mass Spectrometry and Allied Topics, Chicago, IL, 2001. 40. Shang, J.X., Zhong, W.-Z., and Heath, T.G., Examination of matrix-induced ionization suppression in atmospheric pressure chemical ionization, Proceedings of the 49th ASMS Conference on Mass Spectrometry and Allied Topics, Chicago, 2001. 41. Mei, H. et al. Investigation of matrix effects in bioanalytical high-performance liquid chromatography/tandem mass spectrometric assays: application to drug discovery, Rapid Commun. Mass Spectrom., 17(1), 97, 2003. 42. Ding, X., Duggan, J.X., and Fast, D.M., A LC–MS/MS method for quantitation of a small molecule drug candidate in rat plasma, urine and synovial fluid and matrix effect evaluation in these three matrices using API 4000 and API 3000, in Proceedings of the 51st ASMS Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, 2003. 43. Eshraghi, J. and Chowdhury, S.K., Factors affecting electrospray ionization of effluents containing trifluoroacetic acid for high-performance liquid chromatography/mass spectrometry, Anal. Chem., 65(23), 3528, 1993. 44. Bruins, A.P., Covey, T.R., and Henion, J.D., Ion spray interface for combined liquid chromatography/atmospheric pressure ionization mass spectrometry, Anal. Chem., 59, 2642, 1987. 45. Apffel, A. et al. Enhanced sensitivity for peptide mapping with electrospray liquid chromatography–mass spectrometry in the presence of signal suppression due to trifluoroacetic acid-containing mobile phases, J. Chromatogr., A, 712(1), 177, 1995. 46. Romanyshyn, L. et al. Ultra-fast gradient vs. fast isocratic chromatography in bioanalytical quantification by liquid chromatography/tandem mass spectrometry, Rapid Commun. Mass Spectrom., 15(5), 313, 2001.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 146/150

146

Using Mass Spectrometry for Drug Metabolism Studies

47. Hsieh, Y. et al. Quantitative screening and matrix effect studies of drug discovery compounds in monkey plasma using fast-gradient liquid chromatography/tandem mass spectrometry, Rapid Commun. Mass Spectrom., 15(24), 2481, 2001. 48. Choi, B.K., Hercules, D.M., and Gusev, A.I., Effect of liquid chromatography separation of complex matrices on liquid chromatography–tandem mass spectrometry signal suppression, J. Chromatogr., A, 907(1–2), 337, 2001. 49. Choi, B.K., Hercules, D.M., and Gusev, A.I., LC–MS/MS signal suppression effects in the analysis of pesticides in complex environmental matrices, Fresenius J. Anal. Chem., 369(3–4), 370, 2001. 50. Pascoe, R., Foley, J.P., and Gusev, A.I., Reduction in matrix-related signal suppression effects in electrospray ionization mass spectrometry using on-line twodimensional liquid chromatography, Anal. Chem., 73(24), 6014, 2001. 51. Bonfiglio, R., King, R.C., Olah, T.V., and Merkle, K., The effects of sample preparation methods on the variability of the electrospray ionization response for model drug compounds, Rapid Commun. Mass Spectrom., 13(12), 1175, 1999. 52. Hsu, F., Bohrer, A., and Turk, J., Formation of lithiated adducts of glycerophosphocholine lipids facilitates their identification by electrospray ionization tandem mass spectrometry, J. Am. Soc. Mass Spectrom., 9(5), 516, 1998. 53. Hsu, F. and Turk, J., Structural characterization of triacylglycerols as lithiated adduct by electrospray ionization mass spectrometry using low-energy collisionally activated dissociation on a triple stage quadrupole instrument, J. Am. Soc. Mass Spectrom., 10(7), 587, 1999. 54. Hsu, F. and Turk, J., Characterization of phosphatidylethanolamine as a lithiated adduct by triple quadrupole tandem mass spectrometry with electrospray ionization, J. Am. Soc. Mass Spectrom., 35(5), 595, 2000. 55. Chen, R. and Li, L., Lithium and transition metal ions enable low energy collisioninduced dissociation of polyglycols in electrospray ionization mass spectrometry, J. Am. Soc. Mass Spectrom., 12, 832, 2001. 56. Volosov, A.L.L. and Nicolas, J., Irregular vehicle-related ion suppression in pharmaceutical studies, Proceedings of the 51st ASMS Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, 2003. 57. Beato, B.D. et al. Strategies for dealing with matrix effects and interferences, in Proceedings of the 51st ASMS Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, 2003. 58. Avery, M.J., Quantitative characterization of differential ion suppression on liquid chromatography/atmospheric pressure ionization mass spectrometric bioanalytical methods, Rapid Commun. Mass Spectrom., 17(3), 197, 2003. 59. Matuszewski, B.K., Constanzer, M.L., and Chavez-Eng, C.M., Matrix effect in quantitative LC/MS/MS analyses of biological fluids: a method for determination of finasteride in human plasma at picogram per milliliter concentrations, Anal. Chem., 70, 882, 1998. 60. Matuszewski, B.K., Constanzer, M.L., and Chavez-Eng, C.M., Strategies for the assessment of matrix effect in quantitative bioanalytical methods based on HPLC– MS/MS, Anal. Chem., 75(13), 3019, 2003. 61. Sojo, L.E., Lum, G., and Chee, P., Internal standard signal suppression by co-eluting analyte in isotope dilution LC–ESI–MS, Analyst, 128(1), 51, 2003. 62. Liang, H.R., Foltz, R.L., Meng, M., and Bennett, P., Ionization enhancement in atmospheric pressure chemical ionization and suppression in electrospray ionization between target drugs and stable-isotope-labeled internal standards in

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 147/150

Matrix Effects: Causes and Solutions

63.

64.

65.

66.

67. 68.

69. 70.

71.

72.

73.

74.

75.

147

quantitative liquid chromatography/tandem mass spectrometry, Rapid Commun. Mass Spectrom., 17(24), 2815, 2003. Seliniotakis, R. et al. The use of post column addition to improve signal response and reduce matrix effects in bioanalytical LC/MS/MS assays, Proceedings of the 51st ASMS Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, 2003 Yamaguchi, J. et al. Utility of postcolumn addition of 2-(2-methoxyethoxy)ethanol, a signal-enhancing modifier, for metabolite screening with liquid chromatography and negative ion electrospray ionization mass spectrometry, Anal. Chem., 71(23), 5386, 1999. Yamaguchi, J. et al. Identification of rat urinary and biliary metabolites of esonarimod, a novel antirheumatic drug, using liquid chromatography/ electrospray ionization tandem mass spectrometry with postcolumn addition of 2(2-methoxyethoxy)ethanol, a signal-enhancing modifier, Drug Metab. Dispos., 29(6), 806, 2001. Jemal, M., Ouyang, Z., and Teitz, D.S., High performance liquid chromatography mobile phase composition optimization for the quantitative determination of a carboxylic acid compound in human plasma by negative ion electrospray high performance liquid chromatography tandem mass spectrometry, Rapid Commun. Mass Spectrom., 12(8), 429, 1998. Cech, N.B. and Enke, C.G., Practical implications of some recent studies in electrospray ionization fundamentals, Mass Spectrom. Rev., 20(6), 362, 2001. Shou, W.Z., Eerkes, A., and Weng, N., Simple means to alleviate sensitivity loss by TFA-containing mobile phases in LC–ESI/MS/MS bioanalysis, Proceedings of the 51st ASMS Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, 2003. Apffel, A. et al. Analysis of oligonucleotides by HPLC–electrospray ionization mass spectrometry, Anal. Chem., 69, 1320, 1997. Fountain, K.J., Gilar, M., and Gebler, J.C., Analysis of native and chemically modified oligonucleotides by tandem ion-pair reversed-phase high-performance liquid chromatography/electrospray ionization mass spectrometry, Rapid Commun. Mass Spectrom., 17(7), 646, 2003. Korfmacher, W.A. et al. Cassette-accelerated rapid rat screen: a systematic procedure for the dosing and liquid chromatography/atmospheric pressure ionization tandem mass spectrometric analysis of new chemical entities as part of new drug discovery, Rapid Commun. Mass Spectrom., 15(5), 335, 2001. Watt, A.P., Morrison, D., Locker, K.L., and Evans, D.C., Higher throughput bioanalysis by automation of a protein precipitation assay using a 96-well format with detection by LC–MS/MS, Anal. Chem., 72(5), 979, 2000. O’Connor, D., Clarke, D.E., Morrison, D., and Watt, A.P., Determination of drug concentrations in plasma by a highly automated, generic and flexible protein precipitation and liquid chromatography/tandem mass spectrometry method applicable to the drug discovery environment, Rapid Commun. Mass Spectrom., 16(11), 1065, 2002. Mei, H., Nardo, C., Wang, G., and Hsieh, Y., Application of precision 2000 in rapid rat pharmacokinetic screen: automated standard and sample preparation, in Proceedings of the 51st ASMS Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, 2003. Polson, C. et al. Optimization of protein precipitation based upon effectiveness of protein removal and ionization effect in liquid chromatography-tandem mass

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 148/150

Using Mass Spectrometry for Drug Metabolism Studies

148

76. 77. 78. 79.

80.

81.

82.

83. 84. 85.

86.

87.

88.

89.

90.

91.

92.

93.

spectrometry, J. Chromatogr., B: Analyt. Technol. Biomed. Life Sci., 785(2), 263, 2003. Rossi, D.T. and Zhang, N., Automating solid-phase extraction: current aspects and future prospects, J. Chromatogr., A, 885(1–2), 97, 2000. Wells, D., ‘‘96-well plate products for solid phase extraction’’ in sample prep perspectives, LC–GC, July, 600, 1999. Wells, D., ‘‘Accessory products for SPE using 96-well plates’’ in sample prep perspective, LC–GC, September, 808, 1999. Parker, T.D., 3rd, Wright, D.S., and Rossi, D.T., Design and evaluation of an automated solid-phase extraction method development system for use with biological fluids, Anal. Chem., 68(14), 2437, 1996. Janiszewski, J.S., Swyden, M.C., and Fouda, H.G., High-throughput method development approaches for bioanalytical mass spectrometry, J. Chromatogr. Sci., 38(6), 255, 2000. Lingeman, H. and Hoekstra-Oussoren, S.J., Particle-loaded membranes for sample concentration and/or clean-up in bioanalysis, J. Chromatogr., B: Biomed. Sci. Appl., 689(1), 221, 1997. Smith, G. and Loyd, T., Automated solid-phase extraction and sample preparation—finding the right solution for your laboratory, LC–GC, May, S22, 1998. Majors, R., A review of modern solid-phase extraction, LC–GC, S8, 1998. Lord, H.L. and Pawliszyn, J., Recent advances in solid-phase microextraction, LC–GC, S41, 1998. Ding, J. and Neue, U.D., A new approach to the effective preparation of plasma samples for rapid drug quantitation using on-line solid phase extraction mass spectrometry, Rapid Commun. Mass Spectrom., 13(21), 2151, 1999. Satinsky, D., Sklenarova, H., Huclova, J., and Karlicek, R., On-line coupling of sequential injection extraction with restricted-access materials for sample clean-up and analysis of drugs in biological matrix, Analyst, 128(4), 351, 2003. Ayrton, J. et al. Optimisation and routine use of generic ultra-high flow-rate liquid chromatography with mass spectrometric detection for the direct on-line analysis of pharmaceuticals in plasma, J. Chromatogr., A, 828(1–2), 199, 1998. Herman, J.L., Generic method for on-line extraction of drug substances in the presence of biological matrices using turbulent flow chromatography, Rapid Commun. Mass Spectrom., 16(5), 421, 2002. Grant, R.P., Cameron, C., and Mackenzie-McMurter, S., Generic serial and parallel on-line direct-injection using turbulent flow liquid chromatography/tandem mass spectrometry, Rapid Commun. Mass Spectrom., 16(18), 1785, 2002. Andersson, L.I., Molecular imprinting for drug bioanalysis. A review on the application of imprinted polymers to solid-phase extraction and binding assay, J. Chromatogr., B: Biomed. Sci. Appl., 739(1), 163, 2000. Hsieh, Y. et al. Direct analysis of plasma samples for drug discovery compounds using mixed-function column liquid chromatography tandem mass spectrometry, Rapid Commun. Mass Spectrom., 14(15), 1384, 2000. Boos, K.S. and Fleischer, C.T., Multidimensional on-line solid-phase extraction (SPE) using restricted access materials (RAM) in combination with molecular imprinted polymers (MIP), Fresenius J. Anal. Chem., 371(1), 16, 2001. Koeber, R. et al. Evaluation of a multidimensional solid-phase extraction platform for highly selective on-line cleanup and high-throughput LC–MS analysis of

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 149/150

Matrix Effects: Causes and Solutions

94.

95.

96.

97.

98.

99.

100.

101.

102.

103.

104.

105.

106.

107.

149

triazines in river water samples using molecularly imprinted polymers, Anal. Chem., 73(11), 2437, 2001. Beaudry, F., Le Blanc, J.C., Coutu, M., and Brown, N.K., In vivo pharmacokinetic screening in cassette dosing experiments; the use of on-line Prospekt liquid chromatography/atmospheric pressure chemical ionization tandem mass spectrometry technology in drug discovery, Rapid Commun. Mass Spectrom., 12(17), 1216, 1998. Parker, T.D., 3rd, Surendran, N., Stewart, B.H., and Rossi, D.T., Automated sample preparation for drugs in plasma using a solid-phase extraction workstation, J. Pharm. Biomed. Anal., 17(4–5), 851, 1998. Plumb, R.S., Gray, R.D., and Jones, C.M., Use of reduced sorbent bed and disk membrane solid-phase extraction for the analysis of pharmaceutical compounds in biological fluids, with applications in the 96-well format, J. Chromatogr., B: Biomed. Sci. App., 694(1), 123, 1997. Simpson, H. et al. High throughput liquid chromatography/mass spectrometry bioanalysis using 96-well disk solid phase extraction plate for the sample preparation, Rapid Commun. Mass Spectrom., 12(2), 75, 1998. Mallet, C.R. et al. Performance of an ultra-low elution-volume 96-well plate: drug discovery and development applications, Rapid Commun. Mass Spectrom., 17(2), 163, 2003. King, R. and Mahan, E., Eliminating ionization suppression in plasma extracts, in Proceedings of the 51st ASMS Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, 2003. Zhang, N., Hoffman, K.L., Li, W., and Rossi, D.T., Semi-automated 96-well liquid–liquid extraction for quantitation of drugs in biological fluids, J. Pharm. Biomed. Anal., 22(1), 131, 2000. Ramos, L., Bakhtiar, R., and Tse, F.L., Liquid–liquid extraction using 96-well plate format in conjunction with liquid chromatography/tandem mass spectrometry for quantitative determination of methylphenidate (Ritalin) in human plasma, Rapid Commun. Mass Spectrom., 14(9), 740, 2000. Basileo, G. et al. Quantitative determination of paclitaxel in human plasma using semi-automated liquid–liquid extraction in conjunction with liquid chromatography/tandem mass spectrometry, J. Pharm. Biomed. Anal., 32(4–5), 591, 2003. Bolden, R.D. et al. Semi-automated liquid—liquid back-extraction in a 96-well format to decrease sample preparation time for the determination of dextromethorphan and dextrorphan in human plasma, J. Chromatogr., B: Analyt. Technol. Biomed. Life Sci., 772(1), 1, 2002. Peng, S.X., Branch, T.M., and King, S.L., Fully automated 96-well liquid–liquid extraction for analysis of biological samples by liquid chromatography with tandem mass spectrometry, Anal. Chem., 73(3), 708, 2001. Sandahl, M., Mathiasson, L., and Jonsson, J.A., On-line automated sample preparation for liquid chromatography using parallel supported liquid membrane extraction and microporous membrane liquid–liquid extraction, J. Chromatogr., A, 975(1), 211, 2002. Ito, S. and Tsukada, K., Matrix effect and correction by standard addition in quantitative liquid chromatographic–mass spectrometric analysis of diarrhetic shellfish poisoning toxins., J. Chromatogr., A, 943, 39, 2002. Wilm, M. and Mann, M., Analytical properties of the nanoelectrospray ion source, Anal. Chem., 68(1), 1, 1996.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-04.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:32pm Page: 150/150

150

Using Mass Spectrometry for Drug Metabolism Studies

108. Karas, M., Bahr, U., and Dulcks, T., Nano-electrospray ionization mass spectrometry: addressing analytical problems beyond routine, Fresenius J. Anal. Chem., 366(6–7), 669, 2000. 109. Bahr, U., Pfenninger, A., Karas, M., and Stahl, B., High-sensitivity analysis of neutral underivatized oligosaccharides by nano-electrospray mass spectrometry, Anal. Chem., 69, 4530, 1997. 110. Juraschek, R., Dulcks, T., and Karas, M., Nanoelectrospray—more than just a minimized-flow electrospray ionization source, J. Am. Soc. Mass Spectrom., 10(4), 300, 1999. 111. Schmidt, A., Karas, M., and Dulcks, T., Effect of different solution flow rates on analyte ion signals in nano-ESI MS, or: when does ESI turn into nano-ESI?, J. Am. Soc. Mass Spectrom., 14(5), 492, 2003. 112. Andrews, C.L., Yang, E., Yu, C., and Vouros, P., The analysis of pharmaceutical compounds by LC/MS/MS utilizing a nano-splitting device: investigation of linearity and dynamic range, in Proceedings of the 51st ASMS Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, 2003.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 151/174

Chapter 5 Direct Plasma Analysis Systems Yunsheng Hsieh

5.1

Introduction

The combination of structural genomics techniques and high speed parallel chemical synthesis has resulted in large numbers of routine samples created as part of the in vivo and in vitro pharmacokinetic (PK) and drug metabolism (DM) experiments that are needed to support the discovery of new medicines. This increase in sample load has forced the development of higher throughput screening assays to handle the workload. The high-resolution power of chromatographic methodologies coupled to atmospheric pressure ionization– tandem mass spectrometry (API–MS/MS) has been able to reduce the need for most traditional sample preparation procedures and has also reduced the method development time required for drug analyses [1, 2]. Furthermore, fast high-performance liquid chromatography (HPLC) techniques in combination with the specificity of MS/MS detection have successfully demonstrated the capability of separating and identifying a wide range of small molecules using either a 1-min gradient or isocratic analyses [3–7]. However, sample preparation steps such as the protein precipitation procedure to remove proteins from biological samples are still essential prior to the HPLC–MS/MS assay for small molecules. These procedures are required not only to prevent the HPLC column from clogging in reversed-phase chromatography but also to avoid ion source contamination and matrix ionization suppression in the mass spectrometer [8, 9]. Therefore, most laboratories still utilize sample 0-8493-1963-3/05/$0.00+$1.50 ß 2005 by CRC Press

Copyright © 2005 CRC Press, LLC

151

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 152/174

Using Mass Spectrometry for Drug Metabolism Studies

152

preparation procedures such as protein precipitation, liquid–liquid extraction or solid phase extraction for HPLC–MS/MS analyses [10]. While these standard sample preparation procedures work well in many cases, they are often the slow step (the bottleneck) in the assay procedure; an alternative approach is direct injection analysis. Powell and Jemal [11] and Ackermann et al. [12] have reviewed procedures for direct injection of biological samples focusing on a dual-column approach and column switching techniques, respectively. In this chapter, we include the most current direct HPLC–MS/MS methods developed for the qualitative and quantitative analysis of the drug-related components in biological fluids and their application to new drug discovery assays.

5.2

On-line Solid-phase Extraction Procedures

Solid-phase extraction (SPE) has become one of the more popular techniques to remove interference materials in complex samples because of its simplicity, speed, and effectiveness. The SPE technique can be integrated into HPLC systems by column switching to provide for on-line sample extraction [13]. For on-line SPE, the biological samples are injected into the preconditioned cartridge or disposable pre-column (available under the brand names LiChrograph OSP-2 and PROSPEKTÕ ) followed by distilled water or buffer solution washing, which retains the target analytes. The potentially interfering endogenous components are flushed into the waste with distilled water. The purified analytes retained on the bonded phase of the cartridge are then eluted out into a series-connected analytical column via a switching valve. Simultaneously during the course of chromatographic separation, another cartridge is automatically exchanged and undergoes preconditioning in preparation for the next injection. The potential of several automated on-line SPE systems connected to one mass spectrometer was successfully demonstrated for the simultaneous determination of anabolic steroids and ten new drug candidates in human urine and animal plasma, respectively [14, 15]. In on-line SPE, the compounds of interest are delivered directly from the extraction cartridge into the mass spectrometer to exclude steps like sample extraction, elution, evaporation, and reconstitution, normally employed in traditional (off-line) SPE. The SPE system is often designed to operate at conventional flow rates of 1 mL/min [16]. An increase in the flow rate will lead to shorter times for de-salting and equilibration, but it may also result in a lower extraction recovery for the analytes. An on-line SPE–MS/MS method for the quantitative determination of naratriptan in the 0.05–10 ng/mL range in human serum was validated for its accuracy, precision, and specificity [16]. In summary, on-line sample preparation approaches provide better accuracy and precision as compared with off-line techniques. However, while it may be advantageous to avoid carry-over from previous injections, a major disadvantage of this type of on-line SPE is the single use of the extraction cartridge [17]. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 153/174

Direct Plasma Analysis Systems

5.3

153

Direct Plasma Injection using Restricted Access Media

Another promising packing material designed for direct extraction of small molecules in biological samples to allow multiple injections is the so-called restricted access media (RAM). The working principle of RAM phases is to isolate macromolecules from the targeted small molecules in biological fluids based upon their particle sizes and chromatographic interaction. The large macromolecules such as proteins, which are unable to penetrate the hydrophobic pores and the hydrophilic outer layer of the packing particles, are first eluted to waste. The small molecules such as drug compounds that penetrate the pores are retained through hydrophobic forces. These RAM columns permit the extraction of a wide variety of compounds in untreated proteinaceous fluids by preventing access of macromolecules to the bonded phase via a size-exclusion process combined with a hydrophilic outer packing surface while the low-molecular-mass analytes are retained by conventional retention mechanisms such as hydrophobic interaction. There are four types of RAM phases in common use which are differentiated based on their properties of their diffusion barrier and surface topochemistry: internal-surface reverse phase (ISRP) (ChromSpher 5 Biomatrix [18, 19], Chrompack LiChrospher ADS [20–29]); semi-permeable surfaces (SPS) (Regis [30–32], BioTrap 500, ChromTech [33]); dual zone (DZ, Diazem [34–36]); and mixed functional phases (MFP) (Capcell Pak MF, Shiseido) [37–40]. For ISRP type columns, the most popular RAMs, there is a physical diffusion barrier by an appropriate pore diameter to prevent the access to proteins, which is produced by bonding a high coverage hydrophilic phase such as glycerylpropyl (diol) groups to small pores. The bonded reversed phase, with the ligand being a C4, C8 or C18 moiety, covers the internal pore surfaces of modified silica. However, the alkyl-diol silica (ADS) column provides little chromatographic separation for the low-molecular-mass compounds. Therefore, it was recommended that this restricted access pre-column requires an additional analytical column for chromatographic separation in combination with a column-switching technique, using the so-called coupled-column mode (LC–LC) direct injection method [13] as depicted in Figure 5.1. For example, Koch et al. [20], developed a multidimensional direct LC–LC–MS/MS method for the quantitative determination of two secondary chain-oxidized monoester metabolites of diethylhexylphthalate (DEHP) in human urine. The phthalate analytes were stripped from the urine matrix by an ADS pre-column using a 1% aqueous solution of acetic acid and methanol (90:10, v/v) as the mobile phase at a flow rate of 0.8 mL/min. After this sample clean-up and enrichment step, all analytes were transferred to a reversed-phase mode analytical column following by electrospray ionization (ESI) and tandem mass spectrometric (MS/MS) detection. As described in a short communication, Muzic, Jr. [18] employed an ISRP column to isolate a radiopharmaceutical, (S)-[18F] fluorocarazolol, and its metabolites from various plasma samples. ADS pre-columns allow the extraction of a wide range of small molecules such as tetracyclines [19], alkylphenolic compounds [27], atropine, fenoterol, Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 154/174

154

Using Mass Spectrometry for Drug Metabolism Studies

Figure 5.1 (A) Column-switching setup for dual-column direct plasma injection system, initial valve-switching position. (B) Valve-switching position, desorption, separation, and transfer of the analytes to a tandem mass spectrometer.

ipratropium, procaine, sotalol, terbutaline [41], benzodiazepines [22, 25], salbutamol, clenbuterol [26], cortisol, arachidonic acid, and prednisolone [42]. Coupling an ADS packing material column to a chiral column has been reported for the direct determination of stereoselective drugs such as ketoprofen [21], trihexyphenidyl [23], atenolol [24], pirlindole [28], citalopram [29], and glucuronides of entacapone [43]. Semi-permeable surface (SPS) columns utilize the coating of polyethylene glycol with surfactants to form a bio-compatible layer [44]. The SPS columns appear to have less efficiency in protein removal as compared with ISRP columns and normally were employed as an auxiliary column to enhance both selectivity and sensitivity for direct plasma injection [30–32]. Dual zone (DZ) materials were generated by linking a hydrophilic perfluorobutylethylene dimethylsilyl (PFB) to the outer surfaces of the silica to repel macromolecules from reaching the bonded phase. The performance of the DZ column has been evaluated for the determination of polynuclear aromatic hydrocarbons in a hexane matrix [34], 13 human immunodeficiency virus-suppressing drugs in serum [35], soy isoflavones, such as genistein and daidzein, in rat plasma [36], all by direct injection of the sample matrix. The mixed-function column consists of hydrophilic polyoxyethylene groups (long chain) and hydrophobic phenyl groups (short chain) bonded to a polymer-coated silica surface to offer two separation processes: protein removal and analyte fractionation [45, 46]. The role of the separation on the polymer-coated mixed-function (PMCF) phase was to exclude proteins due to their size and concentrate target substances based on a reversed-phase retention mechanism from a large volume of biological fluids. The samples are first delivered onto the PMCF column with a weak mobile phase (less than 10% organic phase at a pH greater than 6) to prevent protein Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 155/174

Direct Plasma Analysis Systems

155

precipitation. The surface structure of the PCMF was designed to allow largemolecular-mass compounds to pass through the column due to the restricted access to the surface formed by the longer chain with a hydrophilic group at the end. The small molecules are retained by interacting with the hydrophobic groups and are eluted to the detector with a stronger mobile phase (less than 10% aqueous solvent) via reversed-phase chromatographic separation. The PCMF column was not expected to produce plate numbers as large as regular analytical columns. However, it provides sufficient separation capability for targeted compounds with MS/MS detection and is superior to an ADS column in terms of chromatographic power. Direct plasma injection using a single ADS column (without coupling to an analytical column) for quantitative analysis of a few drug candidates was tested in our laboratory and it was found to provide acceptable results. However, in the absence of adequate chromatography during the HPLC–MS/MS procedure, the ionization of the administrated drugs may be suppressed by non-drug-related co-eluting components in the complex biological samples [2, 6] or mass spectral interference may occur from their biotransformation products such as the acylglucuronide from an acid drug [47]. A simple and efficient direct plasma injection system using a single mixedfunction column HPLC–MS/MS procedure for the determination of a drug discovery compound was successfully developed in our laboratory [37]. In this method, untreated plasma samples were directly injected onto a polymercoated mixed-function (PCMF) column for both the sample extraction and analyte separation steps. This dual phase column allows proteins and other macromolecules to pass through the column due to restricted access to the surface of the packing materials while retaining the drug molecules on the bonded reversed-phase absorbent. A 10- to 80-mL portion of the diluted plasma sample (diluted with water containing internal standard in a 1:3 ratio) was transferred and injected by the autosampler onto the CAPCELL MF C8 column (Phenomenex) with a largely aqueous mobile phase [4 mM ammonium acetate in water–acetonitrile (90:10)] at a consistent flow-rate of 1–1.2 mL/min. The post-column switching valve was first diverted to waste to remove the macromolecules from the plasma matrix, then after 1.5 min, the valve was switched to deliver the flow to a tandem mass spectrometer and a linear gradient from 0 to 95% organic mobile phase [4 mM ammonium acetate in water–acetonitrile (10:90)] was run over 1 min, then held for 2 min to elute and separate all the analytes. The separation stages were followed by the equilibration stage with the valve switched back to waste and mobile phase changed from organic to aqueous mobile phase. The retention times for analytes and internal standard were less than 3.5 min depending on the gradient conditions. The total run cycle time was less than 5 min. Figure 5.2 compares the concepts of simultaneous or sequential process using singlecolumn or coupled-column modes for direct HPLC–MS/MS assays, respectively. In a comparative study, the sensitivity of the test compound obtained by the single column method was about four times higher than that obtained by the coupled-column approach [37]. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 156/174

156

Using Mass Spectrometry for Drug Metabolism Studies

Figure 5.2 Flow chart of direct plasma injection method using either single-column or coupledcolumn modes for HPLC–MS/MS.

The ruggedness and durability of the CAPCELL MF column was explored by successive injections of rat plasma samples spiked with a drug discovery compound and an internal standard in two 96-well plates. After 200 plasma sample injections the response ratio (analyte vs internal standard,%CV ¼ 4.6) and the retention times for analyte and internal standard were found to be consistent and no column deterioration was observed. A linear relation of both analyte and internal standard based on peak areas up to 80-mL injection volumes was also observed. With this single column method we have seen a consistent peak shape throughout the entire calibration curve ranging from 1 to 2500 ng/mL. The analytical recoveries of the test compound were studied with mouse, rat, and guinea pig plasma samples spiked at the 500 ng/mL concentration level. The calculated recovery values of the test compound (N ¼ 5) were found to be 94% (%CV ¼ 6.1), 104% (%CV ¼ 3.9) and 92% (%CV ¼ 5.1) in mouse, rat, and guinea pig plasma, respectively. These values were reproducible and acceptable for drug analysis in a discovery setting. The accuracy of this direct plasma injection system was examined by strictly comparing the analytical results with the (standard) protein precipitation method and another direct dual-column (LC–LC) method. The results showed that the direct analysis method using the PCMF column was equivalent with other approaches in terms of accuracy, but is simpler and more efficient in terms of sample preparation and instrumental setup. To avoid protein precipitation during direct plasma injection procedures, the concentration of the organic modifier and the pH of the washing mobile Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 157/174

Direct Plasma Analysis Systems

157

phase applied for the sample-loading step must be non-denaturing. The use of a first wash bottle filled with pure water and a second one with 50% methanol in water for cleaning the injection needle is suggested both to prevent protein precipitation and to avoid carry-over from previous injections. It has been suggested that trifluoroethanol is an effective reagent for removing the buildup of proteins in reversed-phase columns [48]. We found that trifluoroethanol was also effective in restoring the performance of a PCMF column after multiple direct plasma injections. It is extremely important to learn about circulating metabolites in plasma because they may explain pharmacodynamic or toxicological effects as well as suggest further chemical structure modifications during the lead optimization process for new drug discovery [38]. For example, in our recent report [38], we used the direct HPLC–MS/MS method using a single PCMF column to separate the dosed compound and its hydroxyl metabolites in plasma samples in order to provide metabolite profiling information. These metabolites were further characterized based on their MS/MS fragmentation patterns and NMR spectra. Two approaches for providing high throughput pharmacokinetic screening, are cassette dosing (N-in-one dosing) [49] and sample pooling [39, 40]. While cassette dosing seems to be an efficient way to simultaneously screen multiple new chemical entities, the potential for drug–drug interactions is a concern for this technique even at a low dose [50]. Alternately, sample pooling following one-in-one dosing provides a smaller number of study samples to be assayed while still generating substantial PK information. Sample pooling techniques demand more sensitive and selective bioanalytical assays due to the dilution that occurs when combining plasma samples for simultaneous determination of multiple drug molecules. The large sample loading capacity (over 80 mL) of the PCMF column results in enhanced sensitivity, which can compensate for the dilution factor of pooled plasma samples. This is one of the advantages of using direct plasma injection procedure in combination with sample pooling technique [40]. The applicability of simultaneous determination of six drug candidates and one internal standard in a pooled study rat plasma sample using the PCMF column method was demonstrated recently by Hsieh et al. [40]. The PCMF column can be coupled either to atmospheric pressure chemical ionization (APCI), electrospray ionization (ESI) or atmospheric pressure photoionization (APPI) MS (for more information on APPI, see Chapter 9) sources and a tandem mass spectrometer for the quantitative determination of drug molecules [40]. No discrepancy was observed in terms of assay accuracy between the APCI and the ESI interfaces coupled to the tandem mass spectrometer. In a separate study, we also compared analytical results obtained from the traditional method using protein precipitation and off-line SPE procedures and the direct injection method for monkey plasma analysis by HPLC–MS/MS. Monkey plasma samples containing two analytes were obtained from pharmacodynamic experiments that were important studies in selecting biologically active lead compounds for a drug discovery project. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 158/174

Using Mass Spectrometry for Drug Metabolism Studies

158

Figure 5.3 Comparison of conventional sample preparation procedures using the HPLC assay versus simplified sample preparation procedures and no sample preparation using the standard HPLC–MS/MS assay and direct HPLC–MS/MS assay, respectively.

The analytical results obtained by the single-column direct injection method were comparable, within 15% difference, with those obtained by the traditional method using either a protein precipitation or off-line SPE procedure [39]. Figure 5.3 shows a schematic comparison of the sample preparation procedures needed when using conventional HPLC, HPLC–MS/MS or direct HPLC–MS/MS systems.

5.4

High Flow Chromatography for Direct Plasma Injection

High flow rate liquid chromatography–tandem mass spectrometry using a large particle size stationary phase for rapid determination of pharmaceuticals in biological samples with no prior sample preparation has been reported in recent years [51–58]. Typical conditions for high flow rate chromatography involve loading biological samples onto a large particle size extraction column (1
50 mm, 30–50 mm, Oasis, Waters) at a flow rate of 4 mL/min with 100% aqueous mobile phase followed by elution onto a conventional analytical column at a regular flow rate of 1 mL/min. The extraction columns are normally made of a mixed hydrophobic–hydrophilic polymer phase with a plasma loading capacity of up to 100 mL. Although the use of a single extraction format for direct injection system allows for rapid drug assays [53], little chromatographic separation is achieved for the purified analytes. Therefore, most direct plasma injection applications with high flow chromatography involve dual [51–55] or even ternary-column [56] configurations. A direct comparison to manual liquid–liquid extraction method using a drug candidate produced by Bristol-Myers Squibb Pharmaceutical Research Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 159/174

Direct Plasma Analysis Systems

159

Institute was described recently by Jemal et al. [54]. The total analysis time for both methods was 2.0 min per sample. The accuracy and inter- and intra-day precision obtained from the quality control samples were less than 10% for both methods. The human pharmacokinetic results obtained by both methods were comparable. However, the sample preparation time for the direct injection method was about one quarter of the time required for liquid–liquid extraction approach. High flow rate direct-injection systems have been employed in support of in vivo pharmacokinetic studies for multiple components such as olanzapine, clozapine, N-desmethylclozapine [51], pravastatin and its positional isomer [53], aminopterin, apomorphine, benzoylecgonine, carbamazepine, temazepam [55], amitriptyline, nortriptyline, doxepin, dosulepin, dibenzepin, opipramol, and melitracen [57]. Furthermore, the introduction of multiple sprayer interfaces to mass spectrometers provides the potential for even higher throughput. By combining four extraction columns in parallel to a four-way multiple sprayer interface to the mass spectrometer, Bayliss et al. [52] were able to monitor an isoquinoline drug from four plasma samples simultaneously, at low ng/mL concentrations without any sample preparation and with a throughput of up to 120 samples per hour. Wu and co-workers [49] described the application of turbulent flow chromatography coupled to a tandem mass spectrometer for direct pharmacokinetic screening using cassette dosing (14-in-1). To avoid column blockage resulting from protein precipitation by the organic mobile phase, after each injection the aqueous solvent was first used to wash away the plasma residue before washing with an organic solvent. Ten marketed drugs, including alprazolam, oxazepam, temazepam, estazolam, triprolidine, phentolamine, carbamazepine, fenfluramine, puromycin, haloperidol, and bromazepam, were used to evaluate the turbulent-flow column-switching system for direct plasma injection assays. On the basis of their assay results for a large number of compounds [49], this turbulent-flow column-switching method was found to be applicable to poorly water soluble and highly protein bound compounds. For compounds that show extremely strong protein binding, some modifications during sample loading or preparation to the turbulent flow chromatography method were suggested. For example, the use of a low-flow (0.5 mL/min) loading step prior to high-flow washing step to allow more contact time between the analytes and extract sorbent or acidification of the plasma sample in 0.5% formic acid to reduce protein binding were recommended. As a good example, the use of turbulent flow chromatography–tandem mass spectrometry for the rapid, direct determination of an isoquinoline compound in plasma and serum samples was reported [58].

5.5

Direct Monolithic Silica Chromatographic Systems

A useful approach to enhance column efficiency (smaller H) is to increase the column permeability, K ¼ L/
P, where , , L, and
P are linear velocity of Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 160/174

160

Using Mass Spectrometry for Drug Metabolism Studies

mobile phase, solvent viscosity, column length, and pressure drop, respectively in a particle packed column. This can be achieved by using a monolithic silica column, a novel stationary phase with small-sized skeletons and large throughpores to simultaneously reduce the diffusion path length and flow resistance relative to a traditional, particle packed column [59–61]. Monolithic silica columns carrying hydrophobic surface modification made from a single piece of porous silica gel can be operated at higher flow rates without a concern for the back-pressure. The low back-pressure observed from increasing mobile phase flow rates is due to the higher permeability of monolithic silica versus particulate silica columns, which yields a significantly better E, separation impedance values, (flatter H vs  curves) to make high-speed separation possible without a noticeable effect on chromatographic resolution [7, 61, 62]. In a comparative test on the column performance of microparticulate C18 bonded and monolithic C18 bonded reversed-phase HPLC, Bidlingmaier and co-workers [63] demonstrated that both HPLC columns showed a similar column performance and selectivity. In addition, the monolithic silica rod column maintained the excellent separation power even at higher flow rates. Wu and co-authors [62], and Zeng et al. [64] demonstrated the capability of using a monolithic silica column for a baseline separation within 1 min with a plasma extract mixture containing tempazepam, tamoxifen, fenfluramine, and alprozolam. Good column ruggedness, separation efficiency and signal/noise ratios were achievable after 600 plasma extract injections up to a flow rate of 6 mL/min using a commercial monolithic column. Monolithic column separations for a mixture of fenfluramine, temazepam, oxazepam, and tamoxifen combined with on-line high-flow extraction were developed for direct plasma injection analysis. A total cycle time of 1.2 min using a constant flow rate of 4 mL/min was achieved via column switching. A total of over 400 plasma samples were directly analyzed in less than 10 h. The described coupledLC mode direct plasma injection system was routinely used by Wu and co-workers [64] to support in vivo pharmacokinetic studies for drug discovery programs. Plumb and his colleagues [65] first reported the potential of using an alkylbonded silica rod column coupled to a tandem mass spectrometer for direct plasma injection. In their experimental design for direct plasma analysis, 20-mL aliquots of prepared plasma standards were injected onto a 50
4.6 mm Chromolith SpeedROD RP-18e column. The monolithic silica column was eluted with both 0.1% formic acid in 100% aqueous mobile phase and 0.1% formic acid in 95% acetonitrile mobile phase at a flow rate of 4 mL/min. The column eluent was split such that 10% of that was directed to the mass spectrometer and the rest was directed to waste. The first 0.5 min after each injection was for protein removal and the column eluent was directed to waste using an automated column-switching valve [65]. The silica rod column was operated continuously for about 300 injections for a robustness test. The column performance of the silica rod was observed to decrease significantly following these plasma injections in the isocratic mode but remained constant in the gradient mode. The model compounds tested were uracil, ethyl paraben, Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 161/174

Direct Plasma Analysis Systems

161

butyl paraben, naphthalene, and anthracene. An example showing the importance of chromatographic resolution for direct plasma injection system by using paracetamol and its glucuronide metabolite was also illustrated [65]. We then modified the aforementioned procedure by employing a flow programming technique and a monolithic silica column for the high-speed direct determination of a drug discovery compound and its major circulating amine metabolite (M-72) in rat plasma with a 1-min runtime [66]. A 10-mL portion of the diluted plasma sample (diluted 1:1 with water containing the internal standard) was injected by the autosampler onto the monolithic silica C18 column. The switching valve was first diverted to waste for the removal of the macromolecules from the plasma matrix at a high flow rate of 8 mL/min for 0.5 min with an aqueous mobile phase. The valve was then switched to the mass spectrometer and a fast mobile phase and flow rate gradient from 0 to 100% organic mobile phase and from 8 mL/min to 1.2 mL/min was initiated to elute and separate the analytes. The separation stages were followed by the equilibration stage with the divert valve switched back to the waste and the mobile phase changed from organic to aqueous. Figure 5.4 demonstrates that the retention time and band width remain unchanged with increasing injection volumes. After 200 plasma injections on a 50
4.6 mm monolithic silica column, consistent column efficiency of close to 39,000 theoretical plates/m and reproducible retention times for the analytes were observed as shown in Figure 5.5. The apparent on-column recoveries of 12 test compounds in rat plasma samples were greater than 90%. The described fast direct plasma injection method was tested over a 3-day period with the inter-day coefficient of variation (CV) of less than 15% for both analytes [66]. It is important to be able to simultaneously assay for bioactive metabolites to help explain the observed pharmacokinetic or toxicological behavior as well as to suggest further chemical structure modifications for drug discovery programs. The direct monolithic column HPLC–MS/MS method was also applied to the simultaneous determination of a lead compound and its amine

Figure 5.4 Direct monolithic column SRM chromatograms of the compound I after 10 mL, 20 mL, 30 mL and 40 mL plasma injection. Adapted from Hsieh et al. Anal Chem, 75(8), 1812, 2003. ß 2003 with permission from American Chemical Society.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 162/174

Using Mass Spectrometry for Drug Metabolism Studies

162

Figure 5.5 Comparison of chromatographic performance at the first (solid line) and 192nd (dotted line) injections of diluted rat plasma. (Adapted from Hsieh et al. [66]. With permission.)

metabolite (M-72) to demonstrate the suitability of fast direct analyses for actual drug discovery samples. The dosed compound and its amine metabolite were simultaneously assayed with a baseline resolution within about a 1-min runtime. The separation efficiencies of the dosed compound and its amine metabolite were approximately 22,000 and 39,000 theoretical plates/m, respectively, by direct plasma injection. The pharmacokinetic results obtained by this direct plasma injection method were compared with those obtained by the traditional protein precipitation method as indicated in Figure 5.6. The results showed that the direct analysis method was equivalent with the nondirect injection methods in terms of accuracy.

5.5.1

Semi-automated drug plasma stability measurement

The stability of lead molecules in plasma is a concern in both drug discovery and drug development areas. Except for pro-drugs, drug candidates undergoing rapid degradation in plasma may have unreliable pharmacokinetic parameters due to the difficulties in providing a reliable assay. In addition, plasma stability data could be useful in drug discovery programs to avoid the selection of unstable compounds as drug candidates. Traditionally, drug stability analyses in plasma required time-consuming sample preparation procedures, typically including sequential plasma extraction at each incubation time intervals and incubation temperature as shown in Figure 5.7 [67, 68]. Plasma samples from individual incubation timepoints were manually prepared Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 163/174

Direct Plasma Analysis Systems

163

Figure 5.6 Plasma concentration profiles of (a) compound I and (b) its amine metabolite obtained by direct and indirect monolithic column HPLC–MS/MS method and traditional particlepacked silica column HPLC–MS/MS method. (Adapted from Hsieh et al. [66]. With permission.)

Figure 5.7 Conventional procedures used for the stability measurement of drug compounds in plasma.

by using macromolecule removal techniques such as protein precipitation prior to HPLC analysis. Therefore, the conventional labor intensive procedures for measuring the stability of drug compounds in plasma have not been suitable for evaluating a large number of biologically potent compounds. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 164/174

164

Using Mass Spectrometry for Drug Metabolism Studies

Recently, we combined the utility of a thermostatic autosampler (used as an incubator) and the direct single column HPLC–MS/MS system for the semiautomated stability measurement of drug molecules in plasma. Untreated rat, mouse, monkey, and human plasma samples spiked with one drug compound were immediately placed into a 96-well plate in the thermostatic autosampler set at various temperatures. These plasma samples containing the test compound were then sequentially and repetitively injected into the direct HPLC–MS/MS system as shown in Figure 5.8. In the example described [69], we were able to sequentially and simultaneously monitor the responses of the test compound (M) (Figure 5.9) and its carboxylic acid degradation product (M þ 1) (Figure 5.10) in rat plasma as a function of injection intervals and temperatures. In this example, due to the 1 Da difference in the molecular weight between the test compound and its degradation product, the two compounds were not distinguishable on the basis of their MS/MS response characteristics, but could be completely resolved by the PCMF column. The reduction of the precursor ion responses and the growth of the degradation product signals showed the instability of the test compound in plasma

Figure 5.8 Semi-automated procedures for the stability measurement of drug compounds in plasma.

Figure 5.9 Direct HPLC–APCI–MS/MS chromatograms of the test compound in rat plasma after (a) 5 min, (b) 29 min, (c) 53 min, (d) 77 min, (e) 125 min, (f) 149 min, and (g) 173 min incubation at 37 C. (Adapted from Wang et al. [69]. With permission.)

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 165/174

Direct Plasma Analysis Systems

165

Figure 5.10 Direct HPLC–APCI–MS/MS chromatograms of the carboxylic acid metabolite in rat plasma after (a) 5 min, (b) 29 min, (c) 53 min, (d) 77 min, (e) 125 min, (f) 149 min, and (g) 173 min. The incubation temperature was 37 C. (Adapted from Wang et al. [69]. With permission.)

Figure 5.11 The disappearance of the test compound in rat plasma is correspondent to the growth of its M þ 1 metabolite. (Adapted from Wang et al. [69]. With permission.)

(see Figure 5.11). The results of plasma stability of the test compounds obtained by the manual method using a protein precipitation procedure and the semi-automated direct injection method were found to be comparable [69]. We further investigated a cassette assay procedure for an even higher throughput screen-type assay to simultaneously measure the stability of multiple drug candidates in several plasma types [70]. The proposed ten-in-one approach was shown to be reliable as a screen-type assay for semi-automated plasma stability measurement and provided ten times greater sample Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 166/174

166

Using Mass Spectrometry for Drug Metabolism Studies

throughput than the conventional single assay method. For the proposed semiautomated procedure, individual rat, mouse, monkey, and human plasma samples were spiked with ten test compounds in the thermostatic autosampler (also used as the incubator) which was programmed for sequential injections into the direct HPLC–APCI–MS/MS system. The peak responses of all analytes from the rat, mouse, monkey or human plasma were simultaneously monitored every 7 min. The reconstructed mass chromatograms of all ten compounds of interest after approximately 30-min (solid line) and 180-min (dotted line) incubation times are shown in Figure 5.12. The retention times and peak shape for all analytes were found to be reproducible throughout the experiment. The stability of ten test compounds in the rat, mouse, monkey, and human plasma as indicated by the changes of peak responses were simultaneously measured. Compounds #2 and 3 were observed to be stable in mouse, monkey and human plasma within the 3-h incubation time at room temperature but unstable in the rat plasma (Figure 5.13). The stability results of clozapine and nine drug discovery compounds in rat, mouse, monkey, and human plasma obtained by the conventional manual procedures using proteinprecipitation and the proposed semi-automated method using cassette assay procedure were found to be in a good agreement (Figure 5.13).

Figure 5.12 Reconstructed direct HPLC–MS/MS chromatograms of clozapine and the test compounds #1 through #9 in the spiked rat plasma after approximately 5-min (solid line) and 180-min (dotted line) incubation. (Adapted from Wang et al. [70]. With permission.)

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 167/174

Direct Plasma Analysis Systems

167

Figure 5.13 Comparison of stability results of the test compounds #2 and #3 in rat plasma obtained by the proposed cassette assay and by the traditional single component incubation procedure. (Adapted from Wang et al. [70]. With permission.)

In conclusion, drug stability in plasma, as indicated by the change of the mass chromatographic peak area for the test compounds, was a function of animal species, incubation time and incubation temperature. The analytical results of the drug stability test in plasma obtained by the semi-automated direct plasma injection method were found to be comparable with those obtained by the traditional manual method using the protein precipitation procedure. This higher throughput procedure allows one to perform plasma stability structure relationships (PSSR) as part of lead optimization.

5.6

Matrix Ionization Suppression Studies

The accuracy and reproducibility of the analytical results obtained by HPLC–MS/MS method is often affected by the degree of matrix ionization suppression effects (see Chapter 4 for more on this topic) that vary with different sample preparation methods and ionization techniques [2, 5, 6, 71–76]. In our laboratory, we routinely investigate the impact of matrix ionization suppression effects for any new HPLC–MS/MS methods [5, 6, 75] or direct HPLC–MS/MS methods [66, 70] using the post-column infusion technique (Figure 5.14) [74]. For example, as shown by Wang et al. [70], in order to observe the matrix effect on the direct mixed-functional column HPLC–MS/MS system of plasma samples, we monitored the APCI responses for all ten compounds using the post-column infusion scheme. The mixture of analytes was continuously infused into the mass spectrometer by combining it with the HPLC effluent. The differences in ionization efficiency between the extracted infusion mass chromatograms from a Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 168/174

Using Mass Spectrometry for Drug Metabolism Studies

168

Figure 5.14 Schematic of the post-column infusion system for the study of matrix ionization suppression effects on direct HPLC–MS/MS methods.

mobile phase injection (for reference signals) and plasma injection are caused by the matrix effect resulting from co-eluting interference materials in the plasma samples. Any change in consistent APCI responses of the infused compounds monitored after the divert valve was switched to the mass spectrometer were presumed to be due to ionization suppression caused by endogenous molecules from the plasma samples which eluted from the PCMF column. The main objective of the post-column infusion experiments was to access the extent of the matrix effect time window. For accurate quantitative determination, it is strongly recommended that the retention times of all analytes should be in the chromatographic region of little or no matrix ion suppression. As shown in Figure 5.15, no difference between these infusion mass chromatograms was observable suggesting that those endogenous components that would typically produce matrix ionization suppression may be simultaneously removed along with other macromolecules through the PCMF column after plasma injection. These data suggest that reduction in matrix ionization suppression effects may be another advantage of using the direct single-column HPLC–MS/MS method. The impact of matrix effects when employing a monolithic silica rod column for the direct HPLC–MS/MS system was also monitored using the post-column infusion technique [66]. These results provided information about the ability of the monolithic column to remove endogenous plasma components that can cause changes in the observed ionization response of the analytes. The data demonstrated that little or no matrix ion suppression would be seen for both analytes and internal standard when this direct HPLC–MS/MS method was employed.

5.7

Conclusions

The inherent selectivity of HPLC systems with tandem mass spectrometric detection allows for fast chromatography and simple sample preparation. Unfortunately, sample preparation is often the rate-limiting step in efficient HPLC–MS/MS methods for the determination of pharmaceuticals in Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 169/174

Direct Plasma Analysis Systems

169

Figure 5.15 The reconstructed infusion mass chromatograms of clozapine and the test compounds #1 through #9 (from top to bottom) after injection of the mobile phase B (dotted line) and rat plasma (solid line). (Adapted from Wang et al. [70]. With permission.)

biological fluids. An automated method that performs on-line extraction and chromatographic separation is advantageous as compared to off-line liquid– liquid or solid-phase extraction techniques. The on-line automated HPLC– MS/MS methods have the following advantages when providing direct plasma injection: on-column enrichment of analytes, higher sample throughput, costeffective assay, better precision, accuracy and sensitivity. On-line techniques can be used for the semi-automated evaluation of plasma drug stability. Overall, single column integrated HPLC–MS/MS methods appear to be a good choice for direct plasma injection systems because of their efficiency and simplicity.

References 1. Huang, E.C. et al. Atmospheric pressure ionization mass spectrometry, Anal. Chem., 62, 713A, 1990. 2. Miller-Stein, C. et al. Rapid method development of quantitative LC–MS/MS assays for drug discovery, Am. Pharm. Rev., 3, 54, 2000.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 170/174

170

Using Mass Spectrometry for Drug Metabolism Studies

3. Cheng, Y., Lu, Z., and Neue, U., Ultrafast liquid chromatography/ultraviolet and liquid chromatography/tandem mass spectrometric analysis, Rapid Commun. Mass Spectrom., 15(2), 141, 2001. 4. Rule, G., Chapple, M., and Henion, J., A 384-well solid-phase extraction for LC/ MS/MS determination of methotrexate and its 7-hydroxy metabolite in human urine and plasma, Anal. Chem., 73(3), 439, 2001. 5. Hsieh, Y. et al. Simultaneous fast HPLC–MS/MS analysis of drug candidates and hydroxyl metabolites in plasma, J. Pharm. Biomed. Anal., 33(2), 251, 2003. 6. Hsieh, Y. et al. Quantitative screening and matrix effect studies of drug discovery compounds in monkey plasma using fast-gradient liquid chromatography/tandem mass spectrometry, Rapid Commun. Mass Spectrom., 15(24), 2481, 2001. 7. Hsieh, Y. et al. Simultaneous determination of a drug candidate and its metabolite in rat plasma samples using ultrafast monolithic column high-performance liquid chromatography/tandem mass spectrometry, Rapid Commun. Mass Spectrom., 16(10), 944, 2002. 8. Henion, J. et al. Sample preparation and analysis strategies for high throughput LC/MS/MS analysis of biological samples, Am. Pharm. Rev., 3, 19, 2000. 9. Henion, J., Brewer, E., and Rule, G., Sample preparation for LC/MS/MS: analyzing biological and environmental samples, Anal. Chem., 70(19), 650A, 1998. 10. Plumb, R.S. et al. Quantitative analysis of pharmaceuticals in biological fluids using high-performance liquid chromatography coupled to mass spectrometry: a review, Xenobiotica, 31(8–9), 599, 2001. 11. Powell, M.L. and Jemal, M., Rapid chromatography coupled with direct injection LC/MS/MS for quantitative bioanalysis, Am. Pharm. Rev., 4(3), 63, 2001. 12. Ackermann, B.L., Murphy, A.T., and Berna, M.J., The resurgence of column switching techniques to facilitate rapid LC/MS/MS based bioanalysis in drug discovery, Am. Pharm. Rev., 5(1), 54, 2002. 13. Boos, K.S. and Grimm, C., High-performance liquid chromatography integrated solid-phase extraction using restricted access precolumn packings, Trends Anal. Chem., 18, 175, 1999. 14. Barron, D. et al. Direct determination of anabolic steroids in human urine by online solid-phase extraction/liquid chromatography/mass spectrometry, J. Mass Spectrom., 31(3), 309, 1996. 15. McLoughlin, D.A., Olah, T.V., and Gilbert, J.D., A direct technique for the simultaneous determination of 10 drug candidates in plasma by liquid chromatography–atmospheric pressure chemical ionization mass spectrometry interfaced to a Prospekt solid-phase extraction system, J. Pharm. Biomed. Anal., 15(12), 1893, 1997. 16. Bowers, G.D. et al. Automated SPE and tandem MS without HPLC columns for quantifying drugs at the picogram level, LC–GC, 15, 48, 1997. 17. Needham, S.R. and Brown, P.R., The role of the column for the analysis of drugs and other components by HPLC/ESI/MS: part II, Am. Pharm. Rev., 4(1), 79, 2001. 18. Muzic, R.F., Jr. et al. Solid-phase analysis method for (S)-[18F]fluorocarazolol and its metabolites, J. Chromatogr., B: Biomed. Sci. Appl., 759(2), 355, 2001. 19. Weimann, A. and Bojesen, G., Analysis of tetracyclines in raw urine by columnswitching high-performance liquid chromatography and tandem mass spectrometry, J. Chromatogr., B: Biomed. Sci. Appl., 721(1), 47, 1999. 20. Koch, H.M., Gonzalez-Reche, L.M., and Angerer, J., On-line clean-up by multidimensional liquid chromatography–electrospray ionization tandem mass spectrometry for high throughput quantification of primary and secondary

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 171/174

Direct Plasma Analysis Systems

21.

22.

23.

24.

25.

26.

27.

28.

29.

30.

31.

32.

33.

34.

171

phthalate metabolites in human urine, J. Chromatogr., B: Analyt. Technol. Biomed. Life Sci., 784(1), 169, 2003. Baeyens, W.R. et al. Application of the restricted-access precolumn packing material alkyl-diol silica in a column-switching system for the determination of ketoprofen enantiomers in horse plasma, J. Chromatogr., A, 871(1–2), 153, 2000. Mullett, W.M. et al. Bio-compatible in-tube solid-phase microextraction capillary for the direct extraction and high-performance liquid chromatographic determination of drugs in human serum, J. Chromatogr., A, 963(1–2), 325, 2002. Capka, V., Xu, Y., and Chen, Y.H., Stereoselective determination of trihexyphenidyl in human serum by LC–ESI–MS, J. Pharm. Biomed. Anal., 21(3), 507, 1999. Lamprecht, G. et al. Enantioselective analysis of (R)- and (S)-atenolol in urine samples by a high-performance liquid chromatography column-switching setup, J. Chromatogr., B: Biomed. Sci. Appl., 740(2), 219, 2000. Mullett, W.M. and Pawliszyn, J., Direct LC analysis of five benzodiazepines in human urine and plasma using an ADS restricted access extraction column, J. Pharm. Biomed. Anal., 26(5–6), 899, 2001. Hogendoorn, E.A. et al. The potential of restricted access media columns as applied in coupled-column LC/LC–TSP/MS/MS for the high-speed determination of target compounds in serum. Application to the direct trace analysis of salbutamol and clenbuterol, Anal. Chem., 70(7), 1362, 1998. Petrovic, M., Tavazzi, S., and Barcelo, D., Column-switching system with restricted access pre-column packing for an integrated sample cleanup and liquid chromatographic–mass spectrometric analysis of alkylphenolic compounds and steroid sex hormones in sediment, J. Chromatogr., A, 971(1–2), 37, 2002. Chiap, P. et al. Automated determination of pirlindole enantiomers in plasma by on-line coupling of a pre-column packed with restricted access material to a chiral liquid chromatographic column, J. Pharm. Biomed. Anal., 27(3–4), 447, 2002. Ohman, D., Carlsson, B., and Norlander, B., On-line extraction using an alkyl-diol silica precolumn for racemic citalopram and its metabolites in plasma. Results compared with solid-phase extraction methodology, J. Chromatogr., B: Biomed. Sci. Appl., 753(2), 365, 2001. Marrubini, G. et al. Improved coupled column liquid chromatographic method for high-speed direct analysis of urinary trans, trans-muconic acid, as a biomarker of exposure to benzene, J. Chromatogr., B: Biomed. Sci. Appl., 751(2), 331, 2001. Hogendoorn, E.A. et al. Semi-permeable surface analytical reversed-phase column for the improved trace analysis of acidic pesticides in water with coupled-column reversed-phase liquid chromatography with UV detection. Determination of bromoxynil and bentazone in surface water, J. Chromatogr., A, 858(1), 45, 1999. Yu, Z. and Westerlund, D., Direct injection of large volumes of plasma in a columnswitching system for the analysis of local anaesthetics. I. Optimization of semipermeable surface precolumns in the system and characterization of some interference peaks, J. Chromatogr., A, 725(1), 137, 1996. Needham, S.R., Cole, M.J., and Fouda, H.G., Direct plasma injection for highperformance liquid chromatographic–mass spectrometric quantitation of the anxiolytic agent CP-93 393, J. Chromatogr., B: Biomed. Sci. Appl., 718(1), 87, 1998. Gustavson, K.E. et al. Novel use of a dual-zone restricted access sorbent: normalphase solid-phase extraction separation of methyl oleate from polynuclear aromatic

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 172/174

Using Mass Spectrometry for Drug Metabolism Studies

172

35.

36.

37.

38.

39.

40.

41.

42.

43.

44.

45.

46.

47.

48. 49.

hydrocarbons stemming from semi-permeable membrane devices, J. Chromatogr., A, 883(1–2), 143, 2000. Simon, V.A., Thiam, M.D., and Lipford, L.C., Determination of serum levels of thirteen human immunodeficiency virus-suppressing drugs by high-performance liquid chromatography, J. Chromatogr., A, 913(1–2), 447, 2001. Doerge, D.R., Churchwell, M.I., and Delclos, K.B., On-line sample preparation using restricted-access media in the analysis of the soy isoflavones, genistein and daidzein, in rat serum using liquid chromatography electrospray mass spectrometry, Rapid Commun. Mass Spectrom., 14(8), 673, 2000. Hsieh, Y. et al. Direct analysis of plasma samples for drug discovery compounds using mixed-function column liquid chromatography tandem mass spectrometry, Rapid Commun. Mass Spectrom., 14(15), 1384, 2000. Hsieh, Y. et al. Direct simultaneous analysis of plasma samples for a drug discovery compound and its hydroxyl metabolite using mixed-function column liquid chromatography–tandem mass spectrometry, Analyst, 126(12), 2139, 2001. Hsieh, Y. et al. Direct simultaneous determination of drug discovery compounds in monkey plasma using mixed-function column liquid chromatography/tandem mass spectrometry, J. Pharm. Biomed. Anal., 27(1–2), 285, 2002. Hsieh, Y. et al. Direct cocktail analysis of drug discovery compounds in pooled plasma samples using liquid chromatography–tandem mass spectrometry, J. Chromatogr., B: Analyt. Technol. Biomed. Life Sci., 767(2), 353, 2002. Chiap, P. et al. Use of a novel cation-exchange restricted-access material for automated sample clean-up prior to the determination of basic drugs in plasma by liquid chromatography, J. Chromatogr., A, 975(1), 145, 2002. van der Hoeven, R.A. et al. Liquid chromatography-mass spectrometry with on-line solid-phase extraction by a restricted-access C18 precolumn for direct plasma and urine injection, J. Chromatogr., A, 762(1–2), 193, 1997. Keski-Hynnila, H. et al. Quantitation of entacapone glucuronide in rat plasma by on-line coupled restricted access media column and liquid chromatography– tandem mass spectrometry, J. Chromatogr., B: Biomed. Sci. Appl., 759(2), 227, 2001. Umemura, T. et al. Direct injection determination of theophylline and caffeine in blood serum by high-performance liquid chromatography using an ODS column coated with a zwitterionic bile acid derivative, Analyst, 123(8), 1767, 1998. Shirota, O. et al. Low concentration drug analysis by semi-microcolumn liquid chromatography with a polymer-coated mixed-function precolumn, J. Microcol., Sep 7, 29, 1995. Kanda, T. et al. Synthesis and characterization of polymer-coated mixed-functional stationary phases with several different hydrophobic groups for direct analysis of biological samples by liquid chromatography, J. Chromatogr., A, 722(1–2), 115, 1996. Jemal, M. and Xia, Y.Q., The need for adequate chromatographic separation in the quantitative determination of drugs in biological samples by high performance liquid chromatography with tandem mass spectrometry, Rapid Commun. Mass Spectrom., 13(2), 97, 1999. Bhardwaj, S. and Day, R.A., Trifluoroethanol removes bound proteins from reversed-phase columns, LC–GC, 17, 354, 1999. Wu, J.T. et al. Direct plasma sample injection in multiple-component LC–MS–MS assays for high-throughput pharmacokinetic screening, Anal. Chem., 72(1), 61, 2000.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 173/174

Direct Plasma Analysis Systems

173

50. White, R.E. and Manitpisitkul, P., Pharmacokinetic theory of cassette dosing in drug discovery screening, Drug Metab. Dispos., 29(7), 957, 2001. 51. Kollroser, M. and Schober, C., Direct-injection high performance liquid chromatography ion trap mass spectrometry for the quantitative determination of olanzapine, clozapine and N-desmethylclozapine in human plasma, Rapid Commun. Mass Spectrom., 16(13), 1266, 2002. 52. Bayliss, M.K. et al. Parallel ultra-high flow rate liquid chromatography with mass spectrometric detection using a multiplex electrospray source for direct, sensitive determination of pharmaceuticals in plasma at extremely high throughput, Rapid Commun. Mass Spectrom., 14(21), 2039, 2000. 53. Jemal, M. et al. The use of high-flow high performance liquid chromatography coupled with positive and negative ion electrospray tandem mass spectrometry for quantitative bioanalysis via direct injection of the plasma/serum samples, Rapid Commun. Mass Spectrom., 12(19), 1389, 1998. 54. Jemal, M. et al. Direct injection versus liquid–liquid extraction for plasma sample analysis by high performance liquid chromatography with tandem mass spectrometry, Rapid Commun. Mass Spectrom., 13(21), 2125, 1999. 55. Zeng, H., Wu, J.T., and Unger, S.E., The investigation and the use of high flow column-switching LC/MS/MS as a high-throughput approach for direct plasma sample analysis of single and multiple components in pharmacokinetic studies, J. Pharm. Biomed. Anal., 27(6), 967, 2002. 56. Xia, Y.Q. et al. Ternary-column system for high-throughput direct-injection bioanalysis by liquid chromatography/tandem mass spectrometry, Rapid Commun. Mass Spectrom., 14(2), 105, 2000. 57. Kollroser, M. and Schober, C., Simultaneous determination of seven tricyclic antidepressant drugs in human plasma by direct-injection HPLC–APCI–MS–MS with an ion trap detector, Ther. Drug Monit., 24(4), 537, 2002. 58. Ayrton, J. et al. The use of turbulent flow chromatography/mass spectrometry for the rapid, direct analysis of a novel pharmaceutical compound in plasma, Rapid Commun. Mass Spectrom., 11(18), 1953, 1997. 59. Tanaka, N. and Kobayashi, H., Monolithic columns for liquid chromatography, Anal. Bioanal. Chem., 376(3), 298, 2003. 60. Majors, R.E., New developments in the application of monolithic HPLC columns, LC–GC, 12, 1186, 2001. 61. Tanaka, N. et al. Monolithic LC columns, Anal. Chem., 73(15), 420A, 2001. 62. Wu, J.T. et al. High-speed liquid chromatography/tandem mass spectrometry using a monolithic column for high-throughput bioanalysis, Rapid Commun. Mass Spectrom., 15(13), 1113, 2001. 63. Bidlingmaier, B., Unger, K.K., and von Doehren, N., Comparative study on the column performance of microparticulate 5-m C18-bonded and monolithic C18bonded reversed-phase columns in high-performance liquid chromatography, J. Chromatogr., A, 832(1–2), 11, 1999. 64. Zeng, H., Deng, Y., and Wu, J.T., Fast analysis using monolithic columns coupled with high-flow on-line extraction and electrospray mass spectrometric detection for the direct and simultaneous quantitation of multiple components in plasma, J. Chromatogr., B: Anal. Technol. Biomed. Life Sci., 788(2), 331, 2003. 65. Plumb, R. et al. Direct analysis of pharmaceutical compounds in human plasma with chromatographic resolution using an alkyl-bonded silica rod column, Rapid Commun. Mass Spectrom., 15(12), 986, 2001.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-05.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 174/174

174

Using Mass Spectrometry for Drug Metabolism Studies

66. Hsieh, Y. et al. Direct plasma analysis of drug compounds using monolithic column liquid chromatography and tandem mass spectrometry, Anal. Chem., 75(8), 1812, 2003. 67. Peng, S.X., Strojnowski, M.J., and Bornes, D.M., Direct determination of stability of protease inhibitors in plasma by HPLC with automated column-switching, J. Pharm. Biomed. Anal., 19(3–4), 343, 1999. 68. Wang, G. and Hsieh, Y., Utilization of direct HPLC–MS–MS for drug stability measurement, Am. Laboratory, 34(24), 24, 2002. 69. Wang, G. et al. Semi-automated determination of plasma stability of drug discovery compounds using liquid chromatography–tandem mass spectrometry, J. Chromatogr., B: Anal. Technol. Biomed. Life Sci., 780(2), 451, 2002. 70. Wang, G. et al. High-throughput cassette assay for drug stability measurementin plasma using direct HPLC–MS/MS, Spectroscopy-An Int. J., 17, 511, 2003. 71. Matuszewski, B.K., Constanzer, M.L., and Chavez-Eng, C.M., Matrix effect in quantitative LC/MS/MS analyses of biological fluids: a method for determination of finasteride in human plasma at picogram per milliliter concentrations, Anal. Chem., 70(5), 882, 1998. 72. Mei, H. et al. Comparison of matrix effects on different tandem mass spectrometers, Proceedings of the 49th American Society for Mass Spectrometry Conference, Chicago, IL, 2001. 73. Mei, H. et al. Investigation of matrix effects in bioanalytical high-performance liquid chromatography/tandem mass spectrometric assays: application to drug discovery, Rapid Commun. Mass Spectrom., 17(1), 97, 2003. 74. King, R. et al. Mechanistic investigation of ionization suppression in electrospray ionization, J. Am. Soc. Mass Spectrom., 11(11), 942, 2000. 75. Hsieh, Y., Merkle, K., and Wang, G., Zirconia-based column high performance liquid chromatography/atmospheric pressure photoionization tandem mass spectrometric analyses of drug molecules in rat plasma, Rapid Commun. Mass Spectrom., 17, 1775, 2003. 76. Matuszewski, B.K., Constanzer, M.L., and Chavez-Eng, C.M., Strategies for the assessment of matrix effect in quantitative bioanalytical methods based on HPLC– MS/MS, Anal. Chem., 75(13), 3019, 2003.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 175/202

Chapter 6 Acyl Glucuronides: Assays and Issues Sam Wainhaus

6.1

Introduction

The analysis of acyl glucuronide conjugates formed by the glucuronidation of endogenous substrates and xenobiotics has been a subject of rapidly growing interest due to the potential toxicological implications of these special metabolites [1–6]. Historically, the analysis of acyl glucuronide conjugates has been performed using HPLC separation combined with UV or fluorescence detection [3, 7–9]. Nuclear magnetic resonance (NMR) has also been utilized to better characterize acyl glucuronides [9–11]. HPLC combined with mass spectrometric detection (HPLC–MS and HPLC–MS/MS) has provided researchers with a powerful tool to study acyl glucuronide formation, distribution, and elimination that is both complementary and supplementary to other modes of detection. In order to achieve a thorough study of a particular acyl glucuronide, one will most probably utilize all of these analytical techniques. This chapter will touch on many of these techniques, but the application of mass spectrometry for the analysis of acyl glucuronide conjugates will be the primary focus. Acyl glucuronide conjugates are typically formed from nonsteroidal antiinflammatory drugs (NSAIDS). There are at least 35 reported acyl glucuronide forming acidic drugs that have been widely used, including ibuprofen (AdvilÕ ), ketoprofen (OrudisÕ ), celecoxib (CelebrexÕ ), and 0-8493-1963-3/05/$0.00+$1.50 ß 2005 by CRC Press

Copyright © 2005 CRC Press, LLC

175

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 176/202

Using Mass Spectrometry for Drug Metabolism Studies

176

naproxen (NaprosynlÕ ). However, seven of these drugs have been removed from the market due to serious toxicities including anaphylaxis, rash, jaundice, liver failure, and death. These seven drugs are alclofenac, indoprofen, zomepirac, benoxaprofen, suprofen, ibufenac, and ticrynafen. Additionally, diclofenac (VoltarenlÕ ) has been associated with fatal autoimmune hepatitis [12, 13]. The toxicity is idiosyncratic and therefore difficult to assess in preclinical and clinical testing [14]. There has been considerable effort to establish specific biomarkers in early drug discovery that are predictive of potential acyl glucuronide mediated toxicity. Mass spectrometry and specifically liquid chromatography–mass spectrometry/mass spectrometry (LC–MS/ MS) plays a crucial role in the measurement of these important parameters.

6.2

Acyl Glucuronide Formation

Acyl glucuronide metabolites are formed by the conjugation of the carboxylic acid moiety of a drug or metabolite with glucuronic acid. Glucuronidation is a major metabolic pathway for detoxifying and eliminating xenobiotics, including a wide range of hypolipidemic and NSAIDs in mammals. Acyl glucuronides contain an ester group that is susceptible to both hydrolysis and intramolecular acyl migration. Hydrolysis of an acyl glucuronide conjugate converts it to the aglycone which may be the parent drug in the case of a parent drug containing a carboxylic acid moiety, or an oxidative metabolite. Celecoxib (CelebrexÕ ), for example, undergoes oxidation of its methyl group to an alcohol and subsequent oxidation to a carboxylic acid that forms an acyl glucuronide conjugate as confirmed by LC–MS/MS [15]. Acyl migration involves transfer of the acyl group from the 1b position to the C-2, C-3, or C-4 position of the glucuronic acid ring and has been observed for a variety of NSAIDs [1, 2, 11, 16, 17]. Additionally, a,b-anomers of the aforementioned isomeric acyl glucuronides can be formed by mutarotation [6]. Figure 6.1 shows the formation of b-1-O-acyl glucuronide from the conjugation of uridine diphospho-glucuronic acid (UDPGA) with a carboxylic acid containing drug substrate that is enzymatically catalyzed by uridine glucuronosyltransferase (UGT). These isomeric acyl glucuronides have been shown to form covalent adducts with proteins as shown in Figure 6.1. This presents a toxicological problem since there are many examples of highly reactive acyl glucuronides that result in modified proteins which may be immunogenic in vivo and in vitro [1–6]. Clearly, the extent of protein binding depends on several factors that require measurement in order to assess the likelihood of an immunotoxic response. 6.2.1

Mechanism of glucuronidation

Several mechanisms of acyl glucuronide reactivity have been proposed. The transacylation mechanism proposed by van Breemen and Fenselau results in covalent binding of the drug (without the glucuronic acid) and protein via NH2, SH or nucleophillic displacement of the glucuronosyl group by Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 177/202

Acyl Glucuronides: Assays and Issues

177

Figure 6.1 Glucuronidation is one of the major phase II metabolic pathways of carboxylic acid compounds. Once formed, aycl glucuronides may undergo acyl migration/anomerization around the sugar ring. These isomers can form aldehydes that may covalently bind to proteins and trigger immunotoxic reaction such as anaphylaxis. Source: White, R.A., SPRI (personal communication). With permission.

OH groups on the protein molecule [19–22]. The glycation or imine mechanism requires a spontaneous initial acyl migration step as described above, followed by tautomerization of the pyranose ring to its aldose form. Condensation of the aldehyde group on the ring opened tautomer can then bind irreversibly to a protein as shown in Figure 6.1. In this case, both the drug and glucuronic acid are bound to the protein. Both of these mechanisms have been observed and are both probably important in terms of toxicological consequences [2, 23–27]. Benet et al. have shown how the utilization of tandem mass spectrometry (MS/MS) can be very helpful in this endeavor [23–25]. Benet et al. used tandem liquid secondary ion mass spectrometry to show glucuronyl-imine linkages at six lysine residues formed from in vitro studies of tolmetin glucuronide and human serum albumin, as shown in Figure 6.2, thereby providing conclusive evidence for the glycation mechanism [23]. Benet et al. also used matrix assisted laser desorption mass spectrometry (MALDIMS) to investigate the protein binding of benoxaprofen glucuronide. The added sensitivity from MALDI techniques permitted differentiation of binding sites on human serum albumin modified by the drug alone and binding sites modified by the benoxaprofen glucuronide as shown in Figure 6.3. Additionally, different binding sites were observed for tolmetin glucuronide Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 178/202

Using Mass Spectrometry for Drug Metabolism Studies

178

Figure 6.2 Liquid secondary ion mass spectrometry CID spectrum for the molecular ion of m/z 1365.6 from an HPLC fraction of a tryptic digest following the incubation of tolmetin glucuronide with human serum albumin. Fragments containing Lys-199 (Lys*) show a shift of 417 Da for tolmetin glucuronide, indicating that this lysine is the site of covalent binding. y7
y6 ¼ m/z 545 corresponding to lysine-H2O þ tolmetin glucuronide (m/z 417). Starred items in the spectrum (m/z 240, 212, 122, 119, and 94) indicate fragments from the tolmetin moiety. (Source: Ding, A., Proc. Natl. Acad. Sci. USA, 90, 3797, 1993. With permission.)

and benoxaprofen glucuronide which could potentially explain immunological variation observed with several NSAIDs [24]. The identification of such binding sites in vivo will require even greater sensitivity. Both mechanisms provide a variety of parameters that may be measured in the drug discovery and development process to assess the potential for a negative toxicological finding in humans as illustrated in Figure 6.4: (1) The amount of acyl glucuronide or extent of glucuronidation can be measured in bile, urine and plasma; (2) the extent of acyl migration, which is a critical step in the glycation mechanism, can be measured in these matrices; and (3) the amount of protein binding, clearly the most critical measurement, can be measured in plasma and tissue. 6.2.2

Assessing acyl glucuronide toxicity

To date, there have been several approaches used to assess the toxic nature of acyl glucuronide conjugates. One approach measures the reactivity of the Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 179/202

Acyl Glucuronides: Assays and Issues

179

Figure 6.3 (a) MALDI-high energy CID spectrum of a tryptic peptide of HSA showing Lys-199 modified by benoxaprofen glucuronide via an imine-based mechanism. K* is benoxaprofen glucuronide modified lysine with retention of the glucuronic acid moiety (m/z 459). y7
y6 ¼ m/z 587 ¼ Lys
H2O
m/z 459. (b) MALDI-high energy CID spectrum of a tryptic peptide of HSA showing Lys-199 modified by benoxaprofen glucuronide via a nucleophillic displacement mechanism. K* is modified lysine with benoxaprofen (m/z 283) directly attached (y7
y6 ¼ m/z 411 ¼ Lys
H2O þ m/z 283). (Source: Qiu, Y., Drug Metab. Dispos., 26, 246, 1998. With permission.)

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 180/202

180

Using Mass Spectrometry for Drug Metabolism Studies

Figure 6.4 Acyl glucuronide is formed in the liver and either excreted via the bile duct or systemic circulation. While in the liver it can covalently bind to liver protein resulting in hepatotoxicity. In the blood it can covalently bind to plasma protein resulting in an immunotoxic response or cleared renally. (Source: White, R.A., SPRI (personal communication). With permission.)

acyl glucuronide towards acyl migration. This approach requires separation and identification of the positional isomers that can be a time consuming task requiring careful manipulation of mobile phase pH, buffer content, organic content, flow rate, and temperature [28]. Figure 6.5(A) shows the separation of the acyl glucuronides of zomepirac [29]. Identification of each of these isomers is an arduous task that is not always necessary. Identification of the 1-O-acyl glucuronide can be achieved by treating the acyl glucuronide mixture with b-glucuronidase thus hydrolyzing only the 1-O-acyl glucuronide as shown in Figure 6.5(B). The extent of degradation is measured by incubation of the 1bO-acyl glucuronide in buffer at physiological pH and measuring the rate of hydrolysis and acyl migration. Using this method it was possible to measure degradation half-lives of the acyl glucuronide conjugates of telmisartan and diclofenac as 26 and 0.5 h, respectively at pH 7.4 [18]. As stated above, diclofenac has been shown to cause clinically adverse reactions while telmisartan is free of such findings. The degradation half-lives for a variety of acyl glucuronide forming drugs have been measured [18]. While some correlation does seem to exist between half-life and potential toxicity there is much conflicting data. Additionally, there is some variation in the absolute numbers of the acyl glucuronide half-lives. For example, the half-life of zomepirac acyl glucuronide was measured to be 9 min [30] and 27 min [6]. The Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 181/202

Acyl Glucuronides: Assays and Issues

181

Figure 6.5 LC–MS/MS chromatogram of the acyl glucuronide isomers of zomepirac following (1) drug incubation with microsomes or HSA, (2) hydrolysis with b-glucuronidase (only 1-O-acyl glucuronide has been hydrolyzed to the aglycone.), (3) alkaline hydrolysis of the remaining acyl glucuronide isomers. (Source: Bolze, S. et al. Drug Metab. Dispos., 30, 404, 2002. With permission.)

half-life of ibuprofen acyl glucuronide was measured to be 54 min [30] and 3.3 h [31]. Zomepirac was withdrawn from the market due to anaphylaxis while no such findings have been observed for ibuprofen. Thus, there may be some relationship between degradation half-life and toxicity, but there are many exceptions. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 182/202

Using Mass Spectrometry for Drug Metabolism Studies

182

Another approach compares the amount of in vitro binding of acyl glucuronide conjugates to human serum albumin (HSA) as described above. Bolze et al. developed a novel technique whereby the acyl glucuronide is produced in vitro and used to assess the extent of protein binding via LC–MS/ MS [29]. LC–MS/MS is used to determine the amount of parent drug after the corresponding acyl glucuronide that was bound to the HSA has been hydrolyzed. This will be described in greater detail below. A correlation between the extent of covalent binding and observed toxicity for a variety of NSAIDs was observed. For example, Tolmetin, diclofenac, and zomepirac all showed greater extent of covalent binding compared to ibuprofen and furosemide. Tolmetin-1-O-acyl glucuronide has a degradation half-life of 0.26 h [6] and has been withdrawn from the market while furosemide-1-O-acyl glucuronide has a half-life of 5.3 h without any negative findings. Clearly, there appears to be a correlation between degradation half-life, HSA covalent binding and immunotoxic response. Unfortunately, even careful measurement of these parameters may not be sufficient to predict the likelihood of a negative toxicological response and additional antibody measurements may be required. However, these do provide a risk assessment starting point to determine rank ordering of lead candidates, the need to investigate replacement of the carboxylic acid group with one that has similar SAR such as an isostere surrogate and comparison with similar parameters from drugs with known toxicological findings.

6.3

Mass Spectrometry Overview

Mass Spectrometry plays a key role in determining all of the acyl glucuronide parameters described above. The ability to measure acyl glucuronide levels in a variety of matrices was historically performed by HPLC–UV and is now routinely carried out using LC–MS/MS. There are a variety of methodologies that can be used to quantify acyl glucuronide formation, assess the extent of acyl migration and protein adduct formation. While much work has been done with well established drugs and drugs that are at a mature stage in their development, there is a great need to better characterize drug candidates that are in early to late stage drug discovery. The ability to predict the toxicity potential of a given acyl glucuronide hinges on the ability to measure these biomarkers with the sensitivity and selectivity that is provided by LC–MS/MS. 6.3.1

Acyl glucuronide identification

The use of liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS) has been critical in identifying potentially toxic metabolites such as acyl glucuronide conjugates in vivo in early drug discovery. Mass spectrometry has been extensively utilized to assist in acyl glucuronide identification even when another analytical technique is used for quantitation. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 183/202

Acyl Glucuronides: Assays and Issues

183

Figure 6.6 Collision-induced dissociation (CID) mass spectrum of the electrospray generated [M
H]
ion peak from Targretin acyl glucuronide. The precursor ion was m/z 523 and the product ions formed were m/z 347, [M
H
176]
(Targretin aglycone), m/z 303 [M
H
176
44]
(additional loss of CO2). (Source: Shirley, M.A. et al. Drug Metab. Dispos., 25, 1144, 1997. With permission.)

The presence of a glucuronide can be demonstrated with either neutral loss of m/z 176, observation of an [M þ H þ 176]þ peak in the mass spectrum as shown in Figure 6.6, or by simply adding m/z 176 to the parent transition and monitoring for both the parent and product transitions. For example, if the parent compound has an isotopic molecular weight of m/z 500 ([M þ H]þ is m/z 501) and the product ion is m/z 300, the transitions m/z 677 to 501 and m/z 677 to 300 would be monitored. If an acyl glucuronide is present, then one of these transitions should pick it up as shown in Figure 6.7. The mere presence of a glucuronide adduct peak is not sufficient evidence for the presence of an acyl glucuronide. This peak could very well be due to a phenolic glucuronide where the hydroxyl group of the parent molecule or metabolite is glucuronidated. Alternatively, this peak could result from an N-glucuronide. A novel technique to distinguish regioisomeric glucuronides by LC–MS/MS was developed by Prakash and Soliman [32]. They dissociate the glucuronides at the mass spectrometer orifice and analyze the resulting aglycones by MS/MS. All of the glucuronides will result in a peak for neutral loss of m/z 176 and a peak in the mass chromatogram for selected reaction monitoring (SRM). A method to differentiate an acyl glucuronide from a phenolic glucuronide is hydrolysis of the ester via basification. A 100 mM solution of sodium hydroxide will completely hydrolyze an acyl glucuronide, including all positional isomers, to the corresponding aglycone leaving the phenolic glucuronide intact. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 184/202

184

Using Mass Spectrometry for Drug Metabolism Studies

Figure 6.7 Selected reaction monitoring (SRM) for compound X and compound X-AG with LC–MS/MS. Two acyl glucuronide ion chromatograms are monitored. The first corresponds to loss of m/z 176 and subsequent loss of m/z 211 to yield the same product ion as for the aglycone. The second chromatogram monitors loss of m/z 176 resulting in the aglycone. This is an example of an effective screening procedure for NSAIDs.

b-glucuronidase has also been used to hydrolyze glucuronides. Zhao et al. used b-glucuronidase to completely hydrolyze an acyl glucuronide and hydroxyl glucuronide to their corresponding aglycones [33]. Shirley et al. were able to identify several glucuronides of rexinoid by combining GC–MS, LC/MS, MS/MS and isotope cluster techniques [34]. Generally, a 1:1 (v/v) ratio of base to matrix is sufficient to hydrolyze the acyl glucuronide. Figure 6.8 shows the analysis of an acidified bile sample and a bile sample that has been basified. The acyl glucuronide peak is clearly visible in both the acyl glucuronide and the parent transition in the acidified bile sample. The acyl glucuronide transition corresponds to [M þ H þ 176]þ collisionally activated to m/z 265, the same product ion monitored for the parent compound transition. The acyl glucuronide mass chromatogram contains one peak, but, this may correspond to multiple co-eluting acyl glucuronide isomers and even phenolic and N-glucuronides. Upon basification the entire acyl glucuronide peak disappears and the parent peak dramatically increases. This example serves to illustrate several key points. The glucuronide conjugate observed in bile is clearly an acyl glucuronide since complete hydrolysis appears to occur. Since the increase in peak area for the parent compound peak is nearly ten-fold greater than the peak area of the acyl glucuronide peak, this implies that the electrospray ionization cross section of the parent compound is ten-fold greater Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 185/202

Acyl Glucuronides: Assays and Issues

185

Figure 6.8 Comparison of LC–MS/MS chromatograms of an acyl glucuronide in acid stabilized bile followed by base hydrolysis. There is some in-source fragmentation of the acyl glucuronide in the acid stabilized bile that results in a peak at an earlier retention time in the aglycone ion chromatogram. Following base hydrolysis the acyl glucuronide peak disappears with a corresponding increase in aglycone peak area.

than the acyl glucuronide. Therefore, no attempt should be made to glean any quantitative information from the relative peak areas of acyl glucuronides to parent compound peaks. It would be useful to build up a database of relative ionization cross sections for acyl glucuronides and their aglycones. In this way a trend may be observed so that a correction factor may be inserted to rapidly screen acyl glucuronide concentrations. It should be noted that the lack of an [M þ H þ 176]þ peak does not rule out the presence of an in vivo acyl glucuronide that is highly unstable relative to the aglycone ex vivo. Therefore, great care must be taken during the sample collection and analysis of these samples. This issue will be discussed in more detail in the following sections. 6.3.2

Acyl glucuronide quantitation

Quantitation of these metabolites requires an authentic analytical standard that may not be readily available at the early drug discovery stage. The use of an isotopic label such as 3H or 14C on the drug candidate can greatly assist in accurately assessing metabolite levels by radioactivity, unfortunately, the radiolabelled version of a drug is usually not available in early drug discovery. In order to prevent spending resources on drug candidates with severe metabolic liabilities, it is imperative to have some quantitative information on potentially toxic metabolites. Comparison of the acyl glucuronide peak area with that of a known concentration of parent drug to provide a rough estimate of the amount of acyl glucuronide present in a given biological matrix, although tempting, can provide values that are not at all reflective of the true Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 186/202

Using Mass Spectrometry for Drug Metabolism Studies

186

acyl glucuronide concentration. Several quantitation techniques will be described below, but we must first examine how the acyl glucuronide conjugate is affected by the ionization process. 6.3.3

APCI vs ESI

Acyl glucuronide conjugates are inherently unstable and easily hydrolyzed to both the aglycone and rearrangement isomers. Therefore, it is crucial to use the least severe conditions when analyzing the sample. The choice of ion source for a given mass spectrometric determination can be based on a variety of parameters. In the case of acyl glucuronides the most important parameter is analyte stability. Under the more severe atmospheric pressure chemical ionization (APCI) conditions, acyl glucuronides can break down to the aglycone resulting in an underestimate of the acyl glucuronide concentration. If chromatographic separation between the acyl glucuronide and aglycone is not achieved this can also lead to an overestimate of the aglycone concentration. Figure 6.9 shows the analysis of an acyl glucuronide under both APCI and electrospray ionization (ESI) conditions. The acyl glucuronide and aglycone have been chromatographically resolved here, but this cannot always be assumed to be the case a priori. APCI typically results in much greater in-source fragmentation of the acyl glucuronide compared to ESI. Additionally, the mass spectrometer response may be much greater for the aglycone

Figure 6.9 Comparison of electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) for the analysis of compounds that result in acyl glucuronide metabolites. APCI is a harsher ionization technique and can easily result in significant cleavage of the ester, leading to a large peak in the aglycone ion chromatogram. If chromatographic separation is not achieved, APCI could lead to an overestimate of the aglycone concentration. ESI is a softer ionization technique resulting in substantially less in-source fragmentation. Hence ESI is the preferred ionization technique for compounds that form glucuronide metabolites.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 187/202

Acyl Glucuronides: Assays and Issues

187

than for the acyl glucuronide so that only a small amount of decomposition may lead to a large peak area for the aglycone. Therefore, it is imperative to minimize such in-source fragmentation as much as possible by the use of ESI and by making every effort to achieve chromatographic separation of the acyl glucuronide and its aglycone. 6.3.4

Sample handling

The ease of acyl glucuronide hydrolysis makes careful sample handling crucial in order to preserve the in vivo state of the acyl glucuronide. If the acyl glucuronide undergoes hydrolysis ex vivo, the concentration values can be grossly underestimated and the aglycone concentration overestimated and extent of rearrangement overestimated. It is possible to slow down hydrolysis and acyl migration by the following steps: cooling the sample on ice immediately after collection, adjusting the pH to approximately 3 with 100 mM phosphoric acid, storing the samples at or below
20 C and performing the analysis as quickly as possible [28, 35]. Figure 6.10 shows a radiochromatogram of a bile sample collected after dosing with a noncarboxylic acid containing drug. The most intense peak in the radiochromatogram corresponds to a carboxylic acid metabolite and two smaller peaks correspond to an acyl glucuronide as determined by LC–MS/MS. When this same bile sample is collected and immediately acidified, the radiochromatogram shown in Figure 6.11 was obtained; the acyl glucuronide peak has increased by 400% and can be reduced to its original size by base hydrolysis [36]. Alternatively, the extent of acyl migration can be overestimated if proper sample handling is not carried out. This scenario is shown in Figure 6.12 for a bile sample collected following oral administration of a drug known to form

Figure 6.10 Radiochromatogram of a bile sample of a drug that undergoes oxidative metabolism to form a carboxylic acid metabolite which can then form an acyl glucuronide. Two small acyl glucuronide peaks are visible. Since bile is slightly basic there is cause for concern about the stability of the acyl glucuronide. (Source: Rindgen, D. et al. Am. Pharm. Rev., 4, 52, 2001. With permission.)

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 188/202

188

Using Mass Spectrometry for Drug Metabolism Studies

Figure 6.11 Radiochromatogram of acidified and base treated bile sample. The acid stabilized bile sample shows that the acyl glucuronide concentration is much larger than Figure 6.10 seems to indicate. Figure 6.10 can be regenerated by base hydrolysis. Source: Rindgen, D. et al. Am. Pharm. Rev., 4, 52, 2001. With permission.)

Figure 6.12 HPLC chromatograms of an untreated bile sample that was stored at
30 C for 3 months and an acid stabilized bile sample that was analyzed within 3 days of collection. A1 and A2 fractions were analyzed by LC–MS/MS and found to contain an acyl glucuronide. A1 is 1-O-acyl glucuronide while A2 is 2-O-acyl glucuronide as determined by NMR. The acyl glucuronide in the untreated old bile sample has undergone extensive acyl migration while the acid stabilized sample preserves the in vivo form of the acyl glucuronide.

an acyl glucuronide metabolite. When no special handling precautions were taken and the samples stored for 3 months the major peak observed in the UV chromatogram was A2. This peak was identified as an acyl glucuronide by LC– MS/MS, but since an authentic standard was not available the distinction Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 189/202

Acyl Glucuronides: Assays and Issues

189

between a 1-b-O-acyl glucuronide and one of its rearrangement isomers had to be made by NMR. A2 was identified as 2-b-O-acyl glucuronide and A1 was 1-b-O-acyl glucuronide. Clearly, this observation raises a red flag in the progression of a drug since a rearranged acyl glucuronide that is potentially capable of protein binding seemed to be the major metabolite. A more careful experiment showed this to not be the case. When bile was collected under the careful sample handling conditions described above and analyzed within 3 days of collection, the situation was reversed. NMR showed that the major metabolite was now A1, the 1-b-O-acyl glucuronide. Although protein binding via the transacylation mechanism is still possible this newer finding nevertheless implied a reduced risk. Acyl glucuronides that have undergone acyl migration can still be hydrolyzed by base but not by b-glucuronidase. This provides a potential technique for differentiating between the two isomers. Additionally, glucuronide conjugates of phenols and amines are possible, but these are stable with respect to base hydrolysis thus allowing for distinction between acyl glucuronides and phenolic or N-glucuronides as described above.

6.3.5

Difference assay

One of the simplest quantitative approaches when an authentic acyl glucuronide standard is not available is the difference method [29, 37]. This technique takes advantage of the base hydrolysis described above to convert all the acyl glucuronide to aglycone followed by quantitation of the aglycone. The difference between the original (acid stabilized) and hydrolysis aglycone concentration corresponds to the acyl glucuronide concentration. The technique is carried out as follows: two rats and monkeys are orally dosed with 10 mg/kg of the acyl glucuronide-forming drug. Blood is collected at 0.25, 0.5, 1, 2, 4, 6, 8, 24, 48, and 72 h post-dose. Bile is collected at 0–2, 2–4, 4–6, 6–8, 8–24, 24–48, and 48–72 h intervals. The plasma and bile collected is acidified with 100 mM H3PO4 (2:1, v/v) at each time point immediately following sample collection in order to stabilize the acyl glucuronide and stored at
20 C. Another portion of bile and plasma is basified with 100 mM NaOH (2:1, v/v) prior to analysis in order to hydrolyze the acyl glucuronide to the aglycone. Standard curves of the drug are prepared in bile and plasma for each species. Separate curves are prepared for the acidified and basified samples since this can impact ionization. The concentration of aglycone is quantified in all of the samples. The difference in molar concentration between the acidified and basified samples corresponds to the molar concentration of the acyl glucuronide at each time interval. In order to calculate the percent of dose converted to acyl glucuonide, the molar concentration of acyl glucuronide is multiplied by the bile volume to give the number of micromoles of acyl glucuronide for each time interval. The dose multiplied by the animal weight gives the mass of parent compound administered to the animal. This value is then converted to micromoles via the Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 190/202

Using Mass Spectrometry for Drug Metabolism Studies

190

molar mass. The percent of dose converted to acyl glucuronide at each time interval is simply micromoles of acyl glucuronide divided by micromoles of parent compound multiplied by 100%. The percent of dose converted to acyl glucuronide and plasma concentration of acyl glucuronide measured by this method can be substantiated by dosing two rats and cynomologus monkeys with 10 mg/kg of radiolabeled drug. Bile and plasma are collected in a similar manner as mentioned above. Both bile and plasma are counted for radioactivity and bile monitored for metabolites by splitting the flow from the LC between a radio-flow detector and the mass spectrometer. Additionally, the plasma parent concentration is determined by LC–MS/MS and compared with the total radioactivity. The amount of radioactivity recovered in bile and the relative peak area of acyl glucuronide in the radiochromatogram allows the determination of percent of dose converted to acyl glucuronide. The acyl glucuronide concentration in bile following a 10 mg/kg oral dose of compound X is shown in Table 6.1 for rat and monkey. The mean acyl glucuronide concentration of compound X-AG in monkey bile is three to twelve-fold that of rat bile for a given time interval (0–24 h) and is at least several hundred micromolar through 24 h post-dose. The mean ratio of compound X to compound X-AG in monkey bile is only 0.03 (0–24 h) while this value is 1.7 in rat (0–24 h). Additionally, the concentration of compound X in rat bile is one- to twenty six-fold that of monkey bile for a given time interval (0–24 h). We did not observe any compound X-AG in rat or monkey plasma with this assay. This assay provided several important pieces of information about compound X and its propensity to form acyl glucuronide conjugates in rat and monkey several months prior to the availability of radiolabeled compound X. It is useful to convert this data to percent of dose converted to acyl glucuronide by using the bile volume at each time point and the animal weights. Table 6.1 shows the percent of dose converted to acyl glucuronide as measured in rat and cynomologus monkey. The sums of the mean values over 72 h are 38% and 17% for monkey and rat, respectively. The mean

Table 6.1 Rat monkey acyl glucuronide and aglycone bile concentrations as measured by the difference assay using LC–MS/MS. The % of dose converted to acyl glucuronide (AG) is calculated for each time interval Parameter (mean)

0–2 h 2–4 h 4–6 h 6–8 h 8–24 h 24–48 h 48–72 h Total

Monkey (mean values) Percent of dose converted to AG Bile volume (mL) Parent (mM) AG (mM)

2.2 7.7 6 377

4.8 6.9 14 723

3.9 6.5 15 680

5.1 17.2 11 662

12 56.9 20 262

9.2 108.9 13 85

1.1 126.4 0.7 9

38.3 330.5

Rat (mean) Percent of dose converted to AG Bile volume (ml) Parent (mM) AG (mM)

5 2.4 156 135

1.3 2.0 198 59

3.4 5.0 148 94

2.2 2.1 98 61

4.9 10.2 20 29

0.4 18.9 1 0.9

.05 11 0.2 0.4

17.3 51.6

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:33pm Page: 191/202

Acyl Glucuronides: Assays and Issues

191

Figure 6.13 Post-dose time course of acyl glucuronide and aglycone concentrations in monkey and rat bile as determined by the difference assay.

concentration vs time profile acyl glucuronide and parent drug in rat and monkey bile is shown in Figure 6.13. There is a two-fold difference in the percent of dose converted to acyl glucuronide for monkeys 1 and 2. Nevertheless, both monkeys plateau at approximately 24 h and both convert a large proportion of the dose to acyl glucuronide. Figure 6.14 shows the bile (pooled 0–24 h) radiochromatograms for a 10 mg/kg dose of 14C compound X in monkey and rat. The results predicted by the semi-quantitative (difference) assay are borne out in Figure 6.14. While compound X-AG is clearly the major peak in monkey bile, compound X is the major peak in rat bile. The compound X/compound X-AG ratio is 0.03 in monkey bile and 3.3 in rat bile. The percent of dose converted to acyl glucuronide based on the relative peak area of the acyl glucuronide peak in the radiochromatogram and the percent of total radioactivity recovered in bile was 58% in the monkey and 15% in the rat. These results show excellent qualitative agreement with the results from the semi-quantitative assay (see Table 6.1). Good quantitative agreement was observed in monkey for compound X/compound X-AG, while in the rat the radioactivity assay was two-fold the value obtained in the semi-quantitative assay. The percent of dose converted to acyl glucuronide showed excellent agreement for the rat (15% and 17% for the radioactive and semi-quantitative assay, respectively) and both assays showed a large percent conversion of parent compound in the monkey (58% and 38% for the radioactive and semi-quantitative assay, respectively). Figure 6.15 shows the compound X concentration and total radioactivity as a function of time, as measured by LC–MS/MS and scintillation counting, respectively, following a 1 mg/kg oral dose in monkey. These two curves are Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 192/202

192

Using Mass Spectrometry for Drug Metabolism Studies

Figure 6.14 Radiochromatogram of monkey and rat bile. A much larger fraction of the dose is converted into acyl glucuronide in monkeys than in rats. These data support earlier findings from the difference assay.

Figure 6.15 LC–MS/MS determination of 14C parent drug in plasma compared with total radioactivity converted to ng eq/mL. The data suggests that no circulating metabolites are present.

virtually indistinguishable indicating a lack of circulating metabolites. These results agree with the semi-quantitative assay for compound X-AG in plasma which showed no detectable levels of compound X-AG as stated above. Therefore, the data obtained using the semi-quantitative assay can add to the Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 193/202

Acyl Glucuronides: Assays and Issues

193

degradation half-life and HSA binding assays described above to form a more complete picture of the risk assessment involved for a given drug candidate or to rank order a series of drug candidates.

6.4

Isolation of Acyl Glucuronide

The rate-limiting step in most assays is absence of an authentic acyl glucuronide standard. We have seen that it is sometimes possible to form acyl glucuronides in vitro to such an extent that these may be utilized in a reactivity experiment [18, 29]. There are also additional techniques to prepare an acyl glucuronide in the literature [38]. We have utilized the technique of having the animal do the work of the synthetic organic chemist. In the event that the difference assay indicates that there is a large conversion of drug to acyl glucuronide as measured in bile it is possible to isolate this acyl glucuronide, by ramping up the dose and collecting bile. Two monkeys were dosed p.o. with 100 mg/kg of compound X. Bile was collected over 6 h in cold 100 mM phosphoric acid to preserve the acyl glucuronide at pH 3–4. The retention time of the acyl glucuronide was known based on previous data. This fraction was collected, purified and identified as an acyl glucuronide by LC– MS/MS. Additionally, the acyl glucuronide was further characterized as the 1-b-O-acyl glucuronide by NMR. This relatively fast ‘‘synthesis’’ opens the door to all of the assays discussed above including degradation half-life in a variety of matrices and protein binding. Additionally, if the radiolabeled drug is dosed then radiolabeled acyl glucuronide is obtained that may be used for covalent binding experiments. The extracted isolated acyl glucuronide may then be used to construct a calibration curve in a given matrix. Figure 6.16 shows an acyl glucuronide calibration curve in plasma from 25 ng/mL to 5000 ng/mL. Both the aglycone and acyl glucuronide were quantified simultaneously and the concentration versus time curve is shown in Figure 6.17. The difference assay would not be useful for the plasma since there is a large concentration of aglycone and a small concentration of acyl glucuronide. In this case, the aglycone formed by hydrolyzing the acyl glucuronide is lost in the percent error. This is also observed when the total radioactivity measured in plasma is compared with parent drug measured by LC–MS/MS. Typically, when a significant amount of metabolites are formed a significant difference between total radioactivity and parent concentration is observed. However, if a profile like that shown in Figure 6.15 is observed the conclusion is that no circulating metabolites are present. For acyl glucuronides it is important to know the percentage of circulating acyl glucuronide relative to parent. This information can be obtained from the concentration versus time curve shown in Figure 6.17 and is less than 10%. Since solutions of the acyl glucuronide deteriorate over time it is extremely difficult to obtain a validated quantitative assay for acyl glucuronides. The use of the nonvalidated quantitative procedures described above can potentially be viewed as satisfying due diligence by the FDA. For Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 194/202

194

Using Mass Spectrometry for Drug Metabolism Studies

Figure 6.16 Acyl glucuronide LC–MS/MS calibration curve in plasma. The limit of quantification (LOQ) is 10 ng/mL with a linear dynamic range of three orders of magnitude. Stock solutions and plasma standards were carefully monitored for aglycone.

Figure 6.17 Plasma concentration-time profile for parent drug and its acyl glucuronide metabolite. The acyl glucuronide is less than 10% of the aglycone and its 24-h level is less than 100 nM.

example, the metabolism and excretion of Celecoxib, an acyl glucuronide forming drug, in humans has been described in detail [15]. Because of the inherent instability of acyl glucuronides, they can easily be hydrolyzed in vivo to form the aglycone. Enterohepatic recirculation refers to Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 195/202

Acyl Glucuronides: Assays and Issues

195

biliary excretion of the acyl glucuronide and hydrolysis in the gut followed by re-absorption of the parent drug and reuptake by the liver. This can result in a pharmacokinetic profile which has a secondary increase in plasma levels as observed for valproic acid [39]. A decrease in clearance can also be observed in renal failure patients where renal clearance is the major elimination pathway of the acyl glucuronide. This ‘‘futile cycling’’ is the result of in vivo hydrolysis leading to an increase in drug concentration [40].

6.5

Monitoring Acyl Glucuronide Reactivity

When discussing the subject of acyl glucuronide reactivity it is important to differentiate between chemical stability and reactivity. Acyl glucuronide reactivity as it pertains to acyl migration and hydrolysis to the aglycone is a measure of the stability of the 1-O-b-acyl glucuronide. This is a required first step in the glycation mechanism described above. Acyl glucuronide reactivity as it pertains to the ability to form protein adducts relates directly to the chemical reactivity of the acyl glucuronide. The differentiating point is the major mechanism at play. If the transacylation mechanism is the major mechanism then the stability of the acyl glucuronide is not critical, unless of course it is very unstable relative to the aglycone. If the glycation mechanism is at work then acyl migration is a necessary but insufficient step. According to the glycation mechanism, 100% of the 1-O-b-acyl glucuronide may undergo acyl migration, but it may be highly unreactive. Since it is not known a priori which mechanism is at work the assumption is that both are important and acyl migration is a critical parameter that must be monitored. 6.5.1

Monitoring acyl migration and aglycone formation

There are a variety of methodologies that have been used to measure acyl glucuronide stability. The first question to answer when going down this road is: what matrix am I interested in? Many in vitro studies have been carried out using phosphate buffer at physiological pH and temperature. This answers the question of stability from a fundamental standpoint, but may not reflect the in vivo stability. Upon its formation in the liver, the acyl glucuronide may find itself circulating in blood, excreted in bile or urine, undergoing enterohepatic recirculation or binding to a hepatic or plasma protein as shown in Figure 6.4. The in vitro approach is very useful presuming one has sufficient quantities of a well-characterized acyl glucuronide, however, preservation of the in vivo state of the acyl glucuronide with subsequent analysis provides the definitive answer. Figure 6.18 shows the results of a 60-min incubation of zomepirac 1-O-bacyl glucuronide in human plasma as measured by LC–MS/MS [30]. Acyl migration is clearly the dominant process and aglycone formation increases slowly in a linear fashion. Based on these data, the half-life of zomepirac 1-Ob-acyl glucuronide is 9 min. The in vivo half-life of the rearranged zomepirac acyl glucuronides is probably greater than 9 min so that sufficient time exists to Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 196/202

196

Using Mass Spectrometry for Drug Metabolism Studies

Figure 6.18 Time profile of the degradation of zomepirac-1-O-acyl glucuronide. Rearrangement is the dominant degradation process. (Source: Hop, E.C.A. et al. in Proceedings of the 48th ASMS Conference on Mass Spectrometry and Allied Topics, Long Beach, CA, 2000. With permission.)

react with protein molecules. This technique has been carried out using HPLC– UV for a variety of acyl glucuronide forming drugs [6, 18]. A major disadvantage of this technique is that an authentic standard of the 1-O-b-acyl glucuronide is required. This is not always a straightforward synthesis especially in the case of a particularly unstable acyl glucuronide. An alternative assay begins with the incubation of the compound of interest in liver microsomes containing UDPGA [30]. The formation rate of the 1-O-b-acyl glucuronide may be measured by quenching the reaction with acidified acetonitrile or methanol. The degradation rate of the 1-O-b-acyl glucuronide may then be measured by quenching the reaction mixture with UDP. The halflives obtained from this method may not agree with those found above, but this allows for a rank ordering without requiring an authentic acyl glucuronide standard. An alternative approach was developed by the author for drugs which do not easily form acyl glucuronides in vitro and when an authentic acyl glucuronide standard in not available. Typically, a drug candidate in early discovery is incubated with hepatocytes or S9 from a given species and the drug and metabolites are identified after a certain incubation time. In this way, it is possible to compare the propensity of human beings to form a particular metabolite with that of a rat, dog, monkey, for example. Alternatively, it is also possible to identify human specific metabolites. The identification of these metabolites is typically made using HPLC–MS/MS. This technique is particularly useful for measuring acyl glucuronide formation and establishing a risk/benefit framework. Unfortunately, not all drugs display in vivo/in vitro correlation with regard to the amount of acyl glucuronide formed. For example, in vivo results show that 40% of compound X is glucuronidated in Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 197/202

Acyl Glucuronides: Assays and Issues

197

Figure 6.19 LC–MS/MS analysis of acyl glucuronide formation. The parent drug was incubated in rat, monkey and human liver S9 (1.5 mg/mL protein) at a concentration of 10 mM.

rat and 90% is glucuronidated in monkey. In vitro results show little interspecies difference and less than 10% glucuronidation. However, the rate of glucuronidation does show some correlation. Compound X was incubated with rat, monkey, and human S9 (1.5 mg/mL protein) at a concentration of 10 mM. The relative rate of formation was obtained by comparing the LC–MS/ MS response ratio of acyl glucuronide to internal standard at 0, 0.5, and 1 h time points as shown in Figure 6.19. Rats and humans were found to have rates of 6% and 40% respectively, compared to that of monkeys. While these data do not predict the in vivo results in an absolute sense they do suggest that humans are intermediate between rats and monkeys in their ability to form the acyl glucuronide. 6.5.2

Monitoring acyl glucuronide protein binding

The extent of protein binding is arguably the most important parameter to determine, although the question of how much and the site of modification are critical elements. A wide range of techniques has been employed to measure this important property and LC–MS/MS is coming of age in this vital determination. Benet et al. have used various mass spectrometric techniques to investigate protein binding as described above. Akira measured the protein binding of probenecid glucuronides using HPLC–UV [17]. Ware et al. used immunochemical detection to identify protein adducts of diclofenac [12]. Shipkova et al. utilized western blot analysis to investigate the formation of covalent adducts between the acyl glucuronide of mycophenolic acid and plasma albumin [41]. Olsen et al. used LC–MS/MS, UV and fluorescence to Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 198/202

198

Using Mass Spectrometry for Drug Metabolism Studies

determine the reactivity of naproxen acyl glucuronide relative to naproxen coenzyme A thioester [42]. Bolze et al. developed a novel technique to determine acyl glucuronide reactivity toward human serum albumin [29]. The acyl glucuronide forming drug is incubated in human liver microsomes to form the acyl glucuronide. The resulting mixture contains the aglycone and acyl glucuronide isomers as shown in Figure 6.5(A). Quantification of the aglycone (i) is straightforward and requires use of the sample handling and analysis conditions described above. The quantification of the acyl glucuronide isomers requires separation of the 1-b-isomer from the other isomers. b-glucuronidase is used to selectively cleave the 1-b isomer followed by quantification of the aglycone (ii) as shown in Figure 6.5(B). Following this, the remaining acyl glucuronide isomers are quantified via base hydrolysis and subsequent quantitation of the released aglycone (iii) as shown in Figure 6.5(C). The concentration of acyl glucuronide isomers is estimated as the difference between (iii) and (ii). In this way one can use the subtraction method to estimate the concentration of both the 1-b and rearrangement isomers using LC–MS/MS. It is also possible to obtain a time course of the hydrolysis and rearrangement of the acyl glucuronide. Using this technique it was possible to quantify the amount of acyl glucuronide bound to HSA as shown in Figure 6.20. The extent of covalent modification can also be measured directly. Radiolabeled drug can be administered to a rat or monkey.

Figure 6.20 The ranking of compounds according to their extent of covalent binding expressed in millimoles irreversibly bound per mole protein, normalized by protein content and expressed as the percentage of total acyl glucuronide present at the beginning of the reactivity phase. Acyl glucuronide was measured using LC–MS/MS and the difference assay. (Source: Bolze, S. et al. Drug Metab. Dispos., 30, 404, 2002. With permission.)

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 199/202

Acyl Glucuronides: Assays and Issues

199

Figure 6.21 Acyl glucuronide risk assessment cube showing the interplay of acyl glucuronide reactivity, plasma level and percent conversion. When all of these three parameters are high there is a high risk for an immunotoxic response. LC–MS/MS plays a significant role in determining each of these parameters. (Source: White, R.A., SPRI (personal communication). With permission.)

Following sufficient washout time a liver slice can then be analyzed using quantitative whole body autoradiography in order to determine the extent of covalent modification of liver protein. Liver homogenate can also be analyzed by LC–MS/MS to strengthen this analysis. In this way the amount of bound drug per mg of protein can be measured. An acyl glucuronide risk assessment cube is shown in Figure 6.21. When there is a high level of acyl glucuronide circulating in plasma and excreted in urine and bile coupled to a high reactivity as evidenced by significant acyl migration and protein binding, there is cause for concern. As shown, mass spectrometry touches each of these parameters and the extent of its use is growing. 6.6

Summary

HPLC–MS/MS is now routinely being used to determine acyl glucuronide concentrations in a variety of matrices using various methodologies. HPLC– MS/MS is also being used to determine acyl glucuronide stability and potential reactivity with proteins, most notably human serum albumin. This information is important to establish a risk assessment framework, which shows due diligence in regard to FDA approval. In order to accomplish this goal the acyl glucuronide must be well characterized using methodologies that easily lend themselves to mass spectrometric techniques. Given the idiosyncratic nature of the toxicological effect it is difficult to correlate any individual parameter with an effect, but within the drug discovery paradigm it may be possible to build out the reactivity or select candidate that forms a more stable acyl glucuronide. The trend to screen metabolic liabilities in early drug discovery is increasing Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 200/202

Using Mass Spectrometry for Drug Metabolism Studies

200

and LC–MS/MS is a major player [43]. More research is required to recognize altered enzyme function, release of cytokines and track antibody levels mediated by acyl glucuronide action. A significant portion of this research may benefit from the tools of mass spectrometry. 6.7

Acknowledgement

The author thanks Dr Dan Prelusky, Lisa Broske and Lydia Wang for their efforts in animal dosing and radioactivity counting. Drs Ronald White, Nigel Clarke, Diane Rindgen, and Kathleen Cox are gratefully acknowledged for their invaluable input and many discussions regarding acyl glucuronides.

References 1. Faed, E.M., Properties of acyl glucuronides: implications for studies of the pharmacokinetics and metabolism of acidic drugs, Drug Metab. Rev., 15, 1213, 1984. 2. Spahn-Langguth, H. and Benet, L.Z., Acyl glucuronides revisited: is the glucuronidation process a toxification as well as a detoxification mechanism?, Drug Metab. Rev., 24, 5, 1992. 3. Shipkova, M. et al. Acyl glucuronide drug metabolites: toxicological and analytical considerations, Thera. Drug Mon., 25, 1, 2003. 4. Williams, D.P. and Park, B.K., Idiosyncratic toxicity: the role of toxicophores and bioactivation, Drug Disc. Today., 8, 1044, 2003. 5. Bailey, M.J. and Dickinson, R.G., Acyl glucuronide reactivity in perspective: biological consequences, Chem.-Bio. Inter., 145, 117, 2003. 6. Fenselau, C., Acyl glucuronides as chemically reactive intermediates; in Conjugation–deconjugation reactions in drug metabolism and toxicity, Kauffman, F.C., Ed., Springer-Verlag, Berlin, 1994, 367. 7. Spahn, H. et al. Procedures to characterize in vivo and in vitro enantioselective glucuronidation properly: studies with benoxaprofen glucuronides, Pharm. Res., 6, 125, 1989. 8. Ebner, T. et al. Disposition and chemical stability of telmisartan 1-O-acyl glucuronide, Drug Metab. Dispos., 27, 1143, 1999. 9. Prueksaritanont, T. et al. Glucuronidation of statins in animal and humans: a novel mechanism of statin lactonization, Drug Metab. Dispos., 30, 505, 2002. 10. Mutlib, A.E. et al. Disposition of 1-[3-(aminomethyl)phenyl]-N-[3-fluoro20 -(methylsulfonyl)-[1,10 -biphenyl]-4-yl]-3-(trifluoromethyl)-1H-pyrazole-5-carboxamide (DPC 423) by novel metabolic pathways. Characterization of unusual metabolites by liquid chromatography/mass spectrometry and NMR, Chem. Res. Toxicol., 15, 48, 2002. 11. Corcoran, O. et al. HPLC/1H NMR spectroscopic studies of the reactive a-1-O-acyl isomer formed during acyl migration of S-naproxen b-1-O-acyl glucuronide, Chem. Res. Toxicol., 14, 1363, 2001. 12. Ware, J.A. et al. Immunochemical detection and identification of protein adducts of diclofenac in the small intestine of rats: possible role in allergic reactions, Chem. Res. Toxicol., 11, 164, 1998.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 201/202

Acyl Glucuronides: Assays and Issues

201

13. Bougie, D. et al. Sensitivity to a metabolite of diclofenac as a cause of acute immune hemolytic anemia, Blood, 90, 407, 1997. 14. Boelstreli, U.A., Xenobiotic acyl glucuronides and acyl CoA thioesters as protein reactive metabolites with the potential to cause idiosyncratic drug reactions, Curr. Drug, Metab., 3, 439, 2002. 15. Paulson, S.K. et al. Metabolism and excretion of [14C]Celecoxib in healthy male volunteers, Drug Metab. Dispos., 28, 308, 2000. 16. Compernolle, F. et al. Glucuronic acid conjugates of bilirubin-IXalpha in normal bile compared with post obstructive bile. Transformation of the 1-Oacyl glucuronide into 2-, 3-, and 4-O-acyl glucuronides, Biochem. J., 171, 185, 1978. 17. Akira, K., Uchijima, T., and Hashimoto, T. Rapid internal acyl migration and protein binding of synthetic probenecid glucuronides, Chem. Res. Toxicol., 15, 765, 2002. 18. Ebner, T. et al. Disposition and chemical stability of telmisartan 1-O-acyl glucuronide, Drug Metab. Dispos., 27, 1143, 1999. 19. van Breemen, R.B. et al. Reaction of bilirubin glucuronides with serum albumin, J. Chromatogr., 383, 387, 1986. 20. McDonagh, A.F. et al. Origin of mammalian biliprotein and rearrangement of bilirubin glucuronides in vivo in the rat, J. Clin. Invest., 74, 763, 1984. 21. van Breemen, R.B. and Fenselau, C., Acylation of albumin by 1-O-acyl glucuronides, Drug Metab. Dispos., 13, 318, 1985. 22. Wells, D.S., Janssen, F.W., and Ruelius, H.W., Interactions between oxaprozin glucuronide and human serum albumin, Xenobiotica, 17, 1437, 1987. 23. Ding, A. et al. Evidence for covalent binding of acyl glucuronides to serum albumin via an imine mechanism as revealed by tandem mass spectrometry, Proc. Natl. Acad. Sci., 90, 3797, 1993. 24. Qiu, Y., Burlingame, A.L., and Benet, L.Z., Mechanisms for covalent binding of benoxaprofen glucuronide to human serum albumin: studies by tandem mass spectrometry, Drug Metab. Dispos., 26, 246, 1998. 25. Ding, A. et al. Reactivity of tolmetin glucuronide with human serum albumin: identification of binding sites and mechanisms of reaction by tandem mass spectrometry, Drug Metab. Dispos., 23, 369, 1995. 26. Grubb, N., Weil, A., and Caldwell, J., Studies on the in vitro reactivity of clofibryl and fenofibryl glucuronides. Evidence for protein binding via a Schiff’s base mechanism, Biochem. Pharmacol., 46, 357, 1993. 27. Smith, P.C., Benet, L.Z., and McDonagh, A.F., Covalent binding of zomepirac glucuronide to proteins: evidence for a Schiff base mechanism, Drug Metab. Dispos., 18, 639, 1990. 28. Khan, S., Teitz, D.S., and Jemal, M., Kinetic analysis by HPLC–electrospray mass spectrometry of the pH-dependent acyl migration and solvolysis as the decomposition pathways of ifetroban 1-O-acyl glucuronide, Anal. Chem., 70, 1622, 1998. 29. Bolze, S. et al. Development of an in vitro screening model for the biosynthesis of acyl glucuronide metabolites and the assessment of their reactivity toward human serum albumin, Drug Metab. Dispos., 30, 404, 2002. 30. Hop, C.E.C.A. et al. Formation and reactivity of acyl glucuronides assessed by LC/MS/MS, in Proceedings of the 48th ASMS Conference on Mass Spectrometry and Allied Topics, Long Beach, CA, 2000. 31. Hayball, P.J., Formation and reactivity of acyl glucuronides, Chirality, 7, 1, 1995.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-06.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 202/202

202

Using Mass Spectrometry for Drug Metabolism Studies

32. Prakash, C. and Soliman, V., Metabolism and excretion of a novel antianxiety drug candidate, CP-93,393, in Long Evans rats: differentiation of regioisomeric glucuronides by LC–MS/MS, Drug Metab. Dispos., 25, 1288, 1997. 33. Zhao, Y. et al. Simultaneous determination of SU5416 and its phase I and phase II metabolites in rat and dog plasma by LC–MS/MS, J. Pharm. Biomed. Anal., 25, 821, 2001. 34. Shirley, M.A. et al. Oxidative metabolism of a rexinoid and rapid phase II metabolite identification by mass spectrometry, Drug Metab. Dispos., 25, 1144, 1997. 35. Benet, L.Z., Effect of pH on acyl migration and hydrolysis of tolmetin glucuronide, Drug Metab. Dispos., 16, 322, 1988. 36. Rindgen, D. et al. The application of HPLC/tandem mass spectrometry for the assessment of acyl glucuronide metabolite formation in in vitro and in vivo systems in a drug discovery environment, Am. Pharm. Rev., 4, 52, 2001. 37. Wainhaus, S.B. et al. Semi-quantitation of acyl glucuronides in early drug discovery by LC–MS/MS, Am. Pharm. Rev., 5, 86, 2002. 38. Kamimori, et al. Synthesis of acyl glucuronides of drugs using immobilized dog liver microsomes octadecylsilica particles coated with phospholipids, Anal. Bichem., 317, 99, 2003. 39. Dickinson, R.G., et al. Disposition of valproic acid in the rat: dose dependent metabolism, distribution, enterohepatic recirculation and choleretic effect, J. Pharmacol. Exp. Ther., 211, 583, 1979. 40. Verbeek, R.K., Glucuronidation and disposition of drug glucuronides in patients with renal failure, Drug Metab. Dispos., 10, 87, 1982. 41. Shipkova, M. et al. Pharmacokinetics and protein adduct formation of the pharmacologically active acyl glucuronide metabolite of mycophenolic acid in pediatric renal transplant recipients, Ther. Drug Monit., 24, 390, 2002. 42. Olsen, J. et al. Chemical reactivity of the naproxen acyl glucuronide and the naproxen coenzyme A thioester towards bionucleophiles, J. Pharm. Biomed. Anal., 29, 7, 2002. 43. Xue, G., et al. Screening and identification of phase II metabolites using LC–MS/ MS, in Proceedings of the 51st ASMS Conference on Mass Spectrometry and Allied Topics, Montreal, Quebec, 2003.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 203/228

Chapter 7 Utilizing Higher Mass Resolution in Quantitative Assays Xiaoying Xu

7.1

Introduction

Increasing sensitivity and selectivity for quantitation in biological matrices is of special interest in the pharmaceutical industry. Currently, the principal technique used in quantitative bioanalysis is high-performance liquid chromatography coupled with tandem mass spectrometry (HPLC–MS/MS) using either electrospray ionization (ESI) or atmospheric pressure chemical ionization (APCI) [1]. The triple quadrupole (QqQ) mass spectrometer (MS), when operated in the selected reaction monitoring (SRM) mode, offers a unique combination of sensitivity, specificity, and dynamic range. Consequently, the QqQ MS has become the instrument of choice for high-throughput quantification within the pharmaceutical industry. However, even with tandem mass spectrometry, there is a need for chromatographic separation of the analyte from endogenous compounds [2–6]. Traditionally, it is important to achieve maximum chromatographic resolving power within a short chromatographic time; sometimes, the HPLC method development can require a lot of effort and can be quite time consuming. Another possible approach to improve the measurement of the analyte is to increase the mass resolving power of the MS. However, in the past, operation of a quadrupole mass spectrometer at enhanced mass resolution usually resulted in a significant decrease in both ion 0-8493-1963-3/05/$0.00+$1.50 ß 2005 by CRC Press

Copyright © 2005 CRC Press, LLC

203

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 204/228

Using Mass Spectrometry for Drug Metabolism Studies

204

transmission and signal detection. Therefore, unit mass resolution has been a limitation of quadrupole MS instruments and that can be a problem when interference from the matrix or a metabolite cannot readily be eliminated by other means. In this chapter, new technologies are discussed which can provide higher mass resolution that can be used for quantitative assays. Several examples are given which show data comparing higher mass resolution versus unit mass resolution in terms of selectivity, limit of quantitation, accuracy, precision, and linearity.

7.2

Instrumental Technology

Mass resolution, like sensitivity, is commonly used as a performance specification for an MS instrument and varies greatly depending on the mass spectrometer analyzer and the detailed design components of a particular instrument. The mass resolution of a mass spectrometer is qualitatively defined as its ability to discriminate between adjacent ions in a spectrum. Mass resolution is often defined as a function of mass and is given by the following equation: M/
M, where M is the mass of the ion and
M is the smallest increment of mass that can be distinguished by the analyzer. The unit for mass is daltons (Da) and
M is often determined using the full width at half maximum definition (FWHM) of the mass peaks [7]. 7.2.1

Triple quadrupole (QqQ) mass spectrometer

The linear quadrupole mass analyzer is actually a mass filter. It consists of four hyperbolic or round rods, which are placed parallel to each other in a radial array. Opposite rods are charged by a positive or negative CD potential U on which an oscillating radiofrequency voltage, V0,cos!t, is superimposed. The latter successively reinforces and overwhelms the DC field. Ions are introduced into the quadrupole field by means of a low accelerating potential. The ions start to oscillate in a plane perpendicular to the rod length as they traverse through the quadrupole filter. The trajectories of the ions of one particular m/z are stable. These ions are transmitted towards the detector. Ions with other m/z have unstable trajectories and do not pass the mass filter, because the amplitude of their oscillations becomes infinite. The quadrupole analyzer acts as a band pass filter, the resolution of which depends on the ratio of DC and AC potentials [8]. Generally, the resolution is set to unit mass, indicating that, for instance, m/z ¼ 200 and m/z ¼ 201 can be distinguished; all ions with m/z values between 199.5 and 200.49 are attributed to m/z ¼ 200 [9]. When
M
1, not all the m/z 200 ions traverse the analyzer at the same instant. Instead, because a small range of m/z values is allowed through the analyzer at any given time under these conditions, a few m/z 200 ions will begin to leak through the analyzer when the value of the applied voltage (or other variable) corresponds to about m/z 199.5. The number of ions will increase as the value of this variable Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 205/228

Utilizing Higher Mass Resolution in Quantitative Assays

205

Figure 7.1 Typical peak shape for a standard quadrupole mass peak at m/z 200 (Source: Smith, R.M. and Busch, K.L, Understanding Mass Spectra—a Basic Approach, John Wiley and Sons, Inc., New York, NY. With permission.)

approaches that corresponding to m/z 200.0, then taper off again as it approaches that corresponding to m/z 200.5. If m/z 200 ions pass through the analyzer at lower or higher values, they will overlap with the passage of m/z 199 or 201 ions, and the mass resolution will be even lower. The resulting mass peak in this case is thus a curve similar to a typical chromatographic peak, having a maximum value at approximately m/z 200.0 (Figure 7.1). Therefore, the quadrupole mass filter is suitable for the determination of the nominal masses of a compound and its fragment ions [9]. Achieving good mass resolution and peak shape is complex. As a general rule, the more restrictive the conditions for allowing ions through the analyzer, the fewer the number of ions that will be allowed through. In the traditional triple quadrupole mass spectrometer, the amount of sensitivity lost will depend on the resolution of the instrument. The greater the mass resolution (and narrower the peak), the greater the loss in sensitivity. However, improved mass resolution/transmission characteristics for quadrupole mass spectrometers have recently been achieved with the introduction of the TSQ QuantumÕ (Thermo-Finnigan) MS system. The improved sensitivity and enhanced mass resolution may be attributed to several advancements in the TSQ Quantum MS instrument. First, ionization efficiency has been improved with the design of a new orthogonal ion source. The entrance to the heated ion transport tube is under an ion cap. An aluminium bronze block provides a large thermal mass that gives the capillary a uniform heat profile. The ions go through the skimmer and immediately encounter the radially constraining field of the first multipole assembly, Q00. The radial gas conductance of this assembly exceeds the axial conductance so there is a rapid separation of ions from the natural gas load that is pumped away by the turbo molecular pump. The next stage of the ion transport is the second multipole, Q0. Square quadrupoles with flat electrodes are used for both Q00 and Q0, which improves ion transmission. The tandem multipole Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 206/228

Using Mass Spectrometry for Drug Metabolism Studies

206

arrangement also reduces the pressure in Q0, allowing for very efficient adduct fragmentation without the reformation of adducts via ion–molecule reactions. Second, the new instrument has four stages of pumping from a single hybrid turbo molecular pump and single mechanical backing pump. This additional stage of pumping allows the system to have larger orifice diameters between the various stages, thereby increasing ion transmission from the source to the mass analyzer. The ion source transfer optics and the collision cell with square quadrupoles also increases ion transmission. Finally, the hyperbolic quadrupole rods and the accompanying radiofrequency (RF) circuitry have been redesigned. In this instrument, new hyperbolic quadrupole mass filters with larger 6-mm internal field radius and 250-mm length have been developed. It has been shown that the QqQ performance and ion transmission are better when hyperbolic electrodes are used rather than the circular ones, which are used in most traditional QqQ instruments [10]. The mass resolution of a quadrupole mass filter is proportional to the number of RF cycles an ion experiences while traversing the quadrupole rods, which, in turn, is related to the RF frequency and the length of the quadrupole rods. For the TSQ Quantum MS, the m/z range was reduced to 1500 so that the RF frequency could be kept as high as possible at the maximum RF voltage thereby increasing the resolving power. The RF generator circuit was redesigned so that the RF voltage could be increased while minimizing heat production within the RF generator. The overall changes of larger r0 (6 mm), increased RF voltage (10 kV peak to peak) and increased RF frequency (1.123 MHz) contribute to the improved ion transmission at enhanced mass resolution [11]. Figure 7.2(A) shows a test compound’s partial mass spectrum (Q1 scan) under ‘‘unit mass resolution’’ (Q1 at 0.7 Da FWHM) and enhanced mass resolution (Q1 at 0.2 Da FWHM). Figure 7.2(B) shows a ThermoFinnigan test compound’s partial mass spectrum (Q1 scan) under different mass resolution settings (Q1 at 0.7, 0.45, 0.2, 0.1, and 0.07 Da FWHM). The relative abundance of the ion decreased when the mass resolution increased. At a peak width of 0.2 Da FWHM, the relative abundance of the ion (10.2 E5) was only reduced by about 33% relative to the abundance (15.3 E5) at the unit mass resolution setting, 0.7 Da FWHM. At a peak width of 0.1 Da FWHM, the relative abundance of the ion (6.3 E5) is about 40% of the one at 0.7 Da FWHM (15.3 E5). In this example, the mass resolution was also set to 0.07 Da FWHM and the relative abundance of the ion (2.2 E5) decreased significantly (now only about 14% of the original 0.7 Da FWHM ion intensity). In this example, it can be seen that significant increases in mass resolution were obtained (0.2 Da FWHM) before the signal intensity dropped below 50% of the unit mass resolution setting. In other QqQ MS systems, a mass resolution setting of 0.2 Da FWHM would result in an unacceptable loss of signal. 7.2.2

Quadrupole time-of-flight (Q-TOF) mass spectrometer

Mass analysis with a time-of-flight mass analyzer is based on the simple principle that ions that are given the same kinetic energy will have velocities Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 207/228

Utilizing Higher Mass Resolution in Quantitative Assays

207

Figure 7.2 (A) Mass spectra of a candidate compound (Q1 scan). (a) Unit mass resolution (Q1 at 0.7 Da FWHM) and (b) enhanced mass resolution (Q1 at 0.2 Da FWHM). (B) Mass spectra of a candidate compound (Q1 scan) showing the change in peak shape and peak height as the mass resolution was increased. It can be seen that as the mass resolution changed from 0.7 Da FWHM (unit mass resolution) to 0.2 Da FWHM, the mass peaks are sharper, but the signal intensity (peak height) changed only from 15.3 E5 to 10.2 E5. Even going to a mass resolution that gave a 0.07 Da FWHM, the signal intensity was still 2.2 E5. (Figure provided by and used with the permission of Thermo-Finnigan.)

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 208/228

Using Mass Spectrometry for Drug Metabolism Studies

208

proportional to their masses. The potential energy given to each ion, then, is eV, where e is the number of charges on the ion. The output of the detector is plotted as a function of time, and this time is converted to mass-to-charge values by the data system [9]. Unlike quadrupole instruments, which work by eliminating all ions except those of the mass being detected, the TOF instrument detects all of the ions in a draw-out pulse, thus producing a full mass spectrum with each pulse. A hybrid quadrupole orthogonal acceleration time-of-flight (Q-TOF) instrument can be used to acquire data in both the MS and MS/MS modes of operation. For normal mass spectra, the quadrupole is used in the RF-only mode as a wide-bandpass filter to transmit a wide mass range of ions, the collision cell is not pressurized, and ions are transmitted to the TOF for mass analysis. In the MS/MS mode, the quadrupole operates in the normal resolving mode and is able to select precursor ions up to m/z 4000 for collisionally activated dissociation (CAD). Following CAD, the product ions are transmitted to the TOF for mass analysis. In contrast to the QqQ, it is the ratio (m/z)max/(m/z)min that is important, not the difference in these value. The acquisition is made through a time-to-digital converter (TDC). The orthogonal geometry and parallel rather than sequential detection of ions leads to a significant improvement in sensitivity over scanning instruments (e.g., the QqQ) when used to acquire full-scan spectra [12]. To obtain optimum signalto-noise (S/N) ratios, a quadrupole analyzer must allow a limited number of selected ions to pass. Most ions are filtered out, along with much of their qualitative information content. Conversely, time-of-flight instruments inherently conserve, separate, and detect a significantly greater percentage (5–50%) of the ions that have been sampled into the high-vacuum region [13]. The enhanced ion throughput allows time-of-flight instruments to obtain full-scan spectra with better signal-to-noise (S/N) characteristics than comparable spectra obtained with a scanning quadrupole MS. In addition, the increased specificity provided by the higher mass resolution Q-TOF may provide a S/N benefit in some analytical situations [14]. While timeof-flight data appear to be 1 order of magnitude more sensitive than data obtained from single-quadrupole instruments, they cannot yet match the S/N ratios obtained from QqQ systems using selected reaction monitoring (SRM) [15].

7.3 7.3.1

Review of Recent Literature Triple quadrupole (QqQ) mass spectrometers

Triple quadrupole mass spectrometers usually provide excellent sensitivity and selectivity for quantitative analysis. An advantage of the triple quadrupole over many other technologies is the sensitivity of the selected reaction monitoring (SRM) and selected ion monitoring (SIM) modes of operation. Occasionally, interference from the matrix or a metabolite cannot be eliminated using unit Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 209/228

Utilizing Higher Mass Resolution in Quantitative Assays

209

Figure 7.3 Mass spectra of mometasone in the presence of PPG interference. (Source: Yang, L., et al. Rapid Commun. Mass Spectrom., 26, 2060, 2002. With permission.)

mass resolution. One of the main advantages of some of the new generation of triple quadrupoles over the traditional triple quadrupoles is the enhanced mass resolution capability. As a result of this, interfering peaks from isobaric ions (having the same nominal mass) can now be resolved partially or completely with this new QqQ MS capability. With recent advances in instrument designs, some triple quadrupole instruments now provide mass resolution of 0.1 Da using the FWHM definition. Yang et al. [16] demonstrated the advantage of enhanced mass resolution from the TSQ Quantum MS in the case of mometasone with a polypropylene glycol (PPG) interference. The mass spectrometer was operated in the positive electrospray mode. Even though solid phase extraction was used in the sample preparation step, the transmitted precursor ion from the first quadrupole contained not only protonated molecules from mometasone, but also the PPG interference at unit mass resolution (Figure 7.3). The top trace in Figure 7.3 is the Q1 partial scan mass spectrum obtained at enhanced mass resolution (Q1 at 0.1 Da FWHM) showing mometasone peaks 35Cl [M þ H]þ (m/z 521.2) and 37 Cl [M þ H]þ (m/z 523.2)] separated from the PPG interference. The bottom four traces show the precursor ions transmitted from Q1 under different mass resolution settings. As shown in this figure, at unit mass resolution (Q1 at Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 210/228

210

Using Mass Spectrometry for Drug Metabolism Studies

0.7 Da FWHM), not only the selected precursor ions from mometasone, but also ions from the PPG interference were transmitted through Q1 (second and fourth traces). At the enhanced mass resolution (Q1 at 0.1 Da FWHM), only the selected mometasone precursor ions were transmitted (third and fifth traces). The results demonstrate that enhanced mass resolution on a triple quadrupole mass spectrometer could be advantageous when an unexpected interference occurs during sample analysis. Without the enhanced mass resolution function, the method would need to be modified to chromatographically separate the analyte peak from the interfering peak. Since limited sample preparation and fast HPLC are often components of higher throughput pharmacokinetic (PK) methods in a discovery setting, the opportunity for significant improvements in quantitative performance exists by utilizing enhanced mass resolution to remove isobaric interferences when they occur. In a recent study by Paul et al. [17], quantitative LC–ESI–MS/ MS was performed using SRM at unit and enhanced mass resolution settings on a TSQ Quantum MS system. An assay was developed for a pharmaceutical test compound (GSK 2518) using a protein precipitation sample preparation procedure. The most intense SRM transition was a loss of a small molecule, water; this transition was monitored to gain maximum analyte sensitivity. Precursor ion (Q1) settings were 0.7 Da and 0.2 Da FWHM for unit and enhanced mass resolution, respectively, with Q3 held at 0.7 Da FWHM. As shown in Figure 7.4, a dramatic improvement in the

Figure 7.4 Water loss ESI/SRM for GSK 2518 (1 pg) in mobile phase at unit and enhanced mass resolution. (Source: Paul, G. et al. Proceedings of the 50th ASMS Conference on Mass Spectrometry and Allied Topics. With permission.)

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 211/228

Utilizing Higher Mass Resolution in Quantitative Assays

211

S/N ratio was observed at lower analyte concentrations under the enhanced mass resolution conditions. Under enhanced mass resolution conditions, an excellent limit of quantitation (LOQ) of 50 fg on-column was achieved, which was about an order of magnitude better than what was obtained at unit mass resolution [17]. Thus, the enhanced mass resolution capability of a triple quadrupole mass spectrometer can be used to provide more sensitive quantitation for molecules whose most intense SRM transition involves a small molecule loss since this less compound-specific transition is more susceptible to matrix interference. Most users select higher mass resolution for Q1, but one can also increase the Q3 mass resolution. Increasing the mass resolution of the first massanalyzing quadrupole (Q1) improves the specificity for the precursor ion, while increasing resolution in the second mass-analyzing quadrupole (Q3) improves the specificity for the product ion. Schweingruber et al. provided another example of how enhanced mass resolution on Q1 and Q3 can improve signalto-noise ratios at low analyte concentrations in quantitative SRM analyses [18]. An LC–MS/MS assay for compound A in a biological matrix was performed using a Quantum MS system. The triple quadrupole was operated in the SRM mode with argon collision gas at a typical pressure of 1.5 mTorr. As shown in Figure 7.5, four peaks were detected under unit mass resolution (Q1 0.7 Da FWHM and Q3 0.7 Da FWHM). However, only two peaks were detected under enhanced mass resolution (Q1 0.1 Da FWHM and Q3 0.5 Da

Figure 7.5 The improved specificity is manifested by the elimination of extraneous peaks in the mass chromatogram (Source: Schweingruber, H. et al. Proceedings of the 49th ASMS Conference on Mass Spectrometry and Allied Topics. With permission.)

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 212/228

212

Using Mass Spectrometry for Drug Metabolism Studies

FWHM). The improved specificity is evident by the elimination of extraneous peaks in the mass chromatogram. The anti-depressant drug alprazolam (m/z 309.09) and polypropylene glycol (PPG, m/z 309.23) have only a 0.14 Da mass difference; these two components could not be distinguished based on their mass at unit mass resolution. Indeed, if a component of interest of unknown structure had the same nominal mass as a co-eluting unknown background impurity, structural elucidation of the unknown by product ion scanning on a typical unit mass resolution triple quadrupole instrument would be confusing. In order to test the high resolving power of the new triple quadrupole instrument, Amad et al. [19] performed the following test on a Quantum MS system operated in the ESI mode. In this experiment, 10 pg of alprazolam was injected on the column while 10 ng/mL PPG solution was infused post-column to provide a steady background of chemical interference. The higher mass resolving power of the quadrupole mass filters (Q1 0.06 Da FWHM and Q3 0.5 Da FWHM) was used. Figure 7.6(A) shows the mass chromatograms and Figure 7.6(B) shows the corresponding mass spectra that

Figure 7.6 (A) Separation of alprazolam from interfering PPG by enhanced mass resolution (Q1: 0.06 Da FWHM, Q3: 0.5 Da FWHM) in LC/ESI (Source: Amad, M. et al. Proceeding of the 49th ASMS Conference on Mass Spectrometry and Allied Topics. With permission.)

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 213/228

Utilizing Higher Mass Resolution in Quantitative Assays

213

Figure 7.6 (B) Product ion mass spectrum for (a) alprazolam and (b) PPG using enhanced mass resolution (Q1: 0.06 Da FWHM, Q3: 0.5 Da FWHM) (Source: Amad, M. et al. Proceedings of the 49th ASMS Conference on Mass Spectrometry and Allied Topics. With permission.)

were obtained in this study. Despite the close similarity in their masses (
m of only 0.14 Da), the LC–MS mass chromatograms showed excellent separation of alprazolam from the interfering PPG peak with the enhanced mass resolution at 5000 FWHM. By taking full advantage of the enhanced mass resolution setting, high-quality product ion mass spectra were obtained for both alprazolam and PPG, which provided data that could be used for the identification of each compound. In this case, a triple quadrupole mass spectrometer demonstrated the unique ability to routinely achieve a mass resolution up to 5000 FWHM. Under these conditions, components of the same nominal mass and molecular weight less than 500, but whose actual mass differ by 0.1 Da or higher, can be separated by the quadrupole mass filter. Pergolide has potent dopaminergic activity and is indicated for hyperprolactinemic disorders and Parkinson’s disease. Due to its efficacy and long-lasting activity, therapeutic doses are typically less than 1 mg. Plasma concentrations are consequently very low and assay sensitivity has been a major issue in the development of any bioanalytical method for pergolide. Hughes et al. [20] reported the development of an LC–APCI–MS/MS assay Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 214/228

214

Using Mass Spectrometry for Drug Metabolism Studies

Figure 7.7 250 fg on column of pergolide in plasma on column under unit and enhanced mass resolution conditions (Source: Hughes et al. Proceedings of the 50th ASMS Conference on Mass Spectrometry and Allied Topics. With permission.)

using the Quantum MS system to achieve a very low LOQ. Using the older generation mass spectrometers, the development of methods with an LOQ of 5 pg on column has typically included exhaustive sample enrichment procedures. Lengthy chromatographic run times, often involving gradient elution, have also been necessary to facilitate separation of matrix interference from pergolide. By using the Quantum MS system, minimally treated plasma samples were analyzed using isocratic conditions with chromatographic run times of less than 3 min. Using APCI under the unit mass resolution (Q1 0.7 Da FWHM), the LOQ was 500 fg on column. However, further improvements to the LOQ to 250 fg level under the unit mass resolution were difficult due to an apparent poor peak shape due to chemical or matrix background interferences (Figure 7.7). By using the enhanced mass resolution (Q1 0.2 Da FWHM), there was a dramatic decrease in chemical noise and a corresponding 2 enhancement in S/N, which brought the LOQ down to 250 fg on-column. Thus, enhanced mass resolution gives the user a simple and rapid means to improve method sensitivity without the need for further sample preparation or enrichment. Jemal and Ouyeng [21] described the use of the Quantum MS system in the ESI mode for the determination of nefazodone in human plasma or urine samples. Both unit and enhanced mass resolution were investigated under the SRM transition that was selected (m/z 470.232 ! 274.156). For unit mass resolution, Q1 and Q3 were set at 0.7 Da FWHM; for enhanced mass resolution, Q1 and Q3 were set at 0.2 and 0.7 Da FWHM, respectively. After using protein precipitation, plasma or urine samples were injected into the LC–MS/MS system for analysis. As shown in Figure 7.8 the use of enhanced mass resolution allowed the assay to be successfully applied to a human Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 215/228

Utilizing Higher Mass Resolution in Quantitative Assays

215

Figure 7.8 Comparison of the cleanliness of the SRM chromatograms obtained at FWHM settings of 0.7 or 0.2 Th from a 30 pg/mL nefazodone sample in human plasma, with 60 fg injected onto column: upper panel at 0.7 Th; lower panel at 0.20 Th. (Source: Jemal, M. and Ouyang, Z., Rapid Commun. Mass Spectrom., 17, 24, 2003. With permission.)

plasma containing nefazodone at the 30 pg/mL level; the result was a mass chromatogram that had a higher signal specificity (and higher S/N) than was obtained when using unit mass resolution for the same sample. Besides sensitivity, instrument stability is always a big concern for quantitative applications. Under both unit and enhanced mass resolution, the Quantum MS instrument provided very good precision and accuracy, which met the common criteria for bioanalytical quantitation [16, 21]. In our recent investigation [22], we showed that the observed standard deviations between 2.5 to 2500 ng/mL range of a drug discovery compound were all acceptable (<6%) at both unit and enhanced mass resolution for an overnight run lasting 20 h. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 216/228

216

Using Mass Spectrometry for Drug Metabolism Studies

Figure 7.9 Calibration curves of one discovery compound under unit mass resolution (Q1: 0.7 Da FWHM) and enhanced mass resolution (Q1: 0.2 Da FWHM) on the Quantum MS system (Source: Xu, X., et al. Rapid Commun. Mass Spectrom., 17, 832, 2003. With permission.)

Several reports [20, 22] showed that the Quantum MS system provided a better dynamic range than the traditional QqQ MS system, typically over 5 orders of magnitude with excellent linearity, accuracy and precision. In our recent investigation [22] with the Quantum MS operating in the positive ESI mode, we observed a dynamic range between 0.1 and 5000 ng/mL for a drug discovery compound at unit mass resolution (Figure 7.9). At the same operating conditions, the TSQ 7000 (with API-2 source), a traditional QqQ, showed a smaller dynamic range—between 2.5 and 5000 ng/mL (Figure 7.10) for the same compound. By using the enhanced mass resolution, the dynamic range was extended to 0.05–5000 ng/mL on the Quantum MS (Figure 7.9)

Figure 7.10 Calibration curve of one discovery compound under unit mass resolution (Q1: 0.7 Da FWHM) on a TSQ 7000 system (Source: Xu, X. et al. Rapid Commun. Mass Spectrom., 17, 832, 2003. With permission.)

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 217/228

Utilizing Higher Mass Resolution in Quantitative Assays

217

[22]. Hughes showed a similar result for the Quantum MS used in the APCI mode [20].

7.3.2

Quadrupole time-of-flight (Q-TOF) mass spectrometry

The Q-TOF hybrid MS/MS systems have rapidly been embraced by the analytical community as powerful and robust instruments with unique capabilities. Not only have they been widely used for qualitative work to support the structural elucidation of metabolites (see Chapter 8 for more on this topic), but they have also been evaluated for their potential to handle quantitative measurements. The time-of-flight analyzer allows for very high frequency sampling of all ions across the full mass range of up to m/z 10,000. This parallel analysis capability results in a highly efficient duty cycle, maximizing the number of sample ions observed. This is in contrast to triple quadrupole MS instruments that must sequentially analyze one mass at a time while rejecting all others [23]. Another characteristic of modern orthogonal TOF MS is high-mass resolution, with the present instrumentation achieving a mass resolution of 10,000 (FWHM) or greater. Narrow mass range (
0.1 Da) chromatograms can be extracted from total-ion chromatograms to improve the selectivity in situations where analyte detection is chemical noise limited. A comparison study between a traditional triple quadrupole (QqQ) MS system and a Q-TOF mass spectrometer for quantitation was reported by Marvin et al. [24]. Quantitation of o-tyrosine, o-nitrotyrosine, o,o0 -dityrosine, and their isotope-labeled compounds from samples of cat urine was performed by using two LC–ESI–MS/MS systems—a QqQ system (TSQ 7000 API 2) and a Q-TOF system (Micromass with the orthogonal Z-spray interface). All the ions were monitored by either SRM on the QqQ MS system or in full-scan product ion mode on the Q-TOF MS system. After protein precipitation followed by solid phase extraction, the extracts from 500-mL urine samples were analyzed using the two LC–MS/MS systems. Figure 7.11 shows the total ion chromatograms observed from the analysis of a cat urine extract on the QqQ MS system and the Q-TOF MS system set to mass resolution settings of 1000 and 10,000, respectively. Mass accuracy was obtained on the Q-TOF instrument with a lock mass of butylated phenylalanine (theoretical monoisotopic m/z 222.1494) continuously infused post-column at a flow rate of 5 mL/min. Extracted ions of these compounds were set at the exact mass values for the Q-TOF MS system, whereas a unit mass resolution of 0.7 Da FWHM was set for Q1 and Q3 for the QqQ MS system. Under these conditions, a significant improvement in the Q-TOF selectivity can be observed for d3-onitrotyrosine where all the contaminant peaks disappeared. d3-o-nitrotyrosine monitored by the triple quadrupole instrument (SRM analyses) showed the presence of three major peaks that eluted at retention times of 19.0, 23.2, and 24.2 min; the same sample on the Q-TOF showed only one peak detected at 22.9 min. There was one o-nitrotyrosine peak detected at 23.0 min on the Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 218/228

218

Using Mass Spectrometry for Drug Metabolism Studies

Figure 7.11 LC–ESI–MS/MS of a butylated cat urine extract analyzed on the (a–f) QqQ in SRM mode and (g–l) Micromass Q-TOF in full scan product ion acquisition mode. The analysis was performed at unit mass resolution (FWHM) on the QqQ instrument, whereas the extract ions were performed higher mass resolution (using three digits past the decimal) on the Q-TOF instrument on the basis of a lock mass obtained with butylated phenylalanine (m/z 222 ! 120.081) continuously post-column-infused. (Source: Marvin, L.F. et al. Anal. Chem. 75, 261, 2003. With permission.)

Q-TOF system, which was not detectable on the QqQ instrument. A further advantage of using the Q-TOF instrument was the possibility of performing the acquisition in full-scan product ion mode. In this way, the transition ion of each of the compounds can be extracted from the total ion current observed on the Q-TOF system using a narrow mass range (less than 0.1 Da) resulting in a higher selectivity assay. Zhang et al. [25] demonstrated the advantage of using the higher mass resolution (5000 FWHM) on a Micromass LCTÕ MS system with Z-sprayÕ ESI source to separate desipramine from an endogenous plasma interference. The mass spectrum in Figure 7.12 (lower trace) represents a profile mode acquisition under for the analysis of a rat plasma extract containing desipramine. Two masses at 267.277 and 267.194 Da, differing by 0.083 Da, are attributed to desipramine and an endogenous plasma interference, respectively. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 219/228

Utilizing Higher Mass Resolution in Quantitative Assays

219

Figure 7.12 (a) Centroid mode, higher mass resolution mass spectrum and (b) profile mode with nominal mass calibration mass spectrum of desipramine in plasma extract. (Source: Zhang, N. et al. Anal. Chem. 72, 800, 2000. With permission.)

As shown in this figure, when nominal mass calibration was employed, these mass spectral peaks were barely separated and would not be distinguished under unit mass resolution conditions. After calibration with a lock-mass compound and selecting the centroid mode, the higher mass resolution mass spectrum in shown Figure 7.12 (upper trace) was generated. Under these conditions, the narrow mass range of 267.227–267.327 Da could be extracted from the total ion chromatogram to give an exact mass chromatogram that was specific for desipramine without the endogenous interference, thereby improving the selectivity of the assay. The intra- and inter-day precision and accuracy that can be obtained from Q-TOF MS are well within generally accepted criteria for quantitative determination of biological samples [26]. For example, Zhang reported percent relative standard deviation (RSD) values within 15% from standards of 1.5 to 1000 ng/mL for six different compounds [27, 28]. One of the limitations of the TOF-MS system for quantitation is the limited linear dynamic range. Marvin et al. [24] showed that a Q-TOF instrument (Micromass with Z-sprayÕ ) could be a good alternative to a triple quadrupole for quantitative purposes on a relatively small linear dynamic range (3–4 orders of magnitude for the Q-TOF, as compared to 4–5 for the triple quadrupole system). Scott and Zhao [29] also compared the linear dynamic range of the PE SCIEX QSTARÕ hybrid LC-MS/MS system with the PE SCIEX API 3000 QqQ mass Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 220/228

220

Using Mass Spectrometry for Drug Metabolism Studies

Figure 7.13 Calibration curves obtained from LC–TOF–MS (a) and SRM LC–MS (b) for idoxifene in human plasma fortified from 5 to 2000 ng/mL for TOF-MS and 0.5 to 1000 ng/mL for QqQ-MS, respectively. (Source: Zhang et al. J. Chromatogr. B. 757, 151, 2001. With permission.)

spectrometer. Both systems demonstrated good linearity with a correlation coefficient of 0.999 for the selected quantitation ranges, with the QSTARÕ showing a dynamic range over three orders of magnitude and the API 3000 over 4 orders of magnitude under APCI and ESI mode. More applications on the quantitation using Q-TOF MS with a 5000 FWHM mass resolution setting showed a similar linear dynamic range for different compounds [30]. Figure 7.13 shows calibration curves obtained from an LC–TOF–MS system (a) and LC–MS/MS system (b) for idoxifene in human plasma fortified from 5 to 2000 ng/mL for LC–TOF MS system and 0.5 to 1000 ng/mL for LC–QqQ MS system, respectively [28]. A possible reason for the limited linear dynamic range may be related to detection saturation issues of the TOF MS system. Detection saturation is caused by the dead time associated with the time-to-digital converter (TDC) electronics relative to the fast acquisition speed. The microchannel plate ion counting detector of the TOF analyzer also has a relatively unfavorable record regarding linear dynamic range due to depletion of the detector plate charge, effectively blinding the detector, and also due to saturation of the ion counting electronics [31]. Therefore, the potential utility of using accurate mass has been investigated as a means of improving the quantitation limit for bioanalytical applications. However, so far, the QqQ MS systems have been found to be more sensitive (lower LOQ) and to be useful over a broader concentration range. Typically, the Q-TOF MS instruments provided a 5–10 fold higher LOQ Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 221/228

Utilizing Higher Mass Resolution in Quantitative Assays

221

than the traditional QqQ MS instruments [25, 28, 29, 32] in quantitative applications.

7.4

Current Uses and Technology

Pharmacokinetic properties are important decision criteria for selecting drug candidates in early drug discovery programs. A key parameter in drug metabolism and pharmacokinetics is the plasma concentration of the new drug after the administration of the new test compound to laboratory animals. In addition to plasma, more interest has also been given to the target organs in different therapeutic areas, e.g., brain levels in central nervous system (CNS) programs. For compounds designed for CNS targets, it is important to know whether the compound can cross the blood–brain barrier (BBB). Evaluation of brain penetration of compounds can be achieved by measuring the plasma and brain concentration of the compounds from samples collected from individual animals. Liquid chromatography combined with tandem mass spectrometry can be employed to measure the plasma or brain concentration of drug candidates. For typical discovery assays, an LOQ of 5 ng/g brain is considered achievable. As more potent compounds are discovered, there is a need for more sensitive assays [33]. An LC–MS/MS system operated in the ESI positive mode was used in our laboratory to quantify compound W in mouse plasma and brain samples [22]. The sample preparation was a single protein precipitation step for plasma and for the brain samples was homogenization with water followed by protein precipitation of a sample aliquot. Using a traditional QqQ MS, the ThermoFinnigan TSQ 7000, set to unit mass resolution (Q1, 0.7 Da FWHM) resulted in the mass chromatograms shown in Figure 7.14 for a mouse plasma standard spiked with compound W at 1.0 ng/mL (IS is the internal standard for the assay). As shown in Figure 7.14, at the retention time of 1.3 min, only a small peak with a S/N ratio of 1 could been detected as the signal for the analyte (compound W). Clearly there was no baseline separation of this small analyte peak and a similar peak that eluted right in front of the analyte peak that was due to some background interference. When compound W was spiked at 0.1 ng/mL into the same mouse plasma matrix and the extract (supernatant including the IS) was injected onto a Quantum MS system with enhanced mass resolution settings (Q1, 0.2 Da FWHM), a baseline-separated peak was observed with a S/N ratio of 7 (see Figure 7.15). By comparing Figures 7.14 and 7.15, it is evident that the Quantum MS with enhanced mass resolution was able to reduce the background interference so that a lower LOQ could be obtained for this compound in this matrix. Similar results were observed when this compound was assayed in the mouse brain matrix. Figure 7.16 shows the mass chromatograms of compound W (2.5 ng/g) and internal standard spiked into the mouse brain matrix and analyzed by TSQ 7000 LC–MS/MS system using unit mass resolution setting (Q1 0.7 Da FWHM). Only a small peak with a S/N ratio of 2 could be detected Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 222/228

222

Using Mass Spectrometry for Drug Metabolism Studies

Figure 7.14 Mass chromatograms of compound W (1.0 ng/mL) and internal standard spiked into the plasma matrix, obtained using the TSQ 7000 LC/MS/MS system with positive ESI mode under unit mass resolution (Q1 0.7 Da FWHM). (Source: Xu, X. et al. Rapid Commun. Mass Spectrom., 17, 832, 2003. With permission.)

Figure 7.15 Mass chromatograms of compound W (0.1 ng/mL) and internal standard spiked into the plasma matrix, obtained using the Quantum LC–MS/MS system with positive ESI mode under enhanced mass resolution (Q1 0.2 Da FWHM). (Source: Xu, X. et al. Rapid Commun. Mass Spectrom., 17, 832, 2003. With permission.)

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 223/228

Utilizing Higher Mass Resolution in Quantitative Assays

223

Figure 7.16 Mass chromatograms of compound W (2.5 ng/g) and internal standard spiked into the brain matrix, obtained using the TSQ 7000 LC/MS/MS system with positive ESI mode under unit mass resolution (Q1 0.7 Da FWHM). (Source: Xu, X. et al. Rapid Commun. Mass Spectrom., 17, 832, 2003. With permission.)

at the expected retention time. There was no baseline separation and high level of background noise can be seen near the analyte. When compound W was spiked at 0.25 ng/g into the same mouse brain matrix and the extract (supernatant including the IS) was injected onto a Quantum MS system with enhanced mass resolution settings (Q1, 0.2 Da FWHM), a sharp peak was observed with a S/N ratio of 14 and essentially all the background interference was eliminated (see Figure 7.17). From these experiments, it can be seen that the LOQ of compound W was improved at least 10-fold in both plasma and brain matrices by using the enhanced mass resolution capability of the Quantum MS when the same assay is compared to the results that were obtained using a traditional QqQ (TSQ 7000) MS system with unit mass resolution capability. All the results that we have obtained from different experiments have indicated that background interferences from different biological matrices could often be eliminated simply by using the enhanced mass resolution capability of the new Quantum MS system; also, the LOQ was often dramatically improved in these assays. However, it is important to remember Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 224/228

224

Using Mass Spectrometry for Drug Metabolism Studies

Figure 7.17 Mass chromatograms of compound W (0.25 ng/g) and internal standard spiked into the brain matrix, obtained using the Quantum LC–MS/MS system with positive ESI mode under enhanced mass resolution (Q1 0.2 Da FWHM). (Source: Xu, X. et al. Rapid Commun. Mass Spectrom., 17, 832, 2003. With permission.)

that the higher the mass resolution used, the less signal is obtained (see Figure 7.2(B)). In order to get the best balance of sensitivity and selectivity, the following settings are recommended for routine operation of the Quantum MS system: set Q1 to 0.2 Da FWHM and Q3 to 0.7 Da FWHM. It is also important to realize that setting up enhanced mass resolution methods requires more attention to detail than setting up unit mass resolution methods. For instance, the mass setting for the precursor ion selection is more critical when setting up an enhanced mass resolution assay because the analyte mass peak is narrower. Therefore, it is important to use the appropriate mass setting for the Q1 precursor ion (set to the nearest 0.1 Da, not the nominal mass) in order to avoid missing the top of the mass peak which would lead to selecting ions from either the ascending or descending side of the normal distribution of the mass peak for the precursor ion. Furthermore, according to the report by Jemal and Ouyang [21], the precursor ion (Q1) mass values appear to change slightly as the mass resolution (FWHM setting) is changed. Typically, a change of 0.1 Da was observed when the Q1 mass setting changed from 0.7 Da Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 225/228

Utilizing Higher Mass Resolution in Quantitative Assays

225

FWHM to 0.2 Da FWHM. Therefore, for a routine use of an enhanced mass resolution, SRM-based quantitative bioanalytical method, a precursor ion scanning result obtained immediately before the start of the analysis is recommended in order to update the exact precursor ion mass in the SRM table of the bioanalytical method. It is normally not as important to recheck the product ion (Q3) mass setting since the mass resolution (FWHM) for the product ions in the SRM method is typically set at 0.7 Da. Stabilizing the laboratory temperature has also been reported to be very important in terms of operating the MS system under the enhanced mass resolution settings [21]. Jemal and Ouyang [21] reported that the changes in the SRM response correlated very well with the room temperature changes (3–4 C) when an enhanced mass resolution method was used. Jemal concluded that in order to use the enhanced mass resolution properly, the Q1 mass setting in the SRM method should be carefully chosen only when a stable room temperature is available for the MS system. It is likely that the vendor will continue to improve the Quantum MS system so that this problem is diminished; in our laboratory, we have been able to use the enhanced mass resolution feature successfully for overnight assays with no clear evidence that the mass was shifting. We also tested the reproducibility of the Quantum MS system in the enhanced MS SRM mode by 300 repeated injections of the same sample over 20 h; as we reported recently [22], there was no evidence of a mass drift and the reproducibility was very good (standard deviation was 0.5%). Another interesting observation from Jemal and Ouyang [21] showed that in the Quantum MS system, the SRM response (centroid) changes with different scan width parameters selected for the product ion. The response increased with an increase in scan width until the scan width was equal to about twice the FWHM value used for Q3, after which there was no significant change [21]. According to the instrument manufacturer, this result is due to the centroid algorithm used. During the conversion from profile to centroid mode, the centroid algorithm reports the integrated peak area of the profile peak as the intensity of the mass. Therefore, the smaller intensity values from narrower scan ranges are as good as the larger values from larger scan ranges in the same scan time. It is more selective to only scan the top of the profile peak with a small scan width. However, in order to avoid the possibility of falling off the top of the mass peak due to a mass axis shift, particular care is required when selecting the exact mass and using a narrow scan range in combination with the enhanced mass resolution. Therefore, extra care needs to be taken when setting up an enhanced mass resolution SRM assay, but if done properly, the results will be worth the extra effort!

7.5

Conclusions

It is important to increase the specificity of bioanalytical methods; this can be done by enhancing either the chromatographic resolution or the mass Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 226/228

226

Using Mass Spectrometry for Drug Metabolism Studies

resolving power. However, with the new technology, mass resolving power is easy and fast to implement. The higher mass resolution is also important simply because it minimizes the possibility of overlap of an analyte and other mass peaks. The enhanced sensitivity of the Q-TOF MS system allows the acquisition of informative full-scan MS or MS/MS spectra from trace components at levels that would be impossible using a conventional triple quadrupole MS. The improved Q-TOF mass resolution also results in outstanding selectivity, which can be utilized for both qualitative and quantitative applications. A Q-TOF instrument (e.g., Micromass Q-TOF with Z-spray) can be a good alternative to a triple quadrupole mass spectrometer for quantitative purposes for assays with a relatively small linear dynamic range (3–4 orders of magnitude for the Q-TOF MS, as compared to 4–5 for the triple quadrupole MS). The ability of the enhanced mass resolution capability of the TSQ Quantum MS to improve analyte sensitivity through increased mass specificity is demonstrated in this chapter. The mass resolution necessary to separate an analyte from co-eluting compounds in the biological matrix depends on the difference in elemental composition between them. The greater the difference, the more likely that operating one or both mass-analyzing quadrupoles at higher mass resolution will yield improved assay specificity. The best improvement would be expected when mass-deficient atoms such as halogens are incorporated in the analyte, creating a large mass difference from other compounds in the sample matrix. These new quadrupole mass analyzers maintain very high transmission even as mass resolution is increased. Chromatographic peak areas typically decrease by only a factor of 2–3 when mass resolution is increased from 0.7 to 0.1 Da FWHM. However, the elimination of interferences (noise) can improve the S/N ratio, which provides better assay precision and a lower LOQ. In some cases, the LOQ for a drug discovery compound can be lowered by as much as an order of magnitude when using enhanced mass resolution on the Q1 quadrupole mass analyzer. The attainment of enhanced mass resolution on the TSQ Quantum MS is very straight-forward; therefore, this feature provides a practical means for improving the analyte sensitivity in complex biological matrices.

References 1. Jemal, M., High-throughput quantitative bioanalysis by LC/MS/MS, Biomed. Chromatogr., 14, 422, 2000. 2. Ramanathan, R. et al. Liquid chromatography/mass spectrometry methods for distinguishing N-oxides from hydroxylated compounds, Anal. Chem., 72, 1352, 2000. 3. Jemal, M. and Xia Y.Q., The need for adequate chromatographic separation in the quantitative determination of drugs in biological samples by high performance liquid chromatography with tandem mass spectrometry, Rapid Commun. Mass Spectrom., 13, 97, 1999.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 227/228

Utilizing Higher Mass Resolution in Quantitative Assays

227

4. Weng, N. et al. Development and validation of a sensitive method for hydromorphone in human plasma by normal phase liquid chromatography– tandem mass spectrometry, J. Pharm. Biomed. Anal., 23, 697, 2000. 5. Jemal, M. and Ouyang, Z., The need for chromatographic and mass resolution in liquid chromatography/tandem mass spectrometric methods used for quantitation of lactones and corresponding hydroxy acids in biological samples, Rapid Commun. Mass Spectrom., 14, 1757, 2000. 6. Romanyshyn, L., Tiller, P.R., and Hop, C.E.C.A., Bioanalytical applications of ‘fast chromatography’ to high-throughput liquid chromatography/tandem mass spectrometric quantitation, Rapid Commun. Mass Spectrom., 14, 1662, 2000. 7. Fountain, S.T., A mass spectrometry primer, in Mass Spectrometry in Drug Discovery, Rossi, D.T. and Sinz, M. W., Eds., Marcel Dekker, New York, 2002, chap. 3. 8. Niessen, W.M.A., Ed., Liquid-Chromatography–Mass Spectrometry, Marcel Dekker, New York, 1999, chap. 3. 9. Smith, R.M. and Busch, K.L., Understanding mass spectra—a basic approach, Smith, R.M. and Busch, K.L., Eds., John Wiley & Sons, New York, 1999, chaps 1 and 2. 10. Gibson, J.R. and Taylor, S., Prediction of quadrupole mass filter performance for hyperbolic and circular cross section electrodes, Rapid Commun. Mass Spectrom., 14, 1669, 2000. 11. Schoen, A.E. et al. Design and applications of a new high resolution triple quadrupole mass spectrometer, in Proceedings 49th ASMS Conference on Mass Spectrometry and Allied Topics, Chicago, IL, 2001. 12. Morris, H.R. et al. A novel geometry mass spectrometer, the quadrupole orthogonal acceleration time-of-flight instrument, for low femtomole/attomole range biopolymer sequencing, in Mass Spectrometry of Biological Materials, Larsen, B.S. and McEwen, C.N., Eds., Marcel Dekker, New York, 1998, chap. 3. 13. Schultz, S. et al. Comparison of a triple quadrupole using SRM to a TOFMS for quantitative LC–MS support of drug discovery program, in Proceedings 46th ASMS Conference on Mass Spectrometry and Allied Topics, Orlando, FL, 1998. 14. Chernushevich, I.V., Loboda, A.V., and Thomson, B.A., An introduction to quadrupole-time-of-flight mass spectrmetry, J. Mass Spectrom., 36, 849, 2001. 15. Lindemann, T. and Hintelmann, H., Selenium speciation by HPLC with tandem mass spectrometric detection, Anal. Bioanal. Chem., 372, 486, 2002. 16. Yang, L. et al. Investigation of an enhanced resolution triple quadrupole mass spectrometer for high-throughput liquid chromatography/tandem mass spectrometry assays, Rapid Commun. Mass Spectrom., 26, 2060, 2002. 17. Paul, G. et al. Improving LC/ESI/SRM quantitation through high resolution on a triple quadrupole mass spectrometer, in Proceedings 50th ASMS Conference on Mass Spectrometry and Allied Topics, Orlando, FL, 2002. 18. Schweingruber, H. et al. Advantages and limitations of increased mass resolution for quantitative SRM analysis on a triple stage quadrupole mass spectrometer, in Proceedings 49th ASMS Conference on Mass Spectrometry and Allied Topics, Chicago, IL, 2001. 19. Amad, M. et al. Determination of alprazolam in the presence of polypropylene glycol utilizing the high resolution capability of a triple quadrupole mass spectrometer, in Proceedings 49th ASMS Conference on Mass Spectrometry and Allied Topics, Chicago, IL, 2001.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-07.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 228/228

228

Using Mass Spectrometry for Drug Metabolism Studies

20. Hughes, N. et al. High sensitivity electrospray and APCI application of the high resolution TSQ quantum in the quantitiation of cabergoline and pergolide in plasma, in Proceedings 50th ASMS Conference on Mass Spectrometry and Allied Topics, Orlando, FL, 2002. 21. Jemal, M. and Ouyang, Z., Enahnced resolution triple-quadrupole mass spectrometry for fast quantitative bioanalysis using liquid chromatography/tandem mass spectrometry: investigations of parameters that affect ruggedness, Rapid Commun. Mass Spectrom., 17, 24, 2003. 22. Xu, X., Veals, J., and Korfmacher, W.A., Comparison of conventional and enhanced mass resolution triple-quadrupole mass spectrometers for discovery bioanalytical applications, Rapid Commun. Mass Spectrom., 17, 832, 2003. 23. Morris, H.R., et al. High sensitivity collisionally-activated decomposition tandem mass spectrometry on a novel quadrupole/orthogonal-acceleration time-of-flight mass spectrometer, Rapid Commun. Mass Spectrom., 10, 889, 1996. 24. Marvin, L.F. et al. Quantification of o,o0 -dityrosine, o-nitrotyrosine, and o-tyrosine in cat urine samples by LC/electrospray ionization–MS/MS using isotope dilution, Anal. Chem., 75, 261, 2003. 25. Zhang, N. et al. Quantification and rapid metabolite identification in drug discovery using API time-of-flight LC/MS, Anal. Chem., 72, 800, 2000. 26. Yang, L., Wu, N., and Rudewicz, P.J., Applications of new liquid chromatography–tandem mass spectrometry technologies for drug development support, J. Chromatogr. A., 926, 43, 2001. 27. Zhang, H., Heinig, K., and Henion, J., Atmospheric pressure ionization time-offlight mass spectrometry coupled with fast liquid chromatography for quantitation and accurate mass measurement of five pharmaceutical drugs in human plasma, J. Mass Spectrom., 35, 423, 2000. 28. Zhang, H. and Henion, J., Comparison between liquid chromatography–time-of– flight mass spectrometry and selected reaction monitoring liquid chromatographymass spectrometry for quantitative determination of idoxifene in human plasma, J. Chromatogr. B., 757, 151, 2001. 29. Scott, G.J. and Zhao, J.Y., A comparison of quantitation results obtained from a quadrupole time of flight and a triple quadrupole mass spectrometers of APCI, in Proceedings 47th ASMS Conference on Mass Spectrometry and Allied Topics, Dallas, TX, 1999. 30. Clauwaert, K.M. et al. Investigation of the quantitative properties of the quadrupole orthogonal acceleration time-of-flight mass spectrometer with electrospray ionisation using 3,4-methylenedioxymethamphetamine, Rapid Commun. Mass Spectrom., 13, 1540, 1999. 31. Burlingame, A.L., Boyd, R.K., and Gaskell, S.J., Mass spectrometry, Anal. Chem., 70, 647R, 1998. 32. Marchese, S. et al. Quadrupole time-of-flight versus triple-quadrupole mass spectrometry for the determination of non-steroidal antiinflammatory drugs in surface water by liquid chromatography/tandem mass spectrometry, Rapid Commun. Mass Spectrom., 17, 879, 2003. 33. Xu, X. et al. Quantitation of discovery compounds In mouse plasma and brain samples at 0.1 ng/mL and 0.254 ng/g levels using the quantum LC–MS/MS system, in Proceedings 50th ASMS Conference on Mass Spectrometry and Allied Topics, Orlando, FL, 2002.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 229/252

Chapter 8 Special Requirements for Metabolite Characterization Kathleen Cox

8.1

Introduction

The cost to bring a new chemical entity (NCE) to market has escalated in the past two decades to greater than 800 million dollars.1 A breakdown of these costs indicates that the growth rate for discovery and preclinical development costs has decreased substantially while clinical costs have grown at a much more rapid rate due, in part, to the ever increasing complexity of clinical studies. Failure of drugs to reach marketing approval also has to be factored into this process. It is estimated that only one in 10–20,000 NCEs evaluated in discovery programs will be approved for market. As the cost and time involved in developing a successful drug continues to rise, the failure of a potential drug candidate late in the development process results in a tremendous loss of resources.2 While lack of sufficient efficacy is still the predominant cause for early termination of NCE’s, this is followed closely by safety issues and poor pharmacokinetic properties.3,4 Faced with these hurdles, the philosophy of the pharmaceutical industry is changing to put more emphasis on the evaluation of compounds within drug discovery and preclinical development. Drug candidates spend comparatively little time in the discovery phase relative to the period of time required for development and clinical studies. Therefore, the 0-8493-1963-3/05/$0.00+$1.50 ß 2005 by CRC Press

Copyright © 2005 CRC Press, LLC

229

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 230/252

Using Mass Spectrometry for Drug Metabolism Studies

230

challenge posed to discovery scientists is to find out as much as possible about NCEs within the discovery time frame in an effort to minimize costly attrition later in the development process.5 High-throughput analyses have been incorporated throughout the discovery process in an effort to address these needs. High-throughput screening programs have been implemented successfully for the generation of large libraries of potential drug candidates.6 In addition, high-throughput techniques have been successfully implemented to screen large libraries of compounds to look for activity against a particular therapeutic receptor.7 In an effort to adequately screen the large numbers of compounds generated in these high-throughput assays for drug metabolism and pharmacokinetic (DMPK) properties, some of the assays, traditionally reserved for NCEs in development, are now being utilized earlier in the discovery phase.8–12 The challenge in discovery today is to evaluate NCEs as completely as possible while obtaining the information in a rapid and efficient manner. In vitro assays have been developed to predict in vivo parameters such as absorption,13 enzyme inhibition,14 and induction15 in a rapid and resource-efficient manner. These assays are easily amenable to automation and analysis can be conducted in multi-well plate formats. High-throughput in vivo pharmacokinetic techniques have also been developed to obtain critical pharmacokinetic parameters using cassette dosing16 or sample pooling prior to analysis17,18 coupled with multiple analyte detection. However, the complexity of metabolite characterization studies has prevented their integration into a routine, high-throughput format. The application of metabolite identification studies to drug discovery programs is an active and growing field. The goal of this chapter is to discuss the challenges involved in incorporating traditionally time-consuming and complex assays into the fast-paced, high-throughput environment of drug discovery. The success of metabolite identification in this setting depends upon not only the implementation of cutting edge technology, but also in devising strategies based on critical thinking—to answer the questions that are crucial to a particular program as it progresses compounds from general screening to the final selection of a discovery recommendation.

8.2

Review of Recent Literature

It is particularly useful to know the metabolic fate of a promising lead compound early in the discovery phase.19–22 Not only does this lead to the identification of potentially toxic or active metabolites,23–25 but early metabolism studies can also identify metabolically labile portions of a molecule in a particular drug series. Structural analogs of early drug lead candidates can then be designed to block the portions of the molecules that are particularly susceptible to metabolism.26 Drug metabolism involves chemical conversion, usually by an enzyme, to reduce pharmacological activity of an NCE and to facilitate its elimination Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 231/252

Special Requirements for Metabolite Characterization

231

from the body. There are two primary pathways for metabolism. Phase I metabolism involves the introduction of a nucleophilic group by cytochrome P450 enzymes. The most typical Phase I reactions are oxidation, reduction, and hydrolysis. Phase II metabolism involves the addition of a polar group through conjugation to a nucleophilic site on the NCE to substantially increase water solubility and facilitate excretion from the body. The most common Phase II reaction is glucuronidation,27 while other types of conjugation reactions involve sulfation, methylation, acetylation, and conjugation reactions with amino acids or glutathione.28 Drug metabolizing enzymes are located throughout the body in the blood and tissues, but most metabolism takes place in the liver. While the primary purpose of metabolism is detoxification and elimination, metabolic processes can also produce metabolites that are more pharmacologically active, more toxic or more chemically reactive than the parent NCE. The goal of metabolite characterization is to identify the major metabolic pathways, and also to determine whether or not any potentially reactive or toxic metabolites are formed. However, because of the diverse nature of the studies, it is difficult to standardize metabolite characterization studies to meet the challenges of a high-throughput environment. Every compound exhibits a unique metabolic profile dependent on its structure, the system and species selected to metabolize the compound and what matrix is selected for evaluation of metabolites. All mammals exhibit differences in their biochemical make-up between species and sometimes even gender, particularly in the structures and activities of their cytochrome P450 metabolizing enzymes.29 Because of these differences, both the rate of drug metabolism and the metabolic profile may differ between animal species. Ironically, although this diversity complicates routine analysis, knowledge of this diversity can be critical to the discovery program. Metabolic profiling in several species can help determine which species is the most suitable for toxicology studies. While in vitro systems such as microsomes, hepatocytes, and liver slices provide a higher throughput matrix,30 it is difficult to generate a complete picture of the metabolism that will occur in vivo. In addition, since every metabolizing system is unique, it is difficult to design a rapid, generic analytical methodology that is general enough to adequately characterize all samples, yet is specific enough to capture all of the potential metabolic pathways. Because of their complexity, metabolite characterization studies have been typically conducted once a drug enters the development phase. Here, large amounts of drug are available along with a radiolabeled standard and the studies are conducted using HPLC–UV and radioactivity detection. In the discovery phase, relatively small quantities of drug are available (milligram amounts) and a radiolabeled standard is typically not available. However, recent advances in analytical technologies now allow a great deal of metabolism information to be gained from well designed studies utilizing relatively small amounts of non-radiolabeled compounds. An analytical strategy for metabolite profiling outlined by Kostiainen, et al. is shown in Scheme 8.1.20 Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 232/252

Using Mass Spectrometry for Drug Metabolism Studies

232

Scheme 8.1 Strategy and possibilities for metabolite profiling by LC/MS. (Source: Kostiainen, R., et al., J. Mass Spectrom., 38, 357, 2003. With permission.)

8.3

Mass Spectrometry

High-performance liquid chromatography coupled with tandem mass spectrometry (HPLC–MS/MS) is an analytical technique that is ideally suited for metabolite characterization.31,32 The HPLC system partially separates metabolites from the biological matrix background and the mass spectrometer is sensitive enough to detect trace quantities of metabolites. The implementation of atmospheric pressure ionization (API) techniques, such as atmospheric pressure chemical ionization (APCI)33,34 and electrospray ionization (ESI)35 has revolutionized the analysis of biomolecules. API techniques are easily adapted to liquid chromatography inlets, which are necessary for the separation of biomolecules. The ionization sources provide a mechanism for relatively gentle ionization of biomolecules, ensuring that the NCEs and respective metabolites are ionized as intact species. The API techniques enable the evaluation of a diverse set of polar, labile molecules over a wide mass range. Recently, an atmospheric pressure photoionization (APPI) technique has been introduced36,37 which is a powerful complement to the existing API techniques. APPI enables the ionization of less polar compounds that may not have been as readily ionized using the more traditional API techniques and the dopant-assisted APPI has been used successfully for the characterization of metabolites38,39 (For more on APPI, see Chapter 9.) In addition, recent advances in mass spectrometer technology allow these instruments to be used routinely for detailed structural interrogation. They can pinpoint the Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 233/252

Special Requirements for Metabolite Characterization

233

site of structural modification of the metabolite to a small portion of the molecule, while providing exact mass measurement, distinguishing nominally isobaric molecules.5 The use of complementary LC–MS/MS instrumentation provides the best way of completely investigating the metabolic profile of an NCE. The tandem MS capabilities of a triple quadrupole mass spectrometer are useful in providing a first look at the metabolic profile of an NCE and offer the best chance of identifying novel or unexpected metabolites. The triple quadrupole mass spectrometer has the unique ability of performing precursor ion and neutral loss scans in the LC time frames required by metabolite characterization experiments.40 In these tandem MS experiments, the instrument scans to search for any ions that contain a characteristic fragment of the NCE or potential metabolite. These experiments require no prior knowledge of the metabolites and may only require a minor structural similarity to the NCE. In this manner, masses of both expected and unexpected metabolites as well as conjugated metabolites can be pulled out of the mass chromatogram and highlighted for further analysis.41,42 A list of potential metabolites is generated from the precursor ion and neutral loss experiments on the triple quadrupole mass spectrometer, and product ion experiments are utilized for further characterization. In these experiments, the putative metabolites are isolated and subjected to collisioninduced dissociation, providing a fragmentation pattern. In breaking the larger molecule apart into smaller pieces, it is possible to determine what portion of the molecule contains the metabolic alteration. A fragment ion that has shifted in mass from what was seen with the parent NCE indicates that the metabolic modification exists on that portion of the molecule. Product ion experiments can be performed on any tandem mass spectrometer. Often, a single MS/MS experiment is insufficient to narrow down the site of modification. An ion trap mass spectrometer (ITMS) is unique in that it can perform multiple MS/MS experiments. A specific fragment ion produced in a single MS/MS experiment can be isolated and dissociated further. This sequential dissociation experiment (MSn),43,44 narrows the potential sites of modification and provides a more complete assessment of the metabolite structure. Recent advances in quadrupole time-of-flight (Q-TOF) technology45 have provided rugged high performance accurate mass and high resolution capabilities that that are useful in the evaluation of metabolites present in complex matrices. Enhanced mass resolution enables the separation of metabolites from nominally isobaric background ions, facilitating detection. The accurate mass measurements of these metabolites can also provide a limited list of potential empirical formulae for the metabolites of interest, making identification easier. When the accurate mass capabilities are utilized on fragment ions generated in an MS/MS experiment, the potential empirical formulae are even more limited.46,47 It is important to note that an accurate mass measurement of a particular ion will not provide unequivocal identification of its structure and cannot distinguish isomers that have the same exact mass. The true utility of the accurate mass experiments lie in Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 234/252

Using Mass Spectrometry for Drug Metabolism Studies

234

the ability to distinguish between two proposed nominally isobaric structures. The time-of-flight separation of ions combined with the photodiode array detection capabilities of this instrument result in high spectral acquisition speeds and, as a result, can provide highly sensitive detection of low level metabolites. This is particularly useful in the critical identification of metabolites circulating in plasma. Other instruments, such as four sector mass spectrometers or Fourier transform mass spectrometers48 are capable of achieving even higher resolution and mass accuracies and have been used in the characterization of metabolites.49 However, the types of molecules encountered in metabolite ID experiments for small molecule NCEs are typically comprised of only organic atoms and are fairly low molecular weight (<1000 Da). In many cases, the structure of a large portion of the molecule is already known, based on the structure of the parent NCE. Ultra-high-resolution and mass accuracy is not necessary for their characterization. Recent reports have demonstrated that the number of empirical formulae possible for a metabolite can be reduced even further in accurate mass MS/MS experiments when knowledge of the exact mass of the parent NCE is applied.50 Each of the instruments described above provides unique capabilities that are highly useful in evaluating the structures of metabolites. The most effective and comprehensive metabolite characterization experiments utilize a combination of these instruments where their unique capabilities can be combined in a complementary fashion.51 Strategies have been described which utilize separate LC–MS/MS systems in which the inlets are setup in an identical fashion. The LC, column and gradient conditions are the same. Each system is fitted with a radioflow detector in parallel with the mass spectrometer for simultaneous detection of radioactive responses when necessary. Samples can be analyzed on some or all systems depending on the type of experiments that are required.

8.3.1

Sample preparation

Sample preparation and clean-up are also not routine procedures when dealing with samples for metabolite characterization in drug discovery. Often, these samples represent the first evaluation of metabolites for a particular NCE. Since the metabolic pathways are not known and the samples do not contain radiolabeled compound, any clean-up or manipulation of the sample could result in loss of metabolites. However, the matrices that provide the most utility for metabolite characterization are typically extremely dirty, as in the case of bile. The most simple form of sample clean-up involves protein precipitation followed by centrifugation. Liquid–liquid extraction or solidphase extraction procedures can be utilized in cases where some a priori knowledge of the metabolites is available.52 Solid-phase extraction is frequently utilized,53 as the techniques are well established, easily amenable to automation and a wide variety of sorbant materials are available. A further integration of sample cleanup to LC–MS analysis involves the use of in-tube solid-phase Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 235/252

Special Requirements for Metabolite Characterization

235

microextraction (SPME), in which sample extraction, concentration, and introduction into an LC can be integrated into a single step.54 8.3.2

Liquid chromatography

The choice of chromatography conditions for metabolite ID studies can be critical. It is important to separate the metabolites from matrix ions that can influence the ionization and characterization of the compounds of interest. Many high-throughput methodologies which utilize liquid chromatography have adopted small columns and ballistic gradients in order to separate buffer salts or other contaminants from the compounds of interest. Again, with no knowledge of the physico-chemical properties of metabolites, this can be a risky methodology to employ when performing metabolite characterization experiments. In addition, bile salts can have similar chemical properties to conjugated metabolites of small molecules, making them difficult to eliminate. Traditional metabolite characterization experiments involve slow reverse phase gradients and relatively long columns (150–250 mm) to ensure adequate separation of metabolites. However, the selectivity provided by mass spectrometric detection can allow the utilization of shorter columns and shorter run times. Care must be taken to ensure that structurally distinct metabolites do not give the same MS/MS fragmentation pattern, thus providing misleading results. Many researchers, such as Hop et al. have utilized fast gradients without the loss of chromatographic resolution.55,56 Coupling this fast LC time with the rapid scanning capabilities of a quadrupole time of flight mass spectrometer can provide a tremendous amount of metabolism information on several NCEs in a relatively short period of time. New column technologies have been developed to answer the need for good chromatographic resolution in a short run time. Monolithic LC columns offer an advantage over traditional particle columns by providing a unique method of resolving components. Large macro pores (2–6 mm diameter) allow high flow rates due to low resistance and are combined with mesopores (diameters around 120 A˚) to provide a large surface area that facilitates rapid adsorption/desorption and can lead to high resolution separations57,58 (Figure 8.1). Turbulent flow chromatography59 has shown promise in allowing high flow rates, enabling online sample clean-up. However, this technique has shown limited utility in providing the resolution necessary to separate drugs from metabolites that are closely related, structurally. An interesting application of this technique has been described in which on-line extraction was accomplished by turbulent flow chromatography followed by column switching to a traditional reverse phase system for the separation of metabolites.60 While all these innovative column and LC strategies provide added benefits to more rapid analysis of metabolites, their utility, by and large, is in the analysis of known metabolites, not in the elucidation of a completely unknown metabolic profile of an NCE. This type of experiment still requires a fairly long gradient in order to ensure the elution and adequate separation of metabolites. There have been several examples in which fast chromatography has been Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 236/252

Using Mass Spectrometry for Drug Metabolism Studies

236

Figure 8.1 LC/MS chromatogram (m/z 192) of human liver microsome filtrate following analysis on the silica ‘rod’ column, using SIM detection on the triple quadrupole mass spectrometer. (Source: Dear, G., et al., Rapid Commun. Mass Spectrom., 15, 152, 2001. With permission.)

utilized for metabolite characterization experiments. However, extremely fast gradient experiments can often be limited by the scanning capabilities of the mass spectrometer. Often, slower scanning instruments such as ion traps must be replaced by the faster scanning time-of-flight instruments in order to provide adequate sampling to keep up with the rapid chromatography. 8.3.3

Software

Various software programs have evolved in the past few years to aid in the characterization of metabolites. Many programs exist which provide assistance in nearly all stages of the characterization processes. In silico programs exist which can propose metabolic pathways based on the structure of the NCE61 and databases are continually being updated to contain searchable metabolic routes.62 Metabolite ID software programs have been developed by the three major mass spectrometry vendors to aid in the analytical process. These programs include the ability to evaluate data acquired by the mass spectrometer and process massive data files to highlight only the information on potential metabolites. Metabolite ID software can now be utilized to ‘mine’ MS data, numerically evaluating the MS spectra, subtracting a mass chromatogram containing only matrix ions, looking for expected metabolites or characteristic isotopic patterns, intelligently providing lists of potential metabolites and setting up further experiments to confirm the identity of the metabolites. Many of the software programs offer the ability to interrogate the Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 237/252

Special Requirements for Metabolite Characterization

237

Scheme 8.2 A typical software decision tree for metabolite characterization studies. (Source: Cox, K.A., et al., Am. Pharm. Rev., 4, 45, 2001. With permission.)

data ‘on the fly’, searching for characteristic masses in some type of survey scan during a chromatographic run and rapidly switching acquisition modes to a product ion scan as the peak is eluting in order to obtain structural information. Again, the complexity of the sample matrix can prohibit the effective use of survey scans. Abundant matrix ions can overwhelm the sample and overload the software. Although the mass spectrometer is typically run in full scan mode for the survey scan, recent reports have shown that precursor ion or constant neutral loss scans can be used as survey scans, providing enhanced selectivity. A typical decision tree for utilizing these software programs is shown in Scheme 8.2 There are also software packages offered by independent sources that can mine data generated from several different mass spectrometer operating systems. While operator intervention is still crucial and data interpretation continues to be the bottleneck, current software packages provide automated ways to mine the large amounts of data generated in metabolite ID experiments. This has dramatically increased the throughput of metabolite ID studies, allowing these critical experiments to be a useful tool early in the discovery process. A recent report by Nassar et al. incorporates PALLAS MetabolExpert software into an integrated automated metabolic profiling strategy.63 In this approach, compounds were evaluated in microsomes using a robotic liquid handler, software was used to predict possible Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 238/252

Using Mass Spectrometry for Drug Metabolism Studies

238

metabolites, samples were analyzed using a quadrupole time of flight mass spectrometer, and MetaboLynx software was used to find and confirm potential metabolites. Advanced chemistry development/MS (ACD-MS) software was used to guide derivation of metabolite structures based on the MS/MS fragmentation data. The key to streamlining the complicated task of metabolic characterization is to decide what questions need to be answered. For example, definitive metabolite identification studies require absolute structural identification of each metabolite produced. This is a labor-intensive process requiring separation of all metabolites produced in a particular biological matrix (i.e., bile, urine, plasma), analytical characterization of the structure of the metabolite and confirmation with a synthetic standard. This methodology involves the evaluation of one metabolite after another in a serial fashion and often the definitive structural identification must be supplied by NMR. Often the structure of a metabolite can be elucidated by mass spectrometry through the use of exact mass measurements to obtain an empirical formula and/or obtaining a detailed fragmentation pathway for the metabolite. However, the most definitive technique for structural elucidation is NMR. This technique can not only determine the exact site of modification, but also the stereochemistry of the metabolite structure. The drawback of using NMR is that it typically requires a large amount of the metabolite in order to provide definitive structural data (micrograms) while LC–MS/MS typically requires nanograms or even picograms of material for structural characterization. Recently, the direct coupling of LC with MS and NMR has been utilized in the characterization of metabolites.64,65 However, its utility as a routine methodology in the discovery setting remains to be determined. Excellent discussions of recent advances in NMR technology and its application to metabolite characterization studies are included in reviews by Watt et al.66 and Pochapsky and Pochapsky.67

8.4

Current Uses and Technology

Metabolite characterization is needed early in discovery programs to provide a quick look at the metabolic fate of NCEs. These NCEs are not likely to be the final drug candidate, but rather are early structural analogs, designed to understand the overall behavior of a particular structural series. Early feedback about metabolically labile sites or potentially toxic metabolites is crucial to the discovery team in order to direct future synthetic pathways. Many discovery programs utilize in vitro systems to obtain a general picture of the metabolic fate of NCEs at this stage. The evaluation of the metabolic stability of compounds in microsomes68 and hepatocytes69 relies solely on the measurement of the disappearance of parent compound with incubation time and is, thus, amenable to routine, high-throughput analysis. There have been reports describing methods to obtain metabolite identification information from these quantitative metabolic stability samples.70,71 There are also examples in which Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 239/252

Special Requirements for Metabolite Characterization

239

Scheme 8.3 A tiered approach to metabolite characterization.

in vitro protocols have been developed to answer specific questions, such as whether or not glutathione metabolites are formed for an NCE.72 Through the use of characteristic MS/MS scanning techniques, combined with the advantages offered by metabolite ID software programs, we have developed a tiered system designed to answer the most critical questions first, and provide information about the general metabolic profile for an NCE rapidly (Scheme 8.3). The ‘first look’ at the metabolic profile, designated as Tier I, is not comprehensive, but in most cases, provides valuable feedback to the discovery team in a timely manner. Since the goal is to generate orally administered drugs, the metabolites formed after oral dosing are the most relevant. One bileduct cannulated rat is dosed with an NCE and bile and urine are collected for 24 h. The use of a single animal exerts minimal drain on the animal dosing resources and provides a more comprehensive metabolic profile than is typically obtained from an in vitro system. Historical evidence indicates that the majority of the metabolites are excreted in the first 24 h. Once the samples are generated, they are injected directly onto an HPLC–ESI triple quadrupole system. The use of electrospray ionization minimizes the risk of in-source fragmentation of labile conjugated metabolites. Since this is the first evaluation of metabolites for the NCE, the routes of metabolism are not yet known, so no sample clean-up is employed to avoid the risk of losing metabolites. Standard LC conditions are utilized. Analytically, glucuronide, glutathione, and sulfate conjugates can be detected by characteristic constant neutral losses where the mass that is lost is dependent on the conjugate, not the drug (Figure 8.2). Samples in Tier I are subjected to constant neutral loss (CNL) scans that are characteristic for the presence of glucuronide (176 Da), glutathione (129 Da) and sulfate (80 Da) conjugated metabolites. Therefore, conjugated metabolites can be detected without any prior knowledge of the parent drug or previous metabolic pathways. In addition, since these scans are only specific for the conjugate, this approach also can provide indirect evidence of Phase I (P450) metabolism. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 240/252

240

Using Mass Spectrometry for Drug Metabolism Studies

Figure 8.2 Characteristic constant neutral loss (CNL) scans for conjugated metabolites. (Adapted from Cox, K.A., et al., Adv. Mass Spectrum., 16, 204, 2004. With permission.)

More than 95% of the drugs in the market are metabolized by P450s, uridine diphosphate glucuronosyltranferases (UDPGTs) and sulfotransferases and these metabolites are typically excreted in the bile, so evaluation of conjugated metabolites in bile and urine often can provide a fairly comprehensive view of the metabolic fate of an NCE. Glucuronidation is quantitatively the most important conjugation reaction of xenobiotics mediated by UDPGT.73 It is a low affinity, high capacity reaction. Although glucuronidation is typically a detoxification pathway, if the glucuronide is conjugated through an acyl moiety to the corresponding carboxylic acid aglycone, the resulting acyl-glucuronide can undergo acyl migration to form reactive intermediates, capable of covalently binding to proteins. (See Chapter 6 for more on acyl-glucuronides.) This intermediate can interfere with the normal protein function or introduce an immunogenic effect. Again, the characteristic CNL scan for loss of 176 Da will detect and help characterize these potentially toxic metabolites. Glutathione conjugates can be detected by a CNL 129 scan. Glutathione is present in the body and acts as a detoxification mechanism for the elimination of electrophilic entities. Glutathione S-transferase (GST) protects cells from oxidative stress and chemical-induced toxicity by catalyzing the glutathione conjugation reaction with electrophilic, and potentially toxic, xenobiotics.74 Thus, detection of a glutathione metabolite, although not toxic itself, is indicative of a potentially reactive precursor and can have serious Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 241/252

Special Requirements for Metabolite Characterization

241

consequences for the fate of the NCE. An in vitro screen has been reported in which glutathione is used to produce and trap reactive intermediates.75 Evaluation of the incubation mixtures by LC–MS/MS using the selective CNL 129 scan followed by product ion scans for the putative glutathione metabolites provided a fairly rapid method for understanding the nature of the intermediates formed. After detection of conjugated metabolites in CNL scans, the structures of these putative metabolites are confirmed by performing the respective product ion scans in order to obtain structurally characteristic fragments. In addition, targeted product ion scans are conducted to confirm the presence of any common metabolite transitions such as hydroxylation and demethylation, as well as any relevant metabolic transformations common to the particular program area. Metabolite ID software can be utilized at this stage. As discussed previously, a control sample is subtracted from the sample of interest. This can be extremely useful when dealing with complex matrices such as bile and urine where the matrix ions can mask metabolites and parent drug completely. If the NCE contains a characteristic isotopic pattern, such as that generated from the presence of a Cl or Br ion, the total ion chromatogram is evaluated for these patterns. Again, this is a powerful tool to extract drug-related ions from a complex matrix. An example of how software can simplify an extremely complex total ion chromatogram generated from a bile sample is shown in Figure 8.3. Masses corresponding to common or expected metabolites such as oxidation, demethylation and carboxylic acid formation are pulled out of the total ion chromatogram and MS/MS experiments are automatically set up to characterize these metabolites. All of these software tools are intended to complement, not fully replace, manual data interrogation and, although they require carefully chosen initial parameters in order to be effective, they possess the potential to be extremely useful and time efficient. Figure 8.4 shows the results of a constant neutral loss scan in which the specificity provided by only detecting entities that lose 176 amu (characteristic of glucuronide conjugates) can greatly simplify the mass chromatogram. In this case, there is not much gain in performing a background subtraction procedure. The two peaks that are present in the radiochromatogram at 13.78 and 14.28 min are not glucuronide conjugates and thus would not be detected in this specific scan mode. The results from this experiment indicate that this compound is primarily metabolized by Phase II glucuronide conjugation. Once an NCE has progressed past the initial stages in the discovery process and significant resources are being put forth to progress it as a potential drug candidate, a more comprehensive metabolite characterization is required. This puts the compound into Tier II. In this stage, precursor ion scans are performed to detect as many drug-related metabolites as possible. Precursor ions are chosen not only based on characteristic fragments of the protonated parent NCE, but also based on potential metabolic alterations to these fragments. For example, the addition of 16 Da to a characteristic precursor ion Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 242/252

242

Using Mass Spectrometry for Drug Metabolism Studies

Figure 8.3 Software simplification of a rat bile sample of compound X (0–24 h). (a) Full scan MS 100–900 amu; (b) background subtraction; (c) CODA; (d) Cl cluster strip analysis; (e) radiochromatogram.

could capture a hydroxylated metabolite in which the metabolic alteration occurred to that portion of the parent molecule. Additional constant neutral loss scans can also be conducted to track neutral losses that are characteristic of the parent compound in the same manner as the precursor ion experiments are conducted. Again, software programs can evaluate the resulting reconstructed ion chromatogram to highlight potential metabolites and set up and conduct the appropriate MS/MS scans for confirmation. A precursor ion scan (m/z 366) is shown in Figure 8.5. This represents a tier II evaluation of the sample shown in the previous two figures. In this case, m/z 366 represents a characteristic portion of the molecule. Again, application of a selective scan greatly simplifies the mass chromatogram (a). Since the parent molecule in this case contains a Cl atom, the resolution on the third Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 243/252

Special Requirements for Metabolite Characterization

243

Figure 8.4 Selective detection of glucuronide metabolites in rat bile. (a) radiochromatogram; (b) background subtraction; (c) constant neutral loss 176.

Figure 8.5 Data dependent precursor ion scan (pre 366) with open Q3 resolution. (a) mass chromatogram; (b) precursor ion mass spectrum; (c) data dependent MS/MS spectrum of m/z 582.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 244/252

244

Using Mass Spectrometry for Drug Metabolism Studies

quadrupole was adjusted to allow both the 35Cl and the 37Cl isotopes to pass through. This results in the appearance of the characteristic chlorine cluster pattern to emerge for any precursor ions that are detected, providing an even greater level of selectivity (b). In the case of an extremely dirty sample, it is possible to detect spurious matrix ions that are not related to the NCE but also have a characteristic fragment of m/z 366. However, none of the matrix ions should contain a chlorine atom. As mentioned previously, most of the software programs available for mass spectrometers have the ability to acquire product ion spectra ‘on the fly’, changing modes from either full scan or from a selective MS/MS scan such as precursor ion or constant neutral loss, when an ion of interest is detected. In this case, the instrument switched to product ion mode when it detected the peak at 14.49 min and acquired a characteristic product ion spectrum that allowed structural characterization of this metabolite without requiring a second injection of the sample. As more discovery resources are put toward progressing the NCE, it will be dosed in at least one additional nonrodent species for drug metabolism and pharmacokinetic evaluation. The metabolic profile of an NCE is evaluated in additional species in Tier II. Typically, the NCE will be radiolabeled at this stage (most commonly with 3H), allowing for a quantitative evaluation of metabolites based on radioactivity detection. There is a desire to determine relative amounts of metabolites in addition to their identities, so LC conditions are optimized at this stage to separate co-eluting metabolites. The radiotrace will also reveal whether any metabolites containing the radiolabel have been missed in any of the previous characterization experiments. These metabolites typically involve cleavage or some other major alteration of the parent drug. Software programs can again be utilized here to help identify these metabolites. The metabolic profile of an NCE across species, including human, is determined when the compound enters the Tier II phase, utilizing hepatocyte incubations. The metabolic stability of an NCE is determined much earlier when compounds are evaluated for intrinsic clearance in a screening mode. This screen simply monitors the disappearance of parent compound with incubation time and is amenable to a high throughput, automated format. As mentioned previously, these samples are available for evaluation of metabolites, but this type of high-throughput evaluation is only effective if specific routes of metabolism are targeted. For example, if a program knows that a particular structural series is susceptible to acyl-glucuronide formation, this pathway can be monitored in a screening mode. However, a Tier II evaluation of the metabolic profile of an NCE ensures a comprehensive interrogation of metabolic pathways which will answer the critical question of whether human specific metabolites are formed. In addition, since some in vivo metabolism data exists at this stage, it provides a benchmark to assess whether the in vitro system is predictive. Also, the generation of a radiolabeled form the NCE allows the relative routes of metabolism across species to be assessed. Once an NCE is chosen as the lead drug candidate, more specific metabolite characterization is necessary. This stage is designated as Tier III. At this stage, the NCE is subjected to the most comprehensive metabolite characterization Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 245/252

Special Requirements for Metabolite Characterization

245

Figure 8.6 MS5 experiment on the M þ 16 þ gluc metabolite of compound X in rat bile.

possible. MSn experiments along with accurate mass MS and MS/MS experiments are performed to localize the site of metabolic alteration as much as possible. An MS5 experiment on an O-glucuronide metabolite is shown in Figure 8.6. MSn experiments can be problematic, particularly when dealing with low level metabolites or when the most abundant fragment ions do not contain the metabolic alteration. Often, a metabolite of particular interest is isolated from the biological matrix and subjected to NMR for definitive structural elucidation. The metabolic profile of the NCE is determined in plasma at this stage. Identification of circulating metabolites is often critical to explain the pharmacokinetic or the pharmacodynamic profile. An NCE may show efficacy that is inconsistent with what is predicted based upon the known concentration of the parent drug. These inconsistencies could be due to the presence of an active metabolite. Knowledge of these metabolites will also dictate how the analysis of samples will be conducted in development and clinical studies. If significant metabolites are present, they must be monitored throughout the development of the drug.

8.5

Future Directions

The field of metabolite ID and its impact for drug discovery is dynamic and advances in technology and strategies are constantly evolving. There are Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 246/252

246

Using Mass Spectrometry for Drug Metabolism Studies

significant challenges still to be faced and exciting technologies on the horizon. One of the largest challenges is to develop ways to intelligently and rapidly evaluate very large data sets. Software programs are continually evolving to address this need. Databases are growing to incorporate unique as well as expected metabolic alterations to chemical substructures. The caution with the software programs today is that they are far from being ‘black box’ programs. Computers can only evaluate the data sets that are provided by the analytical methodology and if this methodology lacks the selectivity to effectively filter out some of the contaminants, the computer programs can generate meaningless data sets. Because of this, user intervention and interrogation remains critical. Analytical technology is also evolving to address the need to provide more selective data sets. The accurate mass capabilities and fast scanning ability of the time-offlight mass spectrometers have the ability to perform specific MS/MS scans and distinguish xenobiotic masses from excipient matrix masses. Sample clean-up methods as well as advances in chromatography will also contribute to the simplification of the data that is ultimately generated by the mass spectrometer by either eliminating the interfering matrix ions altogether or at least moving them away from the peaks of interest. There is also a demand for a universal detector that will allow quantification of metabolites without requiring synthetic standards. Ultraviolet detectors cannot quantify metabolites out of complex matrices and even have problems detecting the metabolites that are generated at very low concentrations in vivo. Several other universal detectors are available, but their broad-based utility for metabolite evaluation in a discovery setting remains to be seen. Chemiluminescent–nitrogen detectors offer the ability to quantify compounds based upon the number of nitrogen atoms contained in the molecules.76 This technique still requires the chromatographic separation of xenobiotics from other nitrogen containing compounds in the sample, so the utility of this technique for extremely complex biological mixtures remains to be seen. Online coupling of LC with inductively coupled plasma (ICP) mass spectrometry also offers a method of quantifying metabolites that is independent of chemical structure.77,78 ICP atomizes and ionizes compounds, so the response is dependent upon the number of characteristic atoms in the molecule, not the chemical properties and coupling with mass spectrometry provides mass as well as some structural information. Multiple elements can be measured and while ICP is traditionally used for the detection of metals, it can also measure atoms commonly found in drugs such as halogens,79 sulfur,80 and phosphorus. While the contribution of mass spectrometry to the field of metabolite identification has been significant, in many cases, the MS/MS data can only provide a Markush-type structure of a metabolite, identifying the type of modification, but not the exact location of the metabolic alteration. Full structural characterization is, more often than not, dependent upon NMR analysis. As discussed, NMR is not routinely used for studying the structural identification of metabolites at the discovery stage because the metabolites are Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 247/252

Special Requirements for Metabolite Characterization

247

typically not generated in sufficient quantities or sufficient levels of purity. Developments are on-going to increase the selectivity and sensitivity of NMR to evaluate samples without requiring extensive off-line HPLC purification and concentration.

8.6

Conclusions

There is no doubt that metabolite characterization studies can have a tremendous impact on discovery programs. Early knowledge of the metabolic fate of an NCE can redefine the focus of the chemistry, and efforts can, in the end, result in the advancement of a superior drug product. These studies can provide insight into potential metabolic issues that would not otherwise have been brought to light until the NCE was well advanced into the clinical program. A great deal of structural information of metabolites can be obtained using the state-of-the-art LC–MS strategies available today. However, detailed structural characterization of metabolites is not a process that is easily amenable to the high-throughput environment of drug discovery. Each characterization study is unique and the amount of information generated can be prohibitive. The greatest success in utilizing metabolite characterization to support discovery programs has come from structuring studies to answer specific questions, such as whether or not an NCE has the potential to form a toxic metabolite. Some sort of prioritization strategy for metabolite characterization studies is necessary in order to get information back to the discovery team in a timely manner, whether it is similar to the tiered system discussed here or some other strategy. The amount of time spent characterizing a particular NCE should be dependent upon the needs of that particular discovery program and how far the compound has advanced in the discovery process. In this manner, the questions that are most critical to the program can be answered first and all programs can receive some level of support. While advances in analytical technologies continue to improve the quality of the metabolite ID experiments, the critical parameters now appear to center around generating timely and relevant data in support of discovery programs. There are many powerful techniques—both hardware and software—available for conducting structural elucidation of metabolites given enough time and resources. However, the complex nature of the samples generated for metabolite profiling can potentially provide mountains of irrelevant data, requiring significant time for an analyst to decipher. Both in vitro and in vivo samples contain large amounts of endogenous material that can mask metabolites. Experiments designed to increase the amounts of metabolites generated, either by the use of high dose levels or incubation concentrations, can often produce uncharacteristic metabolites by saturating metabolic pathways. The key to successful implementation of metabolite characterization studies in drug discovery is to tailor the studies to the program needs. If a program is interested in broad, general information on common metabolic Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 248/252

Using Mass Spectrometry for Drug Metabolism Studies

248

pathways, large numbers of compounds can be evaluated fairly rapidly from in vitro systems, with the caveat that not all metabolic pathways may be accessed and unusual metabolites will be missed. If the discovery program is interested in toxic metabolic pathways, screening methodologies can be employed to detect metabolite conjugates that are characteristic of reactive intermediates. If the discovery program is nearing the recommendation of an NCE for development, time and resources must be spent to obtain as complete of a picture as possible of the metabolite profile of the NCE.

8.7

Acknowledgements

The author would like to acknowledge D. Grotz, D. Rindgen, D. Weston, and N. Clarke for their contributions to this manuscript.

References 1. DeMasi, J.A., Risks in new drug development: approval success rates for investigational drugs, Clin. Pharmacol. Ther., 69, 297, 2001. 2. Caldwell, J., The role of drug metabolism in drug discovery and development: opportunities to enhance time- and cost-efficiency, Pharm. Sci., 2, 117, 1996. 3. Sinco, P.J., Drug selection in early drug development: screening for acceptable pharmacokinetic properties using combined in vitro and computational approaches, Curr. Opin. Drug Discov. Dev., 2, 42, 1999. 4. Prentis, R.A., Lis, Y., and Walker, S.R., Pharmaceutical innovation by seven UKowned pharmaceutical companies (1964–1985), Br. J. Clin. Pharmacol, 25, 387, 1987. 5. Rodrigues, A.D., Rational high-throughput screening in preclinical drug metabolism, Med. Chem. Res., 8 (1998) 422. 6. Czarnik, A. and Keene, J.D., Combinatorial chemistry, Curr. Biol., 8, R705, 1998. 7. Fernandez, P.B., Technological advances in high throughput screening, Curr. Opin. Chem. Biol., 2 (1998) 597. 8. Lee, M.S. and Kerns, E.H., LC/MS applications in drug development, Mass Spectrom. Rev., 18, 187, 1999. 9. Watt, A.P., Morrison, D., and Evans, D.C., Approaches to higher-throughput pharmacokinetics (HTPK) in drug discovery, Drug Discov. Today, 5, 17, 2000. 10. Eddershaw, P.J., Beresford, A.P., and Bayliss, M.K., ADME/PK as part of a rational approach to drug discovery, Drug Discov. Today, 5, 409, 2000. 11. White, R.E., High-throughput screening in drug metabolism and pharmacokinetic support of drug discovery, Annu. Rev. Pharmacol. Toxicol., 40, 133, 2000. 12. Korfmacher, W.A., Lead optimization strategies as a part of a drug metabolism environment, Curr. Opin. Drug Discov. Develop., 6, 481, 2003. 13. Yamashita, S., et al., Analysis of drug permeation across Caco-2 monolayer: implication for predicting in vivo drug absorption. Pharm. Res. 14, 486, 1997. 14. Crespi, C.L, Miller, V.P., and Penman, B.W., Microtiter plate assays for inhibition of human drug metabolizing cytochromes P450, Anal. Biochem., 248, 188, 1997.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 249/252

Special Requirements for Metabolite Characterization

249

15. Silva, J.M. et al., Refinement of an in vitro cell model for cytochrome P450 induction, Drug Metab. Dispos., 26, 490, 1998. 16. Berman, J., Halm, K., Adkison, K., and Shaffer, J., Simultaneous pharmacokinetic screening of a mixture of compounds in the dog using API LC/MS/MS analysis for increased throughput, J. Med. Chem., 40, 827, 1997. 17. Hop, C.E., Wang, Z., Chen, Q., and Kwei, G., Plasma-pooling methods to increase throughput for in vivo pharmacokinetic screening, J. Pharm. Sci., 3, 901, 1998. 18. Cox, K.A. et al., Novel in-vivo procedure for rapid pharmacokinetic screening of discovery compounds in rats, Drug Discov. Today, 4, 232, 1999. 19. Fernandez-Metzler, C.L. and King, R.C., The emergence and application of technological advances in biotransformation studies, Curr. Top. Med. Chem., 2, 67, 2002. 20. Kostiainen, R., Kotiaho, T., Kuuranne, T., and Auriola, S., Liquid chromatography/atmospheric pressure ionization–mass spectrometry in drug metabolism studies, J. Mass Spectrom., 38, 357, 2003. 21. Clarke, N.J., Cox, K.A., Rindgen, D., and Korfmacher, W.A., Systematic LC/MS metabolite identification in drug discovery, Anal. Chem., 73, 431A, 2001. 22. Korfmacher, W.A. et al., HPLC–API/MS/MS: a powerful tool for integrating drug metabolism into the drug discovery process, Drug Discov. Today, 2, 532, 1997. 23. Pirmohamed, M., Madden, S., and Park, B.K., Idiosyncratic drug reactions. Metabolic bioactivation as a pathogenic mechanism, Clin. Pharmacokinet., 31, 215, 1996. 24. Pohl, L.R., Pumford, N.R., and Martin, J.L., Mechanisms, chemical structures and drug metabolism, Eur. J. Haematol. Suppl., 60, 98, 1996. 25. Kreunter, W. et al., Preclinical pharmacology of desloratadine, a selective and nonsedating histamine H1 receptor antagonist. 2nd communication: lack of central nervous system and cardiovascular effects, Arzneimittelforschung, 50, 345, 2000. 26. Li, C. et al., Integrated application of capillary HPLC/continuous-flow liquid secondary ion mass spectrometry to discovery stage metabolism studies, Anal. Chem., 57, 2931, 1995. 27. Burchell, B., Transformation reactions: glucuronidation, in Handbook of Drug Metabolism, Woolf, T.F., Ed., Marcel Dekker, Inc, New York, 1999, 153. 28. Daly, A.K., Pharmacogenetics, in Handbook of Drug Metabolism, Woolf, T.F., Ed., Marcel Dekker Inc, New York, 1999, 175. 29. Lindberg, L.P. and Negishi, M., Alteration of mouse cytochrome p450coh substrate specificity by mutation of a single amino acid residue, Nature (London), 339, 632, 1989. 30. Elkins, S., et al., Present and future in vitro approaches for drug metabolism, J. Pharmacol. Toxicol. Methods, 44, 313, 2000. 31. Zhang, N., Fountain, S.T., Honggang, B., and Rossi, D.T., Quantification and rapid metabolite identification in drug discovery using API time-of-flight LC/MS, Anal. Chem., 72, 800, 2000. 32. Schultz, G. et al., Comparison of a triple quadrupole using SRM to a TOFMS for quantitative LC-MS support of drug discovery programs, in Proceedings of the 46th ASMS Conference on Mass Spectrometry and Allied Topics, Orlando, FL, 1998. 33. Shahin, M.M., Ion–molecule interaction in the cathode region of a glow discharge, J. Chem. Phys., 43, 1798, 1965. 34. Horning, E.C., et al., Liquid chromatograph–mass spectrometer–computer analytical systems. Continuous flow system based on atmospheric pressure ionization mass spectrometry, J. Chromatogr., 99, 13, 1974.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 250/252

250

Using Mass Spectrometry for Drug Metabolism Studies

35. Yamashita, M. and Fenn, J.B., Electrospray ion source. Another variation on the free-jet theme., J. Phys. Chem., 88, 4451, 1984. 36. Robb, D.B., Covey, T.R., and Bruins, A.P., Atmospheric pressure photoionization: an ionization method for liquid chromatography–mass spectrometry, Anal. Chem., 72, 3653, 2000. 37. Syage, J.A., and Evans, M.D., Photoionization mass spectrometry as a powerful new tool for drug discovery, Spectroscopy, 16, 14, 2001. 38. Keski-Hynnila, H. et al., Comparison of electrospray, atmospheric pressure chemical ionization, and atmospheric pressure photoionization in the identification of apmorphine, dobutamide, and entacapone phase II metabolites in biological samples, Anal. Chem., 74, 3449, 2002. 39. Yang, C. and Henion, J., Atmospheric pressure photoionization liquid chromatographic–mass spectrometric determination of idoxifene and its metabolites in human plasma, J. Chromatogr. A., 970, 155, 2002. 40. Busch, K.L., Glish, G.L., and McLuckey, S.A., Mass Spectrometry/Mass Spectrometry: Techniques and Applications of Tandem Mass Spectrometry, VCH Publishers Inc, New York, 1988. 41. Perchalski, A.D., Yost, R.A., and Wilder, B.J., Structural elucidation of drug metabolites by triple-quadrupole mass spectrometry, Anal. Chem., 54, 1466, 1982. 42. Vrbanac, J.J., O’Leary, I.A., and Bacynski, L., Utility of parent-neutral loss scan screening technique: Partial characterization of urinary metabolites of U-78875 in monkey urine, Biol. Mass Spectrom., 21, 517, 1992. 43. Stafford, G.C. et al., Recent improvements in analytical applications of ion-trap technology, Int. J. Mass Spectrom. Ion Proc., 60, 85, 1984. 44. Louris, J.N. et al., Instrumentation, applications and energy deposition in quadrupole ion trap MS/MS spectrometry, Anal. Chem., 59, 1677, 1987. 45. Sin, C.H., Lee, E.D., and Lee, M.L., Atmospheric pressure ionization time-of-flight mass spectrometry with a supersonic ion beam, Anal. Chem., 63, 2897, 1991. 46. Hop, C.E.C.A. et al., Elucidation of fragmentation mechanisms involving transfer of three hydrogen atoms using a quadrupole time-of-flight mass spectrometer, J. Mass Spectrom., 36, 575, 2001. 47. Eckers, C., Haskins, N., and Langridge, J., The use of liquid chromatography combined with a quadrupole time of flight analyzer for the identification of trace impurities in drug substance, Rapid Commun. Mass Spectrom., 11, 1916, 1997. 48. Marshall, A.G., Hendrickson, C.L., and Shi, S.D.-H., Scaling MS plateaus with high-resolution FT-ICRMS, Anal. Chem., 74, 252A, 2002. 49. Aharoni, A. et al., Non-targeted metabolome analysis by use of Fourier transform ion cyclotron mass spectrometry, OMICS, 6, 217, 2002. 50. Zhang, H., Henion, J., Yang, Y. and Spooner, N., Application of atmospheric pressure ionization time-of-flight mass spectrometry coupled with liquid chromatography for the characterization of in vitro drug metabolites, Anal. Chem., 72, 3342, 2000. 51. Cox, K.A., Clarke, N.J., Rindgen, D., and Korfmacher, W.A., Higher throughput metabolite identification in drug discovery: current capabilities and future trends, Am. Pharm. Rev., 4, 45, 2001. 52. Bolden, R.D., et al., Semi-automated liquid-liquid back-extraction in a 96-well format to decrease sample preparation time for the determination of dextromethorphan and destrorphan in human plasma, J. Chromatogr. B., 772, 1, 2002. 53. Allanson, J.P., Biddlecombe, R.A., Jones, A.E., and Pleasance, S., The use of automated solid phase extraction in the ‘96 well’ format for high throughput

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 251/252

Special Requirements for Metabolite Characterization

54. 55.

56.

57.

58.

59.

60.

61.

62. 63.

64.

65.

66. 67. 68.

69.

251

bioanalysis using liquid chromatography coupled to tandem mass spectrometry, Rapid Commun. Mass Spectrom., 10, 811, 1998. Ulrich, S., Solid-phase microextraction in biomedical analysis, J. Chromatog. A., 902, 167, 2000. Hop, C.E.C.A., Tiller, P.R., and Romanyshyn, L., In vitro metabolite identification using fast gradient high performance liquid chromatography combined with tandem mass spectrometry, Rapid Commun. Mass Spectrom., 16, 212, 2002. Mallett, D.N., Dear, G.J., and Plumb, R.S., Direct analysis of a polar pharmaceutical compound in plasma using ultra-high flow rate liquid chromatography/mass spectrometry with a mixed-mode column, Rapid Commun. Mass Spectrom, 15, 2526, 2001. Hsieh, Y. et al., Simultaneous determination of a drug candidate and its metabolite in rat plasma samples using ultrafast monolithic column high-performance liquid chromatography/tandem mass spectrometry, Rapid Commun. Mass Spectrom., 16, 944, 2002. Dear, G., Plumb, R., and Mallett, D., Use of monolithic silica columns to increase analytical throughput for metabolite identification by liquid chromatography/ tandem mass spectrometry, Rapid Commun. Mass Spectrom., 15, 152, 2001. Ayrton, J. et al., The use of turbulent flow chromatography/mass spectrometry for the rapid, direct analysis of a novel pharmaceutical compound in plasma, Rapid Commun. Mass Spectrom., 11, 1953, 1997. Lim, H.K., Chan, K.W., Sisenwine, S., and Scatina, J.A., Simultaneous screen for microsomal stability and metabolite profile by direct injection turbulent-laminar flow LC–LC and automated tandem mass spectrometry, Anal. Chem., 73, 2140, 2001. Wilson, A.G., White, A.C., and Mueller, R.A., Role of predictive metabolism and toxicity modeling in drug discovery—a summary of some recent advancements, Curr. Opin. Drug Discov. Devel., 6, 123, 2003. Lewis, D.F., Modelling human cytochromes P450 for evaluation drug metabolism: an update, Drug Metabol. Drug Interact., 16, 307, 2000. Nassar, A.-E.F. and Adams, P.E., Metabolite characterization in drug discovery, utilizing robotic liquid-handling, quadrupole time of flight mass spectrometry and in silico prediction, Curr. Drug Met., 4, 259, 2003. Dear, D.J. et al., Mass directed peak selection, an efficient method of drug metabolite identification using directly coupled liquid chromatography–mass spectrometry–nuclear magnetic resonance spectroscopy, J. Chromatog. B., 748, 281, 2000. Shockcor, J.P., Unger, S.E., Savina, P., and Nicholson, J.K., Application of directly coupled LC–NMR–MS to the structural elucidation of metabolites of the HIV-1 reverse-transcriptase inhibitor BW935U83, J. Chromatog. B., 748, 269, 2000. Watt, A.P., Mortishire-Smith, R.J., Gerhard, U., and Thomas, S.R., Metabolite identification in drug discovery, Curr. Opin. Drug Discov. Devel., 6, 57, 2003. Pochapsky, S.S. and Pochapsky, T.C., Nuclear magnetic resonance as a tool in drug discovery, metabolism and disposition, Curr. Top. Med. Chem., 1, 427, 2001. Xu, R. et al., Application of parallel liquid chromatography/mass spectrometry for high throughput microsomal stability screening of compound libraries, J. Am. Soc. Mass Spectrom., 13, 155, 2002. Janiszewski, J.S. et al., A high-capacity LC/MS system for the bioanalysis of samples generated from plate-based metabolic screening, Anal. Chem., 73, 495, 2001.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-08.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:34pm Page: 252/252

252

Using Mass Spectrometry for Drug Metabolism Studies

70. Korfmacher, W.A. et al., Development of an automated mass spectrometry system for the quantitative analysis of liver microsomal incubation samples: a tool for rapid metabolite screening of new compounds for metabolic stability, Rapid Commun. Mass Spectrom., 13, 901, 1999. 71. Lim, H.K., Chan, K.W., Sisenwine, S., and Scatina, J.A., Simultaneous screen for microsomal stability and metabolite profile by direct injection turbulent-laminar flow LC–LC and automated tandem mass spectrometry, Anal. Chem., 73, 2140, 2001. 72. Rindgen, D., Grotz, D.D., Clarke, N.J., and Cox, K.A., The application of HPLC/ tandem mass spectrometry for the assessment of acyl glucuronide formation in in vitro and in vivo systems in a drug discovery environment, Am. Pharm. Rev., 4, 52, 2001. 73. Clarke D.J. and Burchell, B. The uridine diphosphate glucuronosyltransferase multigene family: function and regulation, in Conjugation–Deconjugation Reactions in Drug Metabolism and Toxicity, Kauffman, F.C., Ed., Springer-Verlag, Berlin, 1994. 74. Daly, A.K., Pharmacogenetics, in Handbook of Drug Metabolism, Woolf, T.F., Ed., Marcel Dekker, New York, 1999. 75. Bertrand, M., Jackson, P., and Walther, B., Rapid assessment of drug metabolism in the drug discovery process, Eur. J. Pharm. Sci., 11, S61, 2000. 76. Taylor, E.W., Jia, W., Bush, M., and Dollinger, G.D., Accelerating the drug optimization process: identification, structural elucidation, and quantification of in vitro metabolites using stable isotopes with LC/MSn and the chemiluminescent nitrogen detector, Anal. Chem., 74, 3232, 2002. 77. Suzuki, K.T., Yoneda, S., Itoh, M., and Ohmichi, M., Enriched stable isotopes of elements used as tracers: methods of presenting high-performance liquid chromatographic–inductively coupled argon plasma mass spectrometric data, J. Chromatogr. B, 63, 670, 1995. 78. Sutton, K.L. and Caruso, J.A., Liquid chromatography–inductively coupled plasma mass spectrometry, J. Chromatogr. A, 856, 243, 1999. 79. Axelsson, B.-O., Jornten-Karlsson, J., Michelsen, P., and Abou-Shakra, F., The potential of inductively coupled plasma mass spectrometry detection for highperformance liquid chromatography combined with accurate mass measurement of organic pharmaceutical compounds, Rapid Commun. Mass Spectrom., 15, 375, 2001. 80. Corcoran, O. et al., Directly coupled liquid chromatography with inductively coupled plasma mass spectrometry and orthogonal acceleration time-of-flight mass spectrometry for the identification of drug metabolites in urine: application to diclofenac using chlorine and sulfur detection, Rapid Commun. Mass Spectrom., 14, 2377, 2000.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 253/276

Chapter 9 APPI: A New Ionization Source for LC–MS/MS Assays Yunsheng Hsieh

9.1

Introduction

One common mission for most pharmaceutical companies is to bring new medicines into market through research and development. Bioanalytical methods for supporting biomedical research are an essential element in the process of searching for new leads. High-performance liquid chromatography (HPLC) procedures for the determination of drug components in in vivo and in vitro samples had been the primary analytical tool for several decades prior to the early 1990s. The ideal detector for HPLC techniques should yield linear responses for most analytes as well as providing selective, sensitive, and reliable analyte signals and, ideally, should also be able to provide structural information on test compounds and their metabolites. A tandem mass spectrometer (MS/MS) with molecular weight and fragmentation measurement for both known analytes and unknown components is an obvious candidate for being the ideal detector. Therefore, the importance of selecting the right interface (ionization source) to connect an HPLC to an MS/MS system has been an area of intense research in the last 20 years. The emergence of atmospheric pressure ionization (API) techniques in the last 10 years has allowed HPLC–MS to become the standard analytical technique for many 0-8493-1963-3/05/$0.00+$1.50 ß 2005 by CRC Press

Copyright © 2005 CRC Press, LLC

253

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 254/276

Using Mass Spectrometry for Drug Metabolism Studies

254

pharmaceutical applications. The two most significant atmospheric pressure ionization (API) techniques which are widely employed for HPLC–API/MS/ MS systems are electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI). In this chapter, we focus on a new ionization source design, atmospheric pressure photoionization (APPI), for HPLC–MS and describe how it can be used for pharmaceutical assays.

9.2 9.2.1

Instrumental Technology Early development of HPLC–MS interfaces

Since the late 1960s, much effort on exploring suitable HPLC–MS interfaces was devoted to removing the liquid mobile phase and to ionizing the analytes. A few historical overviews on the coupling of liquid chromatography with mass spectrometric analysis for small molecule determination have been published elsewhere [1–8]. For a reversed-phase chromatography mode, a flow rate of 1 mL/min of water or methanol is converted to 1244 or 700 mL/min vapor at atmospheric pressure, respectively, which can not be handled by the traditional MS vacuum system. Therefore, the initial attempts were to minimize the amount of liquid in order to be able to remove the solvent and to leave the ionized analytes in the gas phase. The use of micro-column chromatography or splitting the mobile phase flow are examples of techniques that have been employed to reduce the overall liquid flow into the MS system. Thermospray (TS), particle beam (PB) and continuous-flow fast atom bombardment (CFFAB) systems are examples of early HPLC–MS interfaces that showed some promise. For the TS source developed by Blakley and co-workers [9], the LC effluent is first introduced to a preheated chamber where the solvent with low molecular mass is instantaneously vaporized and pumped away under a modest vacuum. The rapid spray heating of ionic buffers in the liquid phase results in desorption, evaporation, and ionization of intact ions from the droplets to the gas phase. The analyte molecular ions and cluster ions with larger molecular mass than those of the solvent tend to reach the inlet vacuum region of a mass spectrometer. Three recent examples of using the TS interface for HPLC–MS are the quantitative determination of ceramides [10], analysis of delmopinol and its metabolites [11], and a nicotine N-glucuronide assay [12]. The PB interface consists of three units: aerosol formation, desolvation, and subsequent momentum separation of particles. The LC effluent is mixed with helium gas for nebulization as a high-speed spray of small droplets to a hot desolvation chamber. The flow of droplets is directed through a differentially pumped momentum separator by rotary pumps to remove He and solvent and to form the particle beam. The particle beam entering the ion chamber is suitable for ionization through conventional means such as electron ionization. Three methods of using a combination of liquid chromatography/ particle beam–mass spectrometry (LC/PB–MS) have been reported: (1) for detecting the metabolism of beta-carotene-d8 in humans [13]; (2) for the Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 255/276

APPI: A New Ionization Source for LC–MS/MS Assays

255

structural elucidation of some impurities in nabumetone substances [14]; and (3) for a mechanism study of azole antifungal activity by normal-phase chromatography [15]. Continuous-flow fast atom bombardment (CFFAB) is a direct approach for the HPLC–MS interface. In CFFAB, the column effluent is directly introduced into the vacuum region of the MS at a low flow rate around 5 mL/min. Typically, the mobile phase contains a matrix material such as glycerol that is used to facilitate the ionization process when a fast atom beam (Ar or Xe, at keV energies) bombards the sample. Two examples of combining CFFAB with a capillary column [16] or a micro-bore column [17] have been reported to provide a liquid chromatography–mass spectrometry system that was used for the characterization of bile acids and intact conjugates of bile alcohols in human urine and to detect neurotoxic acylpolyamines in a single venom gland, respectively. 9.2.2

Recent development in HPLC–MS interfaces

The earlier HPLC–MS interfacing techniques described above were generally not robust, were difficult to operate and had poor sensitivity. The recent exponential growth in HPLC–MS applications is primarily due to the introduction of atmospheric pressure ionization (API) techniques for HPLC– MS in the late 1980s. In API, ions are generated at atmospheric pressure using various source designs, such as pneumatic-assisted sonic spray ionization (SSI), electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI), and atmospheric pressure photoionization (APPI) as summarized in Table 9.1. HPLC–API/MS/MS systems have become a standard bioanalytical tool for drug assays in modern pharmaceutical laboratories, providing many benefits including analytical ruggedness, enhanced sensitivity and excellent selectivity [18, 19]. Among all API techniques, ESI and APCI are the most widely employed for HPLC–MS. In ESI, a fused-silica inner capillary and a stainless-steel outer capillary have been used for introducing the sample and the nebulizing nitrogen gas, respectively. The solvent and analytes are ionized through the combined action of applying a high electric field (3–5 kV) and the pneumatic nebulization. These charged droplets shrink due to evaporation leading to the formation of highly charged microdroplets as they are directed toward to the tandem mass spectrometer. Ions emitted from the microdroplet surface appear in the gas phase prior to mass spectrometric detection. ESI normally produces little fragmentation, typically forming protonated molecules, [M þ H]þ and de-protonated molecules, [M
H]
ions, for most polar compounds in the positive and negative ionization mode, respectively. In contrast to ESI, APCI generates ions for less polar compounds up to about 1500 Da by using a corona discharge with a heated nebulizer. The column effluent is converted into gas–vapor mixture through a long (13 cm) heated nebulization quartz tube (350–500 C). Ionization of analytes is mainly induced by a corona discharge needle where the solvent vapor can act as the Copyright © 2005 CRC Press, LLC

Sonic spray ionization (SSI) Electrospray ionization (ESI) Atmospheric pressure chemical ionization (APCI) Atmospheric pressure photoionization (APPI)

Ionization mode

Electric field (kV)

Molecular ions

Best application

þ

0.1–0.5 0.1–2.0 0.5–2.0

RT–200 RT–500 350–500

N/A Yes Yes

N/A 200,000 1,500

þ/
þ/
þ/


None 3.5–5 3.5–5

Thermally labile compounds [M þ H] [M þ H]þ, adduct ions Ionic and polar compounds [M þ H]þ, adduct ions Neutral compounds

0.1–0.6

350–500

Yes

N/A

þ/


1.3

[M þ H]þ, Mþ

N/A: Not available. RT: Room temperature.

Copyright © 2005 CRC Press, LLC

Mass limit (Da)

Nonpolar compounds

Using Mass Spectrometry for Drug Metabolism Studies

Liquid inlet interfaces

Ionization Flow rate Nebulizer (mL/min) temperature ( C) suppression

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 256/276

256

Table 9.1 Comparisons of atmospheric pressure ionization sources for LC–MS/MS systems

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 257/276

APPI: A New Ionization Source for LC–MS/MS Assays

257

reagent gas providing chemical ionization reactions. APCI may yield in-source fragmentation for thermally unstable compounds and therefore is less suitable than ESI for qualitative assays such as metabolite characterization. Both ESI and APCI are often not suitable for the analysis of nonpolar compounds. Another novel API technique is the sonic spray ionization technique developed by Hirabayashi and co-workers in the early 1990s [20, 21]. In SSI, the LC effluent is sprayed from a fused-silica capillary with a very high (sonic) gas flow (3 L/min) coaxial to the capillary. The amount of charged droplets and ions produced from the solution are strongly associated with the gas flow rate. SSI applies neither heat nor an electrical field on the capillary tip and is therefore particularly suitable for the determination of thermally labile compounds. A comprehensive comparative study of SSI, ESI, and APCI on the influence of the eluent composition in terms of ionization efficiency for morphine concluded that APCI proved to be the preferred HPLC–MS interface for the test compound due to its robust character [22]. In this chapter, we focus on a relatively new API source, atmospheric pressure photoionization (APPI), which was introduced by Robb and co-workers in the late 1990s [23]. 9.2.2.1

Photoionization mass spectrometric methods

Photoionization is a direct process of ionizing small molecules. Photoionization detection (PID) was initially adapted for gas chromatography. The research group of Jorgenson at the University of North Carolina-Chapel Hill actively explored the coupling of a vapor-phase photoionization detector for open-tubular liquid chromatography [24]. This investigation led to the further development of atmospheric pressure photoionization (APPI) source for HPLC–MS. Current photoionization techniques can be divided into two categories: sub-atmospheric (lower pressure) photoionization, LPPI, and atmospheric pressure (or so-called dopant-assisted) photoionization, APPI. The major LPPI mechanism of a given drug compound, M, is photon absorption, and electron ejection to yield the molecular ion Mþ which can then extract a proton from water vapor or various protic solvents to form protonated molecules ([M þ H]þ ions), whereas nonpolar compounds such as naphthalene usually form Mþ ions. The LPPI source based on direct photoionization of analyte molecules was developed by Syage and his co-workers at Syagen Technology, Tustin, CA [25, 26]. The integrated LPPI/ MS instrument based on a direct syringe injection autosampler claimed to be able to provide near-universal ionization efficiency, have a linear relationship between signals and concentration, provide minimal fragmentation for new chemical entities and allow for the analysis of 2000 combinatory library samples for drug discovery applications in less than one day. In this chapter, we focus on the APPI interface for HPLC-MS/MS as an alternative method of introducing samples with low-polarity analytes into mass spectrometers. The APPI source was first successfully demonstrated to provide high sensitivity for LC–MS analyses by Robb and co-workers [23]. The APPI source attached to a PE/Sciex API 3000 triple-quadrupole mass spectrometer is Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 258/276

Using Mass Spectrometry for Drug Metabolism Studies

258

Figure 9.1

Schematic diagram of an atmospheric pressure photoionization (APPI) source.

Figure 9.2 An APPI source (PhotoSprayÕ ) coupled to the PE/Sciex API 3000 MS system. The source uses a modified housing of a conventional APCI source.

a commercially available system as shown in Figures 9.1 and 9.2. The APPI source is similar to the APCI source in that mobile phase is vaporized using a heated nebulizer (350–500 C) to generate a dense cloud of gas phase analytes. The mixture of samples and solvent eluting from an HPLC is first converted by Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 259/276

APPI: A New Ionization Source for LC–MS/MS Assays

259

the heated nebulizer into the gas phase prior to introduction into the photoionization region. Ionization uses a vacuum-ultraviolet lamp to emit 10-eV photons (nominal energy) to form dopant radical cations. The lamp discharge filled with Kr was equipped with a magnesium fluoride window (real photon energy at 10 and 10.6 eV). A discharge-lamp mounting bracket (referred to as the offset potential) placed on the heated nebulizer probe was connected to an electrical connector for the high-voltage supply of the discharge lamp [27]. In the dopant-assisted APPI method, large quantities of an ionizable dopant (having an ionization energy below 10 eV) are continuously infused into the vaporizer coaxially by a microsyringe pump at a flow rate of 1/10 of the HPLC flow rate, allowing for the dopant radical cations to be created at atmospheric pressure. Because the ion source is at atmospheric pressure and high temperature (350–500 C), the radical cations of the dopant can further react with solvent and analyte molecules. The protonation reaction of a given analyte, M, involving the dopant and solvent molecules in positive ion mode is summarized as follows: ½dopant þ h
! ½dopantþ þ e
, ½dopantþ þ n½solvent ! ½dopant
H þ ½ðsolventÞn þ Hþ , ½ðsolventÞn þ Hþ þ M ! n½solvent þ ½M þ Hþ : Although most small-molecule analytes have ionization energy (IE) below 10 eV, major HPLC mobile phases such as methanol, acetonitrile, and water used in the reversed-phase chromatography have IEs above 10 eV as shown in Table 9.2. Therefore, the most likely mechanism for charge or proton transfer is from the dopant to the solvent of analyte molecules, while the formation of Mþ directly by photon interactions is not considered to be the primary mechanism. Proton transfer reactions occur only if the proton affinity (PA) of Table 9.2 Ion energetics of the solvents Compound Water Acetic acid Ethanol Methanol Acetonitrile Hexane Iso-octane Chloroform Toluene Benzyl radical Acetone Benzene Naphthalene Reserpine Triethylamine

Copyright © 2005 CRC Press, LLC

Ionization energy (eV)

Proton affinity (kJ/mol)

12.6 10.65 10.48 10.84 12.2 10.13 9.89 11.37 8.83 7.2 9.70 9.24 8.14 7.88 7.53

691.0 783.7 776.4 754.3 779.2

784.0 831.4

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 260/276

260

Using Mass Spectrometry for Drug Metabolism Studies

Figure 9.3 APPI with a dopant. Sensitivity is enhanced about two order magnitudes relatively to no dopant case. Toluene enhances the sensitivity towards all four compounds. Acetone only effectively enhances the sensitivity for carbamazepine and acridine.

the solvent is greater than that of dopant and the PA of analyte is greater than that of the solvent. Toluene (IE ¼ 8.83 eV) is frequently chosen as the preferred dopant due to its relative safety. The APPI chromatograms shown in Figure 9.3 illustrates that acetone (IE ¼ 9.7 eV) is another effective dopant for compounds having a higher proton affinity, such as carbamazepine and acridine, while it does not promote molecular ion formation of naphthalene or diphenyl sulfide, which have a low proton affinity. Therefore, the choice of dopant plays an important role in ionization efficiency of APPI. Kauppila et al. [28] explored the ionization mechanisms of dopant-assisted APPI and the effect of solvent on the ionization efficiency using seven naphthalene derivatives, such as 1-naphthalene methylamine, 2-acetonaphthone, 2-naphthol, 2-ethylnaphthalene, 2-naphthalene ethanol, 2-naphthylacetic acid, and 1,4-naphthoquinone as analytes and 13 different solvent systems. The main reactions for ionization in APPI either in the positive or negative mode were proposed by the authors [28]. It was suggested that in the positive ion mode, the analytes are ionized through either charge exchange or proton transfer as depicted in Figure 9.4. The charge exchange process is favorable for low proton affinity solvents (water, hexane, and chloroform), whereas the addition of methanol or acetonitrile to the solvent can initiate a proton transfer step. The APPI–MS spectra of the solvent systems studied showed that the radical cation of toluene (C7H8þ , m/z 92) remained in the system containing low PA solvents (water, hexane, and others), but was not observed in solvent systems containing methanol or acetonitrile where protonated solvent molecules or their dimers, trimers, or solvent–water clusters were observed, indicating proton transfer from C7H8þ  to the solvent clusters [28]. Although Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 261/276

APPI: A New Ionization Source for LC–MS/MS Assays

Figure 9.4

261

Ionization processes of the dopant-assisted APPI.

the PAs of methanol and acetonitrile are lower than that of the benzyl radical (Table 9.2), the PAs of solvent clusters exceed that of benzyl radical to make the proton transfer thermodynamically possible. The relative abundance of the monomer increases as the temperature increases. Also, the APPI ionization responses of cyclosporine A was observed to be proportional to the nebulizer temperatures as shown in Figure 9.5, indicating a positive impact on the APPI ionization process with increasing temperature. The relationship of solvent eluent flowrate versus the photoionization responses of clozapine and lonafarnib at nebulizer temperatures of 400 C and 500 C was studied in our laboratory [29] and is shown in Figure 9.6(a) and (b), respectively. As indicated in Figure 9.6, the relative responses of both compounds were reduced significantly (100% down to 20%) as the solvent flow rate was increased from 0.1 mL/min to 0.6 mL/min at a consistent dopant delivery speed. The photoionization sensitivity of lonafarnib obtained at two different temperatures was found to be unchanged. This suggested that the heat generated at 400 C was sufficient to vaporize both lonafarnib and the solvent. However, the ion responses of clozapine with APPI source at 400 C were higher than those at 500 C. This suggests that clozapine molecules might be thermally degraded when using a nebulizer temperature above 400 C. The lower sensitivity at the higher mobile phase flow rates was assumed to be the result of the dilution effect on the dopant and poorer heat transfer from the Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 262/276

262

Using Mass Spectrometry for Drug Metabolism Studies

Figure 9.5 Relative APPI responses of cyclosporine A in an ethanol–hexane mixture (20/80) as a function of the temperature of heated nebulizer.

Figure 9.6 Effects of LC eluent flowrates on photoionization efficiency for (a) clozapine and (b) lonafarnib. (Adapted from Hsieh et al. Anal. Chem., 75(13), 3122, 2003. With permission.)

nebulizer. This hypothesis was further examined by the enhanced detection sensitivity of both analytes at a constant solvent flow rate of 1 mL/min when increasing the delivery speed of toluene dopant, as shown in Figure 9.7. At each delivery speed (10–80 mL/min) of dopant solvent, 10 mL of a mixture Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 263/276

APPI: A New Ionization Source for LC–MS/MS Assays

263

Figure 9.7 APPI peak responses of (A) clozapine and (B) lonafarnib as a function of delivery speed of dopant using flow injection analysis. (Adapted from Hsieh et al. Anal. Chem., 75(13), 3122, 2003. With permission.)

containing clozapine and lonafarnib were injected into the flow injection analysis–APPI/MS/MS system three times. It has been well-recognized that mobile phase composition has a substantial effect on the detection sensitivity of HPLC–API/MS/MS systems. Many reports have described the influence of the eluent composition on the ionization efficiency of analytes when HPLC–API/MS/MS systems were used [22, 27–30]. As demonstrated in Figure 9.8, the APCI signals of naphthalene and diphenyl sulfide (low proton affinity components) using acetonitrile as solvent were higher than those using methanol as the organic eluent, while the advantage of APPI over APCI for these test compounds was seen with both solvents. However, in another study, we observed that the solvent combination of water–methanol doubled the photoionization efficiency for clozapine and sarasar as compared to using a water–acetonitrile mobile Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 264/276

264

Using Mass Spectrometry for Drug Metabolism Studies

Figure 9.8 Comparison of APPI and APCI. (a) The HPLC eluant is methanol–water, APPI is more sensitive than APCI. (b) For acetone–water, APPI is still more sensitive, but APCI shows improved sensitivity for naphthalene and diphenyl sulfide. (Adapted from Robb et al. Anal. Chem., 72(15), 3653, 2000. With permission.)

phase [29]. These findings suggest that the detection sensitivity of APPI is similar to other API sources and is strongly associated with the eluent composition. Kauppila and co-authors [28] suggested that the addition of ammonium acetate or ammonium hydroxide would significantly reduce the ionization efficiency of the analytes studied due to the high PA of ammonia. However, we observed that the addition of either ammonium acetate or formic acid (common modifiers for the reversed-phase chromatographic separation) had no significant effect on the photoionization efficiency of clozapine and sarasar at a concentration below 15 mM [29]. Due to the advancement of combinatorial chemistry and parallel synthesis, the pharmaceutical industry has substantially increased the number of new chemical entities (NCEs) produced each year. Consequently, there is a continuing demand for developing sensitive and complementary HPLC–API/ MS/MS assays for detecting drug discovery compounds possessing various chemical properties in a large number of samples derived from various in vitro and in vivo experiments. A generic HPLC–APPI/MS/MS method was developed in our laboratory for quantification of drug components in plasma samples in support of in vivo pharmacokinetics [29]. The same rat Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 265/276

APPI: A New Ionization Source for LC–MS/MS Assays

265

Figure 9.9 Correlation of analytical results obtained by HPLC–APCI/MS/MS method vs the HPLC–APPI/MS/MS method in terms of (A) Cmax and (B) AUC(0–6 h). (Adapted from Hsieh et al. Anal. Chem., 75(13), 3122, 2003. With permission.)

plasma standard and study samples were analyzed for the 42 drug discovery compounds using either APPI or APCI methods under the identical HPLC conditions. The rat pharmacokinetic results of the 42 drug discovery compounds were compared after their assays using either the APPI or APCI interface. The rat PK results of compounds #1 through #42 in terms of Cmax and AUC(0–6 h) measured by APPI method were compared to those obtained by APCI method and found to be very similar. As shown in Figure 9.9, similar correlation coefficients were obtained for both Cmax and AUC(0–6 h) parameters, r2 ¼ 0.980 and r2 ¼ 0.982, respectively, using both approaches. The results of Student’s t test indicated no significant difference of both values for those test compounds determined by both assays with 95% confidence ( ¼ 0.5). The above results confirmed that the APPI method was equivalent with the APCI method in terms of accuracy [29]. It has been reported that APPI outperformed both APCI and ESI in terms of ionization sensitivity and validation statistics for certain neutral compounds with a low proton affinity, such as testosterone [31], idoxifene and its alcohol metabolites in human plasma [32], neurosteroids compounds and their acetylpentafluorobenzyl derivatives [33]. Several comparative studies among ESI, APCI, and APPI sources on the ionization efficiency of anabolic steroid [34] and the phase II metabolites of apomorphine, dobutamine, and entacapone Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 266/276

Using Mass Spectrometry for Drug Metabolism Studies

266

[35] were also investigated. To date, HPLC–APPI/MS/MS has been successfully employed for the determination of vitamins [36], antioxidants [37], polycyclic aromatic hydrocarbons [38], perfluorooctane sulfonate in river water [39], patulin in apple juice [40], chloramphenicol residues in fish [41], and various pharmaceuticals [42–44]. 9.2.2.2

Matrix ionization suppression effect

A general concern about assay reliability of any new HPLC–MS/MS methods is the ionization suppression caused by the co-eluting endogenous materials in biological samples [45–49]; this problem is commonly referred to as matrix ion suppression or simply matrix effects (see Chapter 4 for more information on this topic). The accuracy and reproducibility of the analytical results is often affected by the varying degree of the matrix effects due to different sample preparation methods and ionization interfaces. The post-column infusion technique inserted into HPLC–MS systems is an easy and effective way to evaluate the matrix ionization suppression issue [50]. In general, ESI is more vulnerable than APCI to ionization suppression from biological matrices resulting in inconsistent analytical outcomes. Although the LPPI process should be independent of the surrounding molecules, thereby less sensitive to ion suppression effects, this remains to be demonstrated in multiple examples. The schematic diagram of the post-column infusion system used in our laboratory for the matrix effect studies on APPI source is shown in Figure 9.10. Clozapine and sarasar were continuously infused into PeekÕ tubing in between the analytical column and the mass spectrometer through a tee using a Harvard Apparatus Model 2400 (South Natick, MA, USA) syringe pump. Either a protein precipitation extract of blank rat plasma or mobile phase B (10 mL) was injected into the HPLC column for comparison of ionization responses. Effluent from the HPLC column mixed with the infused compounds and entered the API interface. The infusion HPLC–APPI/MS/MS chromatograms of clozapine and sarasar after either a 10-mL injection of mobile phase or rat plasma extract are shown in Figure 9.11. The differences in the infusion chromatograms between the mobile phase injection and the rat plasma extract

Figure 9.10 Schematic diagram of post-column infusion technique with an atmospheric pressure photoionization source.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 267/276

APPI: A New Ionization Source for LC–MS/MS Assays

267

Figure 9.11 (Top) The reconstructed infusion HPLC–APPI/MS/MS ion chromatograms of lonafarnib following mobile phase (solid line) and blank plasma precipitation extract injections (dotted line). The region showing lower responses indicated the area of matrix ionization suppression. (Bottom) Representative reconstructed HPLC–APPI/MS/MS chromatogram of lonafarnib from standard rat plasma. (Adapted from Hsieh et al. Anal. Chem., 75(13), 3122, 2003. With permission.)

injection are considered to be caused by the matrix ion suppression effects due to plasma sample extract constituents eluting from the column. Figure 9.11 shows that the degree of loss of APPI response and the length of time required for the APPI response to return to its pre-sample injection sensitivity were consistent for both clozapine and sarasar in this study. Therefore, the APPI responses of clozapine and sarasar in the rat plasma protein precipitation extract were not significantly affected by matrix ion suppression in this assay. More severe matrix effects at the same chromatographic region were observed when the dopant was not in use. Increasing the delivery speed of dopant (40 mL/min vs 20 mL/min) enhanced the APPI signals of the analyte but had a marginal effect in reducing ionization suppression, as demonstrated in Figure 9.12. For reliable quantitative determination, it is suggested that the retention times of all analytes be in the region of little or no matrix ion suppression as demonstrated in Figure 9.11

9.3 9.3.1

Other HPLC–APPI–MS/MS applications Zirconia-based HPLC–APPI/MS/MS assay

The zirconia-based packing materials for HPLC columns are capable of providing excellent physical and chemical stability over a wide range of solvent, Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 268/276

268

Using Mass Spectrometry for Drug Metabolism Studies

Figure 9.12 The reconstructed infusion HPLC–APPI/MS/MS ion chromatograms of clozapine following mobile phase (solid line) and blank plasma precipitation extract injections (dotted line) at a constant delivery speed of dopant of 20 mL/min and 40 mL/min. (Adapted from Hsieh et al. Anal. Chem., 75(13), 3122, 2003. With permission.)

pH (1–12), temperature (up to 200 C), and flow rate [51, 52]. The extreme chemical stability over the entire pH range of zirconia particles provides flexible chromatographic conditions to optimize HPLC method development. Zirconia-based columns are complementary to silica-based columns in reversed-phase liquid chromatographic separation and have been used for different diastereomeric selectivity for almost a decade. For the zirconia phase column, buffer systems containing Lewis base additives such as phosphate and fluoride normally provide optimum chromatographic performance for drug molecules. These conditions are normally not compatible with APCI or ESI sources, but can be used with the APPI source. A zirconia-based HPLC– APPI/MS/MS system was developed for the determination of drug discovery compounds in rat plasma in our laboratory in support of in vivo pharmacokinetic studies [53]. The analytical results of ‘‘rapid rat pharmacokinetics’’ for 12 drug discovery compounds obtained by both silica-based phase (S-phase) and zirconia-based phase (Z-phase) chromatographic separation were found to be in good agreement in terms of accuracy [53]. Temperature has been neglected as one of the variables such as the contents of organic solvent, modifier or pH for the optimization of HPLC method development. This is primarily due to the ease of adjusting the mobile phase compositions. In addition, S-phases are thermally unstable and normally are limited to temperatures in the range of 50–60 C. However, increasing the temperature for a chromatographic separation may offer several desirable benefits including the reduction of mobile phase’s viscosity to allow for higher flow rate, faster column efficiency, and better column selectivity. The chemical stability of Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 269/276

APPI: A New Ionization Source for LC–MS/MS Assays

269

Figure 9.13 Reconstructed SRM chromatograms of compound 5, lonafarnib and compound 4 with increasing retention times at the column temperatures of 25 C (top) and 110 C (bottom). Experimental conditions: mobile phase of 60% acetonitrile at flow rates of 0.2 mL/min (top) and 1.0 mL/min (bottom) under isocratic separation. (Adapted from Hsieh et al. Anal. Chem., 75(13), 3122, 2003. With permission.)

Z-phases makes an analytical column that can be used at elevated temperatures and high flow rates. Figure 9.13 shows the zirconia-based HPLC–APPI/ MS/MS chromatograms of two discovery compounds and lonafarnib at column temperatures of 30 C and 110 C with flow rates of 0.2 mL/min and 1.0 mL/min, respectively. The overall back-pressure was observed to decrease as temperature increased at a constant flow rate due to lower eluent viscosity, allowing higher flow rates for faster separations with a minimal change in back pressure. Good consistency in peak shapes was observed and the retention times and peak areas of those analytes using high-temperature chromatography were found to be reproducible after 100 continuous injections (% CV less than 0.4 and 5.0, respectively). The analysis time is significantly decreased from 3 min at 30 C to 30 s at 110 C without a significant loss in chromatographic resolution. Increasing the mobile phase flowrate will result in a poorer detection limits due to the dilution effect of the dopant in the APPI interface, but this can be easily overcome by increasing the delivery speed of dopant solvent. 9.3.2

Normal phase HPLC–APPI/MS/MS assay

Knowledge of the pharmacokinetic characteristics of each of the enantiomeric pharmaceuticals in their absorption, distribution, metabolism, and excretion Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 270/276

270

Using Mass Spectrometry for Drug Metabolism Studies

(ADME) is essential for drug development. It is also important to understand the biological responses of new chemical entities with respect to stereochemistry as part of lead characterization. To evaluate the pharmacokinetics of a single enantiomeror mixture of enantiomers, manufacturers are requested by the FDA to develop quantitative assays for individual enantiomers in in vivo samples early in drug development. Therefore, chiral chromatographic separation is important in developing HPLC–API/MS/MS methods for enantiomers, as they are generally not distinguishable by mass spectrometry. Normally, it is challenging when using methodology based on conventional reversed-phase chromatography to separate enantiomers and regioisomers. Based on our experience, normal-phase chromatography using chiral stationary columns provides better performance in the resolution of enantiomers and regioisomers than reversed-phase chromatography. However, the direct introduction of hexane (a common solvent for normal-phase chromatography) into an APCI source may pose safety concerns [54]. In addition, the postcolumn addition of ammonium acetate buffer in ethanol–water (to allow for the detection of ammonium adducts) was frequently needed for chiral normalphase chromatographic separation because of the incompatibility of electrospray with n-hexane [55]. The APPI source is compatible with normal-phase chromatographic conditions and should therefore be the ideal candidate for normal-phase chiral HPLC–MS/MS systems needed for the enantiometric determination of some drugs. The potential of using APPI as an interface for chiral HPLC–MS/MS is shown in Figure 9.14, which shows the chiral HPLC–APPI/MS/MS chromatograms under isocratic separation with a hexane–ethanol (80:20) mobile phase and a Chiralcel OD-H column containing cellulose tris(3,5 dimethylphenyl carbamate) as a chiral selector for the determination of propanolol mixtures. The chiral HPLC system based on

Figure 9.14 The reconstructed HPLC–APPI/MS/MS chromatogram of standard (R)- and (S)-propranolol hydrochloride isomers. Conditions: Chiralcel OD-H column, mobile phase of hexane:ethanol (80:20, v/v), flow rate 0.7 mL/min, room temperature.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 271/276

APPI: A New Ionization Source for LC–MS/MS Assays

271

Figure 9.15 The reconstructed HPLC–APPI/MS/MS chromatogram of two drug discovery stereoisomeric compounds. Conditions: Chiralcel OD-H column, mobile phase of hexane with decreasing ethanol ratio at a constant flow rate of 0.7 mL/min and room temperature.

isocratic normal phase chromatography was strictly coupled to a PE SCIEX API 3000 tandem mass spectrometer with an APPI interface in the positive ion mode. The chiral HPLC–APPI/MS/MS method using the Chiralcel OD-H column was developed in our laboratory was then tested for two stereoisometric drug discovery compounds containing a hydroxyl group in an asymmetric center. The selected reaction monitoring (SRM) mode ion chromatograms given in Figure 9.15 indicate that the resolution power of chiral separation for the racematic mixtures tested could be strongly affected by several parameters including the mobile phase composition. Interestingly, we observed that there was a marginal effect on the ionization efficiency of the test compounds under normal phase conditions (ethanol/hexane ¼ 20/80) with or without the presence of dopant. This may be explained due to the selfdoping effect where hexane (IE ¼ 10.13 eV) can generate protonated solvent molecules through proton transfer mechanisms. APPI–MS has also been coupled with supercritical fluid chromatography (SFC), a normal-phase chromatographic technique for rapid separation of nonpolar, hydrophobic compounds that are challenging to ionize with two common ionization sources, ESI and APCI [43]. In a comparative study with a SFC–APCI/MS method, the authors observed a 10,000-fold increase in the signal-to-noise ratio for steroids, cortisone, and cortisol with the SFC–APPI/ MS method using an Agilent MSD instrument. In addition, a normal-phase HPLC–APPI/MS/MS method was applied to detecting hydrophobic peptide mixtures that are not easily ionized either by ESI or by matrix-assisted laser desorption ionization (MALDI) interfaces [56]. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 272/276

Using Mass Spectrometry for Drug Metabolism Studies

272

9.4

Conclusions and Future Perspectives

By the combination of liquid-based chromatographic separations with atmospheric pressure ionization techniques coupled to a tandem mass spectrometer it is possible to analyze several hundreds of compounds within a single day. HPLC–API/MS/MS technology offers straightforward method development for the characterization of drug compounds in biological samples and undoubtedly will continue to be important for the analysis of pharmaceuticals. APPI, a complementary ionization technique for LC–MS, may outperform other ionization modes such as ESI and APCI for bioanalysis of less polar, more hydrophobic components which are difficult to ionize with either APCI or ESI [27]. The use of an appropriate dopant substantially offers a means of enhancing the photoionization efficiency for reversed-phase HPLC–MS but provides a marginal effect on the sensitivity under normal phase conditions. The APPI sensitivity is dependent on ion–molecule reactions in the gas phase that are largely governed by the proton affinity of the analytes. The major processes leading to ionization in APPI are proton transfer and charge exchange in the positive ion mode. The APPI technique is in its infancy and there is still much interesting science left to do in terms of understanding how to utilize it in the best way. It is believed that a better understanding of the fundamental processes of APPI will continue to improve its performance. In addition, future instruments will be equipped with combined ionization sources, including at least two of the following: ESI, APCI, and APPI. Finally, miniaturation of ionization devices will be seen as well as smaller chromatography systems and mass spectrometers.

References 1. Oka, H. et al. Mass spectrometric analysis of tetracycline antibiotics in foods, J. Chromatogr. A, 812(1–2), 309, 1998. 2. Maurer, H.H., Liquid chromatography–mass spectrometry in forensic and clinical toxicology, J. Chromatogr. B, Biomed. Sci. Appl., 713(1), 3, 1998. 3. Pico, Y. et al. Pesticide residue determination in fruit and vegetables by liquid chromatography–mass spectrometry, J. Chromatogr. A, 882(1–2), 153, 2000. 4. Willoughby, R., Sheehan, E., and Mitrovich, S., A Global View of LC/MS. Global View Publishing, Phildelphia, PA, 2002. 5. Niessen, W.M., Advances in instrumentation in liquid chromatography–mass spectrometry and related liquid-introduction techniques, J. Chromatogr. A, 794(1–2), 407, 1998. 6. Niessen, W.M., Progress in liquid chromatography–mass spectrometry instrumentation and its impact on high-throughput screening, J. Chromatogr. A, 1000(1–2), 413, 2003. 7. Hayen, H. and Karst, U., Strategies for the liquid chromatographic–mass spectrometric analysis of non-polar compounds, J. Chromatogr. A, 1000(1–2), 549, 2003. 8. Gelpi, E., Interfaces for coupled liquid-phase separation/mass spectrometry techniques. An update on recent developments, J. Mass Spectrom., 37(3), 241, 2002.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 273/276

APPI: A New Ionization Source for LC–MS/MS Assays

273

9. Blakley, C.R., McAdams, M.J., and Vestal, M.L., Crossed-beam liquid chromatograph–mass spectrometer combination, J. Chromatogr., 158, 261, 1978. 10. Yamane, M., Simultaneous quantitative determination method for ceramide species from crude cellular extracts by high-performance liquid chromatography–thermospray mass spectrometry, J. Chromatogr. B, Anal. Technol. Biomed. Life Sci., 783(1), 181, 2003. 11. Eriksson, B. et al. Metabolic fate of delmopinol in man after mouth rinsing and after oral administration, Xenobiotica, 30(2), 179, 2000. 12. Byrd, G.D. et al. Determination of nicotine N-1-glucuronide, a quaternary N-glucuronide conjugate, in human biological samples, Drug Metabol. Drug Interact., 16(4), 281, 2000. 13. Pawlosky, R.J., Flanagan, V.P., and Novotny, J.A., A sensitive procedure for the study of beta-carotene-d8 metabolism in humans using high performance liquid chromatography–mass spectrometry, J. Lipid Res., 41(6), 1027, 2000. 14. Wolff, J.C. et al. The use of particle beam mass spectrometry for the measurement of impurities in a nabumetone drug substance, not easily amenable to atmospheric pressure ionisation techniques, Rapid Commun. Mass Spectrom., 15(4), 265, 2001. 15. Heimark, L. et al. Mechanism of azole antifungal activity as determined by liquid chromatographic/mass spectrometric monitoring of ergosterol biosynthesis, J. Mass Spectrom., 37(3), 265, 2002. 16. Yang, Y. et al. Analysis of bile acids and bile alcohols in urine by capillary column liquid chromatography–mass spectrometry using fast atom bombardment or electrospray ionization and collision-induced dissociation, Biomed. Chromatogr., 11(4), 240, 1997. 17. Itagaki, Y. et al. Detection of new spider toxins from a Nephilengys borbonica venom gland using on-line mu-column HPLC continuous flow (FRIT) FAB LC/ MS and MS/MS, Nat. Toxins, 5(1), 1, 1997. 18. Huang, E.C. et al. Atmospheric pressure ionization mass spectrometry, Anal. Chem., 62, 713A, 1990. 19. Cox, K.A., White, R.E., and Korfmacher, W.A., Rapid determination of pharmacokinetic properties of new chemical entities: in vivo approaches, Comb. Chem. High Throughput Screen., 5(1), 29, 2002. 20. Hirabayashi, A., Sakairi, M., and Koizumi, H., Sonic spray ionization method for atmospheric pressure ionization mass spectrometry, Anal. Chem., 66, 4557, 1994. 21. Hirabayashi, A., Sakairi, M., and Koizumi, H., Sonic spray mass spectrometry, Anal. Chem., 67(17), 2878, 1995. 22. Dams, R. et al. Influence of the eluent composition on the ionization efficiency for morphine of pneumatically assisted electrospray, atmospheric-pressure chemical ionization and sonic spray, Rapid Commun. Mass Spectrom., 16(11), 1072, 2002. 23. Robb, D.B., Covey, T.R., and Bruins, A.P., Atmospheric pressure photoionization: an ionization method for liquid chromatography–mass spectrometry, Anal. Chem., 72(15), 3653, 2000. 24. de Wit, J.S.M. and Jorgenson, J.W., Photoionization detector for open-tubular liquid chromatography, J. Chromatogr. A, 411, 201, 1987. 25. Evans, M.D. and Hanold, K.A., Photoionization mass spectrometry, Am. Laboratory, 32, 24, 2000. 26. Syage, J.A. and Evans, M.D., Photoionization mass spectrometry, Spectroscopy, 16, 14, 2001.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 274/276

274

Using Mass Spectrometry for Drug Metabolism Studies

27. Raffaelli, A. and Saba, A., Atmospheric pressure photoionization mass spectrometry, Mass Spectrom. Rev., 22(5), 318, 2003. 28. Kauppila, T.J. et al. Atmospheric pressure photoionization mass spectrometry. Ionization mechanism and the effect of solvent on the ionization of naphthalenes, Anal. Chem., 74(21), 5470, 2002. 29. Hsieh, Y. et al. High-performance liquid chromatography–atmospheric pressure photoionization/tandem mass spectrometric analysis for small molecules in plasma, Anal. Chem., 75(13), 3122, 2003. 30. Rauha, J.P., Vuorela, H., and Kostiainen, R., Effect of eluent on the ionization efficiency of flavonoids by ion spray, atmospheric pressure chemical ionization, and atmospheric pressure photoionization mass spectrometry, J. Mass Spectrom., 36(12), 1269, 2001. 31. Alary, J.F., Comparative study: LC–MS/MS analysis of four steroid compounds using a new photoionization source and a conventional APCI source. In 49th ASMS Conference on Mass Spectrometrty and Allied Topics, Chicago, IL, 2001. ASMS. 32. Yang, C. and Henion, J., Atmospheric pressure photoionization liquid chromatographic–mass spectrometric determination of idoxifene and its metabolites in human plasma, J. Chromatogr. A, 970(1–2), 155, 2002. 33. Alary, J.F. et al. Comparative LC–MS/MS analysis of four neurosteroid compoundsand their acetyl-pentafluorobenzyl derivatives using a photoionization ion source and a conventional atmospheric-pressure chemical ionization source. In 50th ASMS Conference on Mass Spectrometry and Allied Topics, Orlando, FL, 2002. ASMS. 34. Leinonen, A., Kuuranne, T., and Kostiainen, R., Liquid chromatography/mass spectrometry in anabolic steroid analysis—optimization and comparison of three ionization techniques: electrospray ionization, atmospheric pressure chemical ionization and atmospheric pressure photoionization, J. Mass Spectrom., 37(7), 693, 2002. 35. Keski-Hynnila, H. et al. Comparison of electrospray, atmospheric pressure chemical ionization, and atmospheric pressure photoionization in the identification of apomorphine, dobutamine, and entacapone phase II metabolites in biological samples, Anal. Chem., 74(14), 3449, 2002. 36. Miller, C.A., Cormia, P.H., and Fischer, S.M., Atmospheric pressure photoionization ion trap analysis of fat-soluble vitamins. In 49th ASMS Conference on Mass Spectrometry and Allied Topics, Chicago, IL, 2001. ASMS. 37. Lytle, C.A., van Berkel, G.J., and White, D.C., Comparison of atmospheric pressure photoionization and atmospheric pressure chemical ionization for the analysis of ubiquinones and menaquinones. In 49th ASMS Conference on Mass Spectrometry and Allied Topics, Chicago, IL, 2001. ASMS. 38. Impey, G., Kieser, B., and Alary, J.F., The analysis of polycyclic aromatic hydrocarbons (PAHs) by LC/MS/MS using a new atmospheric pressure photoionization source. In 49th ASMS Conference on Mass Spectrometry and Allied Topics, Chicago, IL, 2001. ASMS. 39. Takino, M., Daishima, S., and Nakahara, T., Determination of perfluorooctane sulfonate in river water by liquid chromatography/atmospheric pressure photoionization mass spectrometry by automated on-line extraction using turbulent flow chromatography, Rapid Commun. Mass Spectrom., 17(5), 383, 2003.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 275/276

APPI: A New Ionization Source for LC–MS/MS Assays

275

40. Takino, M., Daishima, S., and Nakahara, T., Liquid chromatography/mass spectrometric determination of patulin in apple juice using atmospheric pressure photoionization, Rapid Commun. Mass Spectrom., 17(17), 1965, 2003. 41. Takino, M., Daishima, S., and Nakahara, T., Determination of chloramphenicol residues in fish meats by liquid chromatography–atmospheric pressure photoionization mass spectrometry, J. Chromatogr. A, 1011(1–2), 67, 2003. 42. Helias, N. and Cepa, S., Charaterization and optimization of an atmospheric pressure photoionization (APPI) interface for routine use in drug discovery and development. In 51st ASMS Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, 2003. ASMS. 43. Quenzer, T.L. et al. Atmospheric pressure photoionization mass spectrometry: high throughput applications. In 51st ASMS Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, 2003. ASMS. 44. McKenzie, D.E. and McDermott, L.L., LC–MS investigation of atmospheric pressure photoionization versus electrospray ionization and atmospheric pressure chemical ionization using eleven test compounds. In 51st ASMS Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, 2003. ASMS. 45. Mei, H. et al. Investigation of matrix effects in bioanalytical high-performance liquid chromatography/tandem mass spectrometric assays: application to drug discovery, Rapid Commun. Mass Spectrom., 17(1), 97, 2003. 46. Matuszewski, B.K., Constanzer, M.L., and Chavez-Eng, C.M., Matrix effect in quantitative LC/MS/MS analyses of biological fluids: a method for determination of finasteride in human plasma at picogram per milliliter concentrations, Anal. Chem., 70(5), 882, 1998. 47. Hsieh, Y. et al. Quantitative screening and matrix effect studies of drug discovery compounds in monkey plasma using fast-gradient liquid chromatography/tandem mass spectrometry, Rapid Commun. Mass Spectrom., 15(24), 2481, 2001. 48. Hsieh, Y. et al. Simultaneous fast HPLC–MS/MS analysis of drug candidates and hydroxyl metabolites in plasma, J. Pharm. Biomed. Anal., 33(2), 251, 2003. 49. Hsieh, Y. et al. Simultaneous determination of a drug candidate and its metabolite in rat plasma samples using ultrafast monolithic column high-performance liquid chromatography/tandem mass spectrometry, Rapid Commun. Mass Spectrom., 16(10), 944, 2002. 50. King, R. et al. Mechanistic investigation of ionization suppression in electrospray ionization, J. Am. Soc. Mass Spectrom., 11(11), 942, 2000. 51. Dunlap, C.J. et al. Zirconia stationary phases for extreme separations, Anal. Chem., 73(21), 598A, 2001. 52. Thompson, J.D. and Carr, P.W., High-speed liquid chromatography by simultaneous optimization of temperature and eluent composition, Anal. Chem., 74(16), 4150, 2002. 53. Hsieh, Y., Merkle, K., and Wang, G., Zirconia-based column high performance liquid chromatography/atmospheric pressure photoionization tandem mass spectrometric analyses of drug molecules in rat plasma, Rapid Commun. Mass Spectrom., 17, 1775, 2003. 54. Ceccato, A. et al. Enantiomeric determination of tramadol and its main metabolite O-desmethyltramadol in human plasma by liquid chromatography– tandem mass spectrometry, J. Chromatogr. B, Biomed. Sci. Appl., 748(1), 65, 2000.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-09.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 276/276

276

Using Mass Spectrometry for Drug Metabolism Studies

55. Zavitsanos, A.P. and Alebic-Kolbah, T., Enantioselective determination of terazosin in human plasma by normal phase high-performance liquid chromatography–electrospray mass spectrometry, J. Chromatogr. A, 794(1–2), 45, 1998. 56. Delobel, A. et al. Characterization of hydrophobic peptides by photoionization– mass spectrometry and tandem mass spectrometry. In 51st ASMS Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, 2003. ASMS.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 277/304

Chapter 10 Q Trap MS: A New Tool for Metabolite Identification Ge´rard Hopfgartner and Manfred Zell

10.1

Introduction

Liquid chromatography coupled with tandem mass spectrometry (LC–MS/ MS) has emerged as a sensitive, rapid, robust, and highly automated technique for the quantification1 and characterization2 of pharmaceutical compounds and their metabolites. The screening and identification of drug metabolites in biological matrices is an important aspect in the discovery phase and in early drug development in order to elucidate the biotransformation products of a drug after it is dosed into laboratory animals. This knowledge helps to avoid the development of a drug where its metabolites may exert adverse toxicological effects or exhibit unwanted pharmacodynamic or pharmacokinetic properties. Metabolism is generally classified as an oxidative, reductive or hydrolytic process (phase I) and also has a conjugation phase involving glucuronidation, sulfatation, and glutathione formation (phase II). Preliminary metabolism information can be obtained in vitro by incubation of microsomes or hepatocytes or in an isolated perfused liver experiment. However, incubations are static systems and the in vitro findings need to be confirmed by in vivo studies. The key task is to find and identify metabolites in complex biological matrices using nonradiolabeled drugs. LC–MS/MS is the most widely used 0-8493-1963-3/05/$0.00+$1.50 ß 2005 by CRC Press

Copyright © 2005 CRC Press, LLC

277

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 278/304

278

Using Mass Spectrometry for Drug Metabolism Studies

technique for drug metabolite identification providing molecular weight and structural information mediated by collision induced dissociation experiments. Another important aspect is sample throughput. In vitro samples can be generated very rapidly and large numbers of samples have to be analyzed in a short time. Ideally, the metabolic findings should be generated in such a way that they might have some impact on the chemical synthesis program for optimizing the biological properties of a drug. Metabolite screening and identification in the drug discovery phase and the early phase of drug development requires mass spectrometric detection with the following features: high sensitivity, high selectivity, MS/MS and MSn capabilities, and accurate mass measurements (for more on metabolite identification, see Chapter 8). Currently, there is no single mass spectrometer that provides all these capabilities. Therefore, it is essential to use complementary analytical systems. Commonly used mass analyzers are triple quadrupole (QqQ), ion trap (IT), and hybrid quadrupole time-of-flight (QqTOF) mass spectrometers.3 Conventional ion trap mass spectrometers operate with a three-dimensional quadrupole field. High sensitivity can be obtained in full scan mode due to the ability of ion accumulation before mass analysis. Due to the small volume, 3-D ion traps have a limited capacity for ion storage. Overfilling of the ion storage device results in a deterioration of the mass spectrum and the dynamic response range. The number of ions introduced in the trap can be controlled in different ways to avoid space charging. In a linear 2-D trap, there is no quadrupole field along the z-axis. In contrast to the 3-D trap where ions are focused in a small spherical volume (<2 mL), ions in a 2-D trap are focused in a cylindrical volume alongside the center line (z-axis) of the quadrupole which allows the system to store more ions before observing space charge. Linear ion traps have been successfully coupled to time-of-flight mass spectrometer (LIT-TOF-MS) systems4 and Fourier transform ion cyclotron (FTICR) mass spectrometer systems.5 The intention of such hybrid instruments is to combine both ion accumulation and MSn features with the superior mass analysis (accuracy and resolution) and high sensitivity of TOF-MS or FTICR–MS. The ions stored in the trap are axially ejected to the mass analyzer in a non-mass dependent fashion. Very recently linear ion traps have emerged as a mass analyzer either as a hybrid device combined with a triple quadrupole (QqLIT) mass analyzer6 (Figure 10.1) or as a standalone single quadrupole ion trap (LIT)7 (Figure 10.2). Mass analysis with the standalone LIT is performed by ejecting the ions radially through slits of the rods using the mass instability mode. The QqLIT operates Q3 either as a conventional RF/DC quadrupole mass filter or a linear ion trap with axial mass ejection. The LIT differs from the classical 3-D ion trap (IT) by having enhanced sensitivity, resolution and dynamic range; the QqLIT combines these features with the additional ability to perform completely new scan combinations while still providing the classical features of both types of mass analyzers (i.e., a triple quadrupole MS and an ion trap MS system). This chapter will exclusively focus on the application of Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 279/304

Q Trap MS: a New Tool for Metabolite Identification

279

Figure 10.1 Schematic of the Q trap.

Figure 10.2 Schematic of the Finnigan LIT. (Source: Schwartz, J.C., J. Am. Soc. Mass Spectrom., 13, 659, 2002. With permission.)

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 280/304

Using Mass Spectrometry for Drug Metabolism Studies

280

the QqLIT. Its use for drug metabolism will be demonstrated based on published literature and studies with two pharmaceutical compounds, tolcapone and compound A. The metabolism of tolcapone has been extensively investigated using classical LC–MS approaches while compound A is a discovery compound were the QqLIT was used to support clinical candidate selection.

10.2

Review of Recent Literature

The QqLIT is based either on an API 2000 or an API 4000 triple quadrupole platform (Q TRAP, AB/MDS Sciex) (Figure 10.1). All specific scan functions of the triple quadrupole such as constant neutral loss (CNL), precursor ion scan (PC) or selected reaction monitoring (SRM) mode are maintained along with the trap scan modes (Figure 10.1). In the Q3 trap mode (enhanced single MS or EMS) the ions generated at atmospheric pressure are pulsed out from q0, pass through Q1 and the pressurized q2 quadrupole, and are trapped in Q3 by the RF voltage in the radial direction and by the DC biased aperture plates. In Q3 the trapped ions are cooled, typically in 10–30 ms. The energy in q2 is set in such a way that no fragmentation occurs during the passage of the ions. Trap fill times are in the range of 1 to 500 ms. Fringe fields caused by the lenses at the end of the quadrupole, which are considered as detrimental in the LIT, are exploited to eject mass-selectively the trapped ions in an axial fashion. Therefore, the same mass spectrometer can be used in the QqQ or QqLIT mode or can be switched from one mode to the other in milliseconds (ms). The QqLIT is calibrated for three scan rates: 250, 1000, and 4000 Th/s (where Th is Thompson) and the mass resolution is dependent on the scan speed. Typical mass resolution values are: 0.1–0.2 Th (FWHM) at 250 Th/s, 0.3–0.5 Th at 1000 Th/s and 0.5–0.7 Th at 4000 Th/s. The mass range is 50–1700 Th and 80–2800 Th for the Q Trap 2000 and the Q Trap 4000, respectively. The Q Trap 2000 and the Q Trap 4000 have completely different ion source designs and the second one is able to sample much more ions. The major difference between the two instruments is the better sensitivity for the Q Trap 4000 compared for the Q Trap 2000 in SRM, PC, and CNL scan modes. For the Q Trap 4000 no significant difference in signal-to-noise ratio (S/N) is observed between the standard Q3 mode and the EMS mode except the faster scan and the enhanced resolution. The big difference between the QqLIT and a standalone IT device is the MS/MS mode. With the QqLIT, MS/MS (enhanced product ion or EPI) is performed as follows: (1) isolation of the precursor ion is performed in Q1 utilizing RF/DC at any resolution; (2) collision-induced dissociation (CID) occurs in the collision cell (q2) that is filled with nitrogen; and (3) fragment ions are trapped in Q3. RF/DC isolation8 has a significant advantage over an isolation waveform (used in the IT) where for isolation of fragile ions, elimination of the precursor ion can be observed.9 In a quadrupole collision cell, the ions undergo multiple collisions producing fragment ions. As soon as Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 281/304

Q Trap MS: a New Tool for Metabolite Identification

281

the fragment ions are formed they become reactivated and can undergo further fragmentation. On the other hand, fragmentation with an IT occurs solely by excitation of the precursor ion. In most cases, product ions are too cool to fragment further, and therefore, require specific excitation, which is done using the MS3 and MS4 modes. Typically ITs have a low mass cut-off in MSn mode which corresponds, as a rule of thumb, to about one third of the mass of the precursor ion. With the QqLIT the precursor ion is fragmented in the quadrupole collision cell q2. Therefore a product ion spectrum can be obtained without the low mass cut-off issue. However, to obtain a full scan mass spectrum over the complete mass range starting at m/z 50 Th, the trapping of the fragments ions and sequential mass analyzing has to be performed in time segments which affects duty cycle. The time limiting factor is the trap filling time. The QqLIT has also MS3 capability which is performed in the following manner: (1) the first stage of fragmentation is accomplished by accelerating the precursor ions chosen by Q1 into the pressurized collision cell, q2; (2) the resulting fragment ions and residual precursor ions are transmitted into the Q3 linear ion trap quadrupole and are cooled for approximately 10 ms; (3) the next generation precursor ion is isolated within the linear ion trap by application of resolving DC near the apex of the stability diagram at q
0.706; (4) the RF voltage of the linear ion trap is adjusted such that the isolated ions are at a q-value of 0.238 where they are excited by a single frequency of 85 kHz auxiliary signal and fragmented to produce the MS3 ions. This auxiliary signal is user controllable up to 200 mVp-p for a duration of up to 200 ms. Figure 10.3(A) shows the quadrupole product ion spectrum in the trap mode (EPI) for trocade where many fragment ions are observed down to m/z 86. Therefore, no low mass cut-off is observed with the QqLIT system as compared to LIT system. An ion trap like (MS2) spectrum can also be generated with QqLIT where the collision energy of q2 is set such that no fragmentation occurs in q2. In this case a low mass cut-off (about 1/3 of the mass of the precursor ion) would be observed. The fragmentation of trocade has been investigated and is presented in detail elsewhere.10 Figure 10.3(B to E) shows the MS, MS2, MS3, and MS4 spectra of trocade, respectively. As expected, the fragmentation pathway can be elegantly followed, but sensitivity is lost at each step. The QqLIT does not have MS4 features. Actually, this is not implicitly necessary because quadrupole CID spectra are very informative. On the other hand the fragmentation pathway can also be established when combining quadrupole CID with MS3 spectra. The QqLIT also has two new unique scan functions, which are the enhanced multi-charged scan (EMC) and the time delayed fragmentation (TDF).11 EMC allows the removal of singly charged ions from the LIT; this scan function is mainly designed for proteomics applications. TDF is particularly interesting for small molecules because it allows the reduction of sequential fragmentation leading to more simple spectra.11 It is a three-step process including ion activation, ion relaxation, and fragment collection. In contrast to classical triple quadrupole ion activation, in this case, ion activation occurs via q2-to-Q3 acceleration Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 282/304

282

Using Mass Spectrometry for Drug Metabolism Studies

Figure 10.3 Product ion mass spectra of trocade, comparison QqLIT and IT. (Adapted from Hopfgartner G., J. Mass Spectrom., 38(2), 138, 2003. With permission.)

rather than via Q1-to-q2 acceleration. The product ion spectra originate from a precursor ion which has a modified internal energy based on time delay. This is achieved by collecting the precursor ions in the trap while fragment ions outside a given mass range are not trapped. After a cooling period, typically in the range of milliseconds, the trap is adjusted such that it can now trap the fragment ions originating from the cooled precursor ions (Q3 fill mass). Therefore, TDF can be applied to determine the origin of secondary fragment ions by changing the Q3 fill mass. This is nicely illustrated in Figure 10.4 showing the TDF spectra of bosentan recorded with different Q3 fill masses (200 and 400 Th). The principal difference between the two spectra is the strong decrease of the ion at m/z 280 Th for the Q3 fill mass of 400 Th. This implies that the ion at m/z 280 Th is a second generation ion. It is known that the fragment at m/z 280 Th originates from the ion at m/z 311 Th through the loss of a CH3O radical, which is also confirmed with the TDF experiment.12 To increase throughput in drug metabolism the use of informationdependent acquisition (IDA) becomes very important. IDA is a procedure that combines two or more different scan modes in a sequential fashion for the same LC–MS run. The first scan is defined as the survey scan where data are processed on the fly to determine the candidates of interest based on predefined selection criteria. If the selection criteria are met a second scan (data dependent) is then performed. A typical IDA experiment is to perform full scan single MS as a survey scan and then MS/MS as a dependent scan. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 283/304

Q Trap MS: a New Tool for Metabolite Identification

283

Figure 10.4 Time delayed fragmentation spectra of bosentan. (Source: Hager, J.W., Rapid Commun. Mass Spectrom., 17(13), 1389, 2003. With permission.)

Table 10.1 Summary of information dependent acquisition scan combinations with the QqLIT Scan combination

Analysis type

Specificity

Comments

Screening

High sensitivity but poor selectivity

CNL–ER–EPI–MS3

Screening

High selectivity, moderate sensitivity with CNL

PC–ER–EPI–MS3

Screening

High selectivity, moderate sensitivity with CNL

EPI (N)

Target analysis

Up to up 8 simultaneous EPI experiments are possible

SRM–EPI

Target analysis and confirmatory analysis

High sensitivity and selectivity

With dirty samples requires inclusion and exclusion lists Requires an understanding of the fragmentation process Requires an understanding of the fragmentation process The mass of the precursor is predicted when phase I and phase II metabolism are known Up to 50 SRM transitions can be defined

EMS–EPI–MS

3

This type of experiment can also be performed on most tandem MS instruments. Unlike the 3-D trap, the QqLIT retains the traditional triple quadrupole scan modes such as selected reaction monitoring (SRM) mode, constant neutral loss (CNL) scan or precursor ion scan (PC). The use of these scan functions as survey scans is a particularly interesting way to achieve better selectivity. The various common scan combinations in the IDA mode are summarized in Table 10.1. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 284/304

284

Using Mass Spectrometry for Drug Metabolism Studies

Figure 10.5 EMS–EPI–MS3 Analysis of gemfibrozil. (Source: Xia, Y.-Q., Rapid Commun. Mass Spectrom., 17(11), 1137, 2003. With permission.)

The analysis of radiolabeled gemfibrozil in human liver microsomes fortified with NADPH and UDPGA using an EMS–EPI–MS3 IDA experiment was performed by Xia et al.13 and is illustrated in Figure 10.5. It is noteworthy that such an experiment can also be performed on a 3-D IT. However, one of the benefits of the QqLIT versus the IT is speed and the minimized space charge effects due to the selection of the precursor ion in the first quadrupole. Using this approach, five metabolites of gemfibrozil could be identified in one single LC–MS analysis. An IDA experiment was performed, using two looped neutral loss scans as survey scans to trigger MS2 and MS3 dependent scans. The neutral loss of 176 Da (specific for glucuronide) and 128 Da (specific for modification on the benzyl moiety) were used to detect phase I and phase II metabolites. The sensitivity of the Q Trap for quantification was also evaluated using the SRM and EPI modes for the determination of propanolol in rat plasma. Owing to the higher capacity of the LIT, the linear dynamic range was found to be Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 285/304

Q Trap MS: a New Tool for Metabolite Identification

285

up to 3 orders of magnitude without ion gating. Similar dynamic ranges were observed for both modes. The EPI mode was found to be slightly less sensitive than the SRM mode. The sensitivity of quantitation on the Q Trap was compared to that of the LCQ Deca and similar results were reported.13 The critical issue with an IDA experiment is full scan MS, which is inherently nonselective. An increase in sensitivity in the full scan MS mode does not necessarily significantly improve the ability to find metabolites in biological samples because the signals of the background or interfering endogenous compounds increase in-line with the metabolites. This is nicely illustrated in Figure 10.6 which shows the LC–MS analysis of remikiren (MW ¼ 630 Da) in rat hepatocytes using either EMS or PC as survey scan and EPI as dependent scan. The purpose of this analysis was to find phase I metabolites such as the hydroxylate metabolite (MW ¼ 646 Da) of remikiren. The EMS total ion current (TIC) trace does not provide any relevant information (see Figure 10.6(A)). When extracting m/z 647 Th, a small peak is observed at RT ¼ 3.2 min and the EMS spectrum is illustrated in Figure 10.6(B). In an IDA experiment, generally the most abundant ion of the survey scan is chosen to perform the dependent scan, in this case EPI. It is obvious that in this case it is almost impossible to properly select a

Figure 10.6 Comparison EMS–EPI and PC–EPI analysis of remikiren in rat hepatocytes. (A) EMS TIC, (B) EMS spectrum of RT ¼ 3.2 min, (C) PC TIC, (D) EPI spectrum of peak at RT ¼ 3.2 min of precursor ion at m/z 647 Th.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 286/304

286

Using Mass Spectrometry for Drug Metabolism Studies

precursor ion. The use of an inclusion list may help, but the utility of this type of scan is limited when the ratio of the background to the ion of interest is high. On the other hand, when using PC of a relevant fragment as the survey scan most of the observed peaks in the TIC are metabolites of remikiren (Figure 10.6(C)). Here the system can automatically select the precursor ion (m/z 647 Th) present in the TIC of the PC trace (data not shown) and generate an EPI spectrum (Figure 10.6(D)) corresponding to the terbutyl hydroxylation metabolite of remikiren. Nonlinearity is caused by space charge from overfilling the LIT. Compared to the 3-D trap, the linear range of the Q Trap is much larger, but for some applications it is still not sufficient. The use of a dynamic fill time (DFT) circumvents this overload problem. DFT performs a Q1 pre-scan (30 ms) to determine the effective ion load entering from the ion source. The fill time is then calculated to achieve the target TIC. Currently the minimum fill time is 1 ms. The effect of DFT on the dynamic range of the EPI scan is shown in Figure 10.7.14 CNL and PC functions do not have the sensitivity of the trap scan modes, which might be considered a severe drawback. In fact, they are only use as a filter to trigger the mass of the precursor ion for the EPI scan and in that case the sensitivity is considered to be acceptable. An alternative way to achieve higher sensitivity while still maintaining selectivity is to select SRM as a survey scan. Due to the fast duty cycle of SRM up to 50 SRM transitions can be monitored sequentially in one second.

Figure 10.7 Effect of dynamic fill time (DFT) in the dynamic range response (A) SRM (B) EPI with DFT (C) EPI without DFT.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 287/304

Q Trap MS: a New Tool for Metabolite Identification

10.3 10.3.1

287

Current Use of the Technology Screening of metabolites of tolcapone

Tolcapone (3,4-dihydro-40 -methyl-5-nitrobenzophenone) is a reversible orally active inhibitor of catechol-O-methyltransferase. The compound was developed for therapy in Parkinson’s disease. The metabolism of tolcapone has been described by Jorga et al.15 Tolcapone undergoes various phase I and phase II metabolism pathways as shown in Figure 10.8. Tolcapone shows moderate ion spray response in the negative ion mode and poor response in the positive ion mode. Chromatography was performed with various analytical columns such as Inertsil ODS-3 and Kromasil C18. The gradient consisted of aqueous 1% formic acid/methanol. The enhanced product ion mass spectra in positive and negative mode are illustrated in Figure 10.9(A and B), respectively. The fragmentation pathway of tolcapone in the positive ion mode is straightforward (Figure 10.10). In a first step, fragmentation occurs at the protonated molecule generating two fragment ions at m/z 182 Th and m/z 119 Th. The ion at m/z 182 Th undergoes further fragmentation to the ion at m/z 136 Th by the loss of a nitro radical. The further loss of carbon monoxide generates the

Figure 10.8 Metabolism of tolcapone in humans.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 288/304

288

Using Mass Spectrometry for Drug Metabolism Studies

Figure 10.9 Product ion spectra of tolcapone. (A) positive ion mode, (B) negative ion mode.

Figure 10.10 Postulated fragmentation pathway of tolcapone in positive ion mode.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 289/304

Q Trap MS: a New Tool for Metabolite Identification

289

Figure 10.11 TDF of tolcapone in positive ion mode, TDF CE 20 eV, Q3 cool time 1 ms. (A) Q3 fill mass 250 Th, (B) Q3 fill mass 160 Th.

fragment ion at m/z 108, corresponding to a radical cation. On the other side, the loss of a CO from the fragment ion at m/z 119 Th produces the tropylium ion at m/z 91 Th. The elemental formulae of the proposed fragments were confirmed by accurate mass measurements on a QqTOF II (Micromass) system. Like with 3-D trap the MS3 function of the QqLIT allows the user to follow the fragmentation cascade. The TDF spectra of tolcapone in the positive ion mode are shown in Figure 10.11. In Figure 10.11(A) the Q3 fill mass was m/z 260 Th showing only two fragments at m/z 119 and 182 Th, illustrating that these two ions were generated directly from the protonated molecule at m/z 274 Th. In Figure 10.11(B) the Q3 fill mass was set at m/z 160 Th and ions above this mass can undergo further fragmentation and are stored into the trap. By comparing the spectra from Figure 10.11(A and B) it can be concluded that the ions observed at m/z 136 Th and m/z 165 Th originated from the fragment ion at m/z 182 Th. These finding are also confirmed by MS3 experiments. TDF is certainly complementary to MS3 because fragmentation processes can be monitored more precisely; in addition, more experience needs to be gained in order to learn how to make the best use of this scan function. It appears that it may be difficult to use TDF in conjunction with HPLC, because the Q3 fill mass is strongly analyte dependent. In the negative ion mode, the spectral interpretation appears to be much more complex. Starting from the [M  H] ion at m/z 272 Th, a loss of the hydroxy radical (17 Th) or a nitroso radical (30 Th) is observed. Accurate mass Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 290/304

290

Using Mass Spectrometry for Drug Metabolism Studies

Figure 10.12 Postulated fragmentation pathway of tolcapone in negative ion mode.

measurements on a QqTOF along with MS/MS of structural analogs and MS3 were used to propose the fragmentation scheme depicted in Figure 10.12. The MS3 experiment of the fragment ion at m/z 255 Th generated the fragment ion at m/z 182 Th, while this was not observed with the precursor at m/z 225 Th (data not shown). Accurate mass data were also not satisfactory for this fragment suggesting an overlapping of isobaric fragments ions that caused some confusion. In biological fluids such as urine or plasma the EMS–EPI approach (single MS dependent mode) failed to find most of the known metabolites even when using inclusion lists. This was mainly due to poor electrospray response in the positive ion mode and moderate response in the negative ion mode for tolcapone and most of its metabolites. This observation was found to be quite general when the analyte of interest was hidden in the Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 291/304

Q Trap MS: a New Tool for Metabolite Identification

291

background of the total ion current trace due to low concentration or poor MS response of the analyte. In this case, most systems were not capable of properly selecting the precursor ion. Nitro catechol compounds are slightly acidic and thus require an acidic mobile phase to obtain a satisfactory chromatographic peak shape. To achieve this requirement, the mobile phase consisted of 1% aqueous formic acid/methanol allowing for detection in the positive ion mode and most surprisingly also in the negative ion mode. Notably, the signal observed in negative ion mode was similar to that from solutions at pH > 7. Another approach to finding metabolites is to perform simultaneous MS/ MS analysis of various postulated metabolites (targeted analysis). Targeted product ion analysis relies on the prediction of metabolic alterations on the basis of related drugs and knowledge of their metabolites. The molecular mass of the major phase I and phase II metabolites can be predicted; for example, the addition of 16 Th corresponds to an oxidation metabolite or the addition of 80 and 176 Th corresponds to a sulfate and a glucuronide conjugate, respectively. On a typical QqQ instrument, the duty cycle for a product ion spectrum is in the range of 1 s (500 Th/s) which allows, at best, the successive performance of about three product ion experiments in 3 s. Usually, to obtain a sufficiently complete picture, at least 30 predicted metabolites or metabolic alterations have to be looked for using targeted product ion analysis. Thus, many injections of the sample need to be performed and this may lead to rapid consumption of the sample. Ion traps are capable of scanning much faster than beam-type mass spectrometers. In the case of the QqLIT the fastest scan rate is 4000 Th/s. As discussed above, in contrast to a 3-D trap, MS/MS fragmentation is not performed in the trap, but in the collision cell, q2. This difference has an important impact on the duty cycle. With an injection time of 50 ms, a complete cycle lasts about 400 ms for a mass range from m/z 70 to m/z 600 Th. This allows the user to run six to eight EPI experiments during the time scale of a chromatographic peak with much better sensitivity (>50 times) than on a QqQ system while maintaining good chromatographic resolution due to sufficient data points per chromatographic peak. Targeted product ion analysis is illustrated in Figure 10.13(A and B) for the analysis of tolcapone and several of its metabolites in both the positive and negative ion modes. One of the key advantages of targeted product ion analysis over single MS dependent analysis is that minor metabolites can be selectively ‘‘fished out’’ from the whole bulk of endogenous compounds even when co-eluting with a major metabolite. Most MS instruments can perform LC–MS analysis in the positive and negative modes in the same run. In the case of the QqLIT, this can also be done, but it requires 700 ms additional cycle time. The targeted product ion analysis in the positive ion mode (Figure 10.14(A)) and negative ion mode (Figure 10.14(B)) was found to be a more successful approach to screen for metabolites of tolcapone in human urine as compared to the EMS–EPI approach. Figure 10.15(A) illustrates the EPI mass spectrum of the acid metabolite of tolcapone. The nitro function of tolcapone can undergo reduction to the corresponding amine followed by further acetylation. The product ion mass spectrum of this metabolite is depicted in Figure 10.15(B). Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 292/304

292

Using Mass Spectrometry for Drug Metabolism Studies

Figure 10.13 Targeted analysis of tolcapone and several metabolites (5 ng on-column). (A) negative ion mode, (B) positive ion mode.

Figure 10.14 Targeted analysis of a human urine (0–72 h) sample after administration of tolcapone. (A) negative ion mode, (B) positive ion mode.

In many projects it is of interest to perform sample analysis either in the positive or negative ion mode for sensitivity reasons. On the other hand, when a metabolite can be detected in both the positive and negative ion modes, the EPI spectra are generally complementary. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 293/304

Q Trap MS: a New Tool for Metabolite Identification

293

Figure 10.15 Enhanced product ion spectra: (A) peak 5 of Figure 10.14 corresponding to acid metabolite; (B) peak 7 of Figure 10.14 corresponding to the acetyl amine metabolite.

Phase II conjugates such as glucuronides and sulfates might be fragmented unintentionally to their aglycone by up-front CID. Therefore, special attention should be given to this issue. For example, the peak at 6.2 min (Figure 10.14(B)) gave a product ion spectrum of the amine tolcapone derivative (MW ¼ 243 Da). However, the synthetic reference showed that this metabolite eluted normally at about 3.8 min. Further investigation revealed that this metabolite was the sulfate conjugate of the amine tolcapone metabolite. Therefore, in targeted analysis consideration should always be given to phase II transitions of metabolites that require additional experiments and thus more injections of sample. There are two approaches to solve this issue. The first is to perform an IDA experiment where SRM is used as survey scan while EPI is the dependent scan. Due to the very short dwell time of SRM many transitions could be monitored in a single LC–MS/MS analysis. Regarding sample consumption and analysis time, this is a very efficient way for screening for metabolites, but unexpected metabolites may be missed. The second more general approach is to perform an IDA experiment where CNL is used as a survey scan and EPI as a dependent scan. Glucuronide, sulfate or glutathione metabolites generate very specific neutral losses (80 Th for sulfate, 176 Th for glucuronide and 129 Th for glutathione). The CNL TIC of glucuronide metabolites, either in the negative or positive ion mode, is illustrated in Figure 10.16(A and B). For the screening of phase II metabolites, two collision energies were used in the EPI mode (30 and 50 eV). Despite the selectivity provided by neutral loss, the CNL trace is overloaded with peaks. In the positive ion mode, the fragment at m/z 119 Th can be used as a marker, as shown in Figure 10.16(C). Five glucuronide metabolites could be easily Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 294/304

294

Using Mass Spectrometry for Drug Metabolism Studies

Figure 10.16 IDA experiment with CNL 176 as survey scan and EPI as dependent scan. (A) EPI trace negative ion mode, (B) EPI trace positive ion mode, (C) extracted ion current profile of (b) using m/z 119.

identified, corresponding to: (a) and (c) glucuronides of the N-acetylamino tolcapone metabolite; (b) glucuronide of the amine tolcapone metabolite; (d) glucuronide of tolcapone; and (e) glucuronide of the O-methyl tolcapone metabolite. The same metabolites could also be found in the negative ion mode. In the case of the N-acetylamino glucuronides, the EPI mass spectra either in the positive ion mode or the negative ion mode are identical with that of N-acetylamino tolcapone. The site of glucuronidation either in 3-O or 4-O position could not be localized by spectra interpretation. The CNL and EPI spectra in negative and positive mode of metabolite (e) (glucuronide of methoxy metabolite of tolcapone) are depicted in Figures 10.17 and 10.18. Tolcapone might be methylated either in position 3 or 4 of the catechol moiety. However, the catechol-O-methyltransferase (COMT) is selective for methylation in the 3 position of the catechol moiety! Not surprisingly, the 3-methoxy tolcapone metabolite was found to be the important metabolite in human plasma. Nevertheless, there should be evidence that exclusively methylation occurs at the 3 position of the catechol. The negative ion mode spectrum (Figure 10.17(C)) is not very conclusive for the distinction between the site of methylation, either at the 3-O or the 4-O position of the catechol. However, in the positive ion mode, there should occur a fragment ion of m/z 150 Th for 3-methoxy tolcapone, analogous to the fragmentation pathway of tolcapone. This would correspond to a shift of m/z 136 Th plus CH2 to give m/z 150 Th. Surprisingly, the mass fragment at m/z 150 Th could not be found in the EPI spectrum of the postulated glucuronide of 3-methoxy tolcapone (Figure 10.18(C)). This finding initiated the synthesis of 4-methoxy tolcapone. The comparison of the EPI spectra Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 295/304

Q Trap MS: a New Tool for Metabolite Identification

295

Figure 10.17 Mass spectra of peak 5 of Figure 10.15. Negative ion mode (A); CNL spectrum (B); EPI from precursor at m/z 462 Th, CE ¼ 30 eV (C). CE ¼ 50 eV.

Figure 10.18 Mass spectra of peak 5 of Figure 10.15 in positive ion mode (A); CNL spectrum (B); EPI from precursor at m/z 464 Th, CE ¼ 30 eV (C). CE ¼ 50 eV.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 296/304

296

Using Mass Spectrometry for Drug Metabolism Studies

Figure 10.19 EPI spectra of the 4- (A) and the 3- (B) O-Me metabolite in the positive ion mode.

of 4-methoxy tolcapone and 3-methoxy tolcapone are depicted in Figure 10.19(A and B), respectively. While for 3-methoxy tolcapone the fragment at m/z 150 Th is highly abundant, the same fragment is very minor for 4-methoxy tolcapone. Since the fragment ion at m/z 150 Th was missing in the EPI spectrum of Figure 10.18(C), evidence accumulated that the glucuronide of peak (e) corresponded to that of 4-methoxy tolcapone. Actually, this finding was in contrast to the notion that COMT is specific for the methylation of the catechol in the 3-position. However, since peak (e) (Figure 10.17(C)) was found to be a very minor metabolite there was no strong contradiction. It has to be mentioned that 3-glucuronidation is also preferred to 4-glucuronidation. Once the 3-position is blocked by a glucuronide, methylation becomes only possible at the cathecol on position 4. As a consequence of this finding, methylation mediated by COMT was found to be not specific, but highly selective. This was a favorable case for showing that one can sometimes distinguish between structural isomers by comparison of their EPI spectra. Rapid scanning in CNL or precursor ion mode (PC) (>500 Th/s) results in a significant shift of mass accuracy. In such a situation the selection of the precursor ion mass for the EPI experiment may be off by up to 0.5 Th. However, reducing the CNL or PC scan rate would result in much a longer duty cycle. An alternative to this is to add an enhanced resolution scan in between the CNL/PC and EPI scan for more accurate mass measurement and correct selection of the respective precursor ion. One of the well-characterized roles of glutathione (GSH) is the detoxification of xenobiotics. GSH adducts are often formed at very low concentrations and require extensive efforts to be detected by LC–MS. GSH adducts mostly undergo a very specific neutral loss (NL) of 129 Th in CID.16 The analysis of a tolcapone sample obtained from Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 297/304

Q Trap MS: a New Tool for Metabolite Identification

297

Figure 10.20 LC–MS analysis of tolcapone incubated in rat hepatocytes using an IDA experiment: (A) EMS, (B) EPI, (C) MS3.

incubation in rat hepatocytes was performed using CNL on a QqQ instrument and did show two peaks corresponding to protonated molecules at m/z 593 Th and 563 Th. However, the quality of the resulting product ion spectra was not sufficient to provide good structural information except for the loss of 129 Th. The same sample was run on the QqLIT using the following IDA experiment with an inclusion list: (1) EMS, (2) EPI, and (3) MS3 as illustrated in Figure 10.20. The duty cycle was 2.2 s. The product ion mass spectrum of the peak (g) with the precursor ion at m/z 563 Th is illustrated in Figure 10.21(A). The mass of metabolite (f) is 30 Th higher suggesting that for metabolite (g) the nitro group mass is reduced to the amine. The product ion mass spectrum of this metabolite confirms this finding as most higher masses are shifted by 30 Th (data not shown). It was postulated that both metabolites are glutathione conjugates (thioesters) of the acid metabolite of tolcapone and the acid form of the amine derivative of tolcapone. This hypothesis was further supported by the MS3 spectra of the precursor at m/z 331 Th (Figure 10.21(B)). Only a few thioesters of carboxylic acids have been reported17 and their relevance has not yet been sufficiently explored. 10.3.2

Screening of metabolites for discovery compound A

The selection of the most appropriate drug candidate in discovery and early nonclinical drug development demands the examination of pharmacological activity and toxicological findings as well as the evaluation of pharmacokinetic and metabolic properties of the drug. Therefore, it is highly desirable to Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 298/304

298

Using Mass Spectrometry for Drug Metabolism Studies

Figure 10.21 (A) Product ion mass spectrum of precursor ion at m/z 563 Th (peak g of Figure 10.20). (B) MS3 spectrum of precursor ion at m/z 331 Th.

elucidate the metabolic fate of the drug in in vitro experiments as well as in laboratory animals. Correlation of animal data with human microsomes, hepatocytes, and CYP 450 isoenzyme incubations should also be considered as early as possible in the development process. The analytical challenge is the identification of metabolites at the picogram level in samples from in vivo experiments mainly due to the limited volume of bioanalytical fluid available from small animals. Compound A (see Figure 10.22) was found to be one of a series of drug candidates identified in drug discovery for which its pharmacokinetic properties and metabolic pathway were selection criteria for further development. Owing to the early stage of drug development only plasma samples from low-dose pharmacokinetic trials in various animals were available for metabolic investigation. For this reason, even the major metabolites were expected to occur in plasma at the lower ng/mL concentration level. In drug metabolism it is of utmost importance to optimize sample treatment to avoid any loss of relevant metabolites. Losses of metabolites are caused primarily by an inappropriate clean-up procedure with respect to recovery or degradation of labile metabolites. Direct plasma injection (see Chapter 5 for more details on this subject) might ensure the complete transfer of metabolites onto an HPLC column, but the whole bulk of endogenous components of the sample could cause significant ion suppression (see Chapter 4 for more details on this subject) and thus poor sensitivity at least for some of the metabolites. The most straightforward, but nevertheless effective, clean-up procedure was found to be protein precipitation. To a Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 299/304

Q Trap MS: a New Tool for Metabolite Identification

299

Figure 10.22 EPI spectrum of compound A (MW ¼ 430 Da) at CE ¼ 50 eV.

50-mL plasma aliquot were added 100 mL of ethanol. Following vortexing and precipitation of proteins by centrifugation, the supernatant was further diluted 10-fold with 0.2% aqueous formic acid to reduce the elution strength of the sample. Just a 50-ml aliquot of the diluted supernatant was injected onto a trapping column (TC) (YMC AQ, dp 5 mm, 2.0 mm i.d.  10 mm) of an HPLC column-switching system. Thereafter, the retained analytes of interest were transferred in the backflush mode to the analytical column (XTerra MS C18, dp 3 mm, 1.0 mm i.d.  100 mm) using gradient elution with 5 mM ammonium formate/methanol. Owing to the lipophilic character of the parent drug the most relevant metabolites were expected to have moderate polarity, and therefore exhibit good retention on the TC. Even though the involved clean-up procedure diluted the metabolites of interest by a factor of 10, this was not found to be detrimental for the sensitive detection of the metabolites. The reason for that was as follows: if sensitivity was not sufficient, the columnswitching approach allowed the injection of up to a 500-mL supernatant aliquot onto the TC at a loading time of about 4 min when using a flow-rate of 0.5 mL/min. The EPI spectrum of compound A is shown in Figure 10.22. The peak at m/z 232 Th corresponds to a quaternary amine and is characteristic of the methyl-carbamic acid 4-trifluoromethyl-phenylester moiety of the molecule. MS3 fragmentation indicated that the peaks at m/z 175 and 145 Th originate from the precursor ion at m/z 232 Th. The fragment at m/z 175 Th (Figure 10.22) is produced by a re-arrangement reaction via a radical cation. On the other hand, the fragment at m/z 269 Th was formed by cleavage of the Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 300/304

300

Using Mass Spectrometry for Drug Metabolism Studies

carbamate ester ion, which is partially complementary to the fragment ion at m/z 232 Th. Assuming that the carbamate-phenylester moiety of the parent drug was not very prone to metabolic alteration, the fragments at m/z 175 and m/z 145 Th could be used for precursor ion scanning to find metabolites in biological fluids. Even metabolic transformation of the trifluoromethyl phenyl moiety via oxidation would not make this approach useless, provided the m/z value of the product ions were adjusted accordingly. The only shortcoming was the very moderate sensitivity of the precursor ion (PC) mode even though compound A elicited a good response in the positive ion mode with product ion scanning or SRM. The first approach used to identify the metabolites in biological fluids was to perform an IDA experiment with EMS as the survey scan and EPI as the dependent scan. Due to low concentrations of the metabolites in the sample and the inherent nonselectivity of EMS, only the parent drug, its glucuronide conjugate and a metabolite generated by oxidation of the parent drug could be found by this method. The second approach involved an IDA experiment with CNL of 176 Th as the survey scan and EPI as the dependent scan for screening for glucuronides. In this case, only the glucuronide of the parent drug could be identified. In a third run, targeted analysis with EPI using predicted precursor ions including oxidation, de-alkylation and glucuronidation was performed. The result was as follows: 11 metabolites could be identified at picogram amounts (on-column) with two chromatographic LC–MS/MS runs; three further glucuronide conjugates of metabolites could be unambiguously identified which had not been detected using the unique constant neutral loss scanning of a beam-type mass spectrometer, due to its moderate sensitivity in this mode. Chromatographic resolution remains very important for separating not only closely related metabolites, such as isobaric ones, but also metabolite conjugates from their respective metabolites. Metabolite conjugates always have the potential to degrade in the ion spray source due to their thermal liability or to the non-optimized orifice or skimmer voltages in the ion source. Up to six EPI experiments could be conducted concomitantly without compromising chromatographic resolution by maintaining at least 10 data points per chromatographic peak. Targeted analysis using EPI was found to be the most successful approach for the screening of metabolites at low ng/mL concentrations in biological fluids. However, IDA experiments with EMS–EPI, CNL–EPI and PC–EPI remain important to ensure that major unexpected metabolites are not overlooked. Another interesting approach to monitoring large numbers of metabolites at very low concentrations is to build an IDA experiment where SRM is selected as the survey scan. In the triple quadrupole mode, SRM provides very short duty cycles down to 10 to 50 ms without comprising sensitivity too much. Sensitivity with a short duty cycle in SRM is only affected by the increase in background signal. Therefore, SRM would be the ideal survey scan in combination with EPI if it were not for the challenge of predicting the right transitions of unknown metabolites. In our case, the product ions at m/z 175 and 145 Th can be regarded as characteristic fragments of the parent drug (compound A) but also of its metabolites. Therefore, the Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 301/304

Q Trap MS: a New Tool for Metabolite Identification

301

Figure 10.23 LC–MS/MS analysis of dog plasma sample, taken 4 h after multiple p.o. administration of 30 mg/kg in IDA mode (A); 14 SRM transitions (B). TIC of the EPI traces at a CE of 40 eV.

transitions can be composed of the precursor ion (predicted molecular mass) of the metabolite and the characteristic fragment ion including a possible shift due to metabolic alteration. This approach allows the simultaneous monitoring of up to 50 transitions in one single LC–MS/MS assay. This setup is particularly effective when comparing metabolite patterns in different species or in various samples from different studies but from the same species. Figure 10.23 illustrates an IDA experiment with SRM–EPI scanning for a dog plasma sample taken 4 h after p.o. administration of the test compound at a dose of 30 mg/kg. A total of 13 SRM transitions, using a dwell time of 30 ms each, were used as survey scans (Figure 10.23(A)) while two EPI experiments with 40 and 50 eV were taken as dependent scans. Figure 10.23(B) shows the corresponding TIC traces of EPI at a collision energy of 40 eV. The EPI mass spectra of 10 out of 11 metabolites could be acquired in one LC–MS/MS assay without using dynamic exclusion. The same approach was successfully applied to monitor phase I and II metabolites. Figure 10.24(A) shows the representative EPI mass spectrum of a precursor at m/z 607 Th corresponding to the glucuronide of compound A while Figure 10.24(B) illustrates the EPI spectrum of the acid metabolite. As expected, the spectral quality was the same compared to that obtained by targeted analysis using EPI. Quadrupole CID spectra are strongly dependent on the collision energy (CE) and the nature of the analyte. To maximize spectral information two EPI scans are recorded in general with at least two different collision energies. In the case of the QqLIT, the trap is placed after the collision cell, and therefore fragments generated at different collision energies can be trapped Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 302/304

Using Mass Spectrometry for Drug Metabolism Studies

302

Figure 10.24 (A) EPI spectrum at CE ¼ 50 eV of the peak at RT ¼ 7.9 min corresponding to the glucuronidation of the parent drug. (B) EPI spectrum at CE ¼ 40 eV of the peak at RT ¼ 7.5 min corresponding to the acid metabolite.

simultaneously. This feature allows one to conduct only one EPI experiment using a collision energy window.18 Another advantage of the IDA experiment with SRM–EPI scanning is that the SRM traces can be used to calculate the peak area ratio from the respective analyte (metabolite) and an internal standard added to the sample prior to analysis. This ratio can be used to establish concentration–time profiles of metabolites to assess their pharmacokinetic properties particularly such as half-life.

10.4

Conclusion

The data shown demonstrate that hybrid RF/DC-quadrupole linear ion mass spectrometry is particularly suitable for drug metabolism studies especially when the radiolabeled drug is not yet available. More information can be extracted from a single LC–MS/MS assay for metabolite identification than one can obtain from conventional (QqQ) mass spectrometers, thereby saving sample and analysis time. High quality MS/MS spectra with no low mass cutoff and MS3 spectra can be obtained at the low picogram range (on-column). Nevertheless, spectral interpretation remains an important and challenging task and accurate mass measurement is mandatory in most cases for reliable fragment assignments. Accurate mass measurement can be obtained at adequate resolution with a QqTOF mass spectrometer (see Chapter 8 for Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 303/304

Q Trap MS: a New Tool for Metabolite Identification

303

more information on this topic), and the QqLIT technology may regarded as complementary to it. It is the combination of the triple quadrupole and the LIT features which makes the QqLIT particularly versatile. Compared to the 3-D trap where MS/ MS is performed in time, the QqLIT allows the performance of MS/MS in space, thereby reducing the duty cycle. The QqLIT also has a much larger ion volume capacity versus the 3-D trap. However, the capacity of the LIT can also be controlled by the dynamic fill time option, allowing a linear range in the LIT mode that is over three orders of magnitude to be obtained. Various IDA experiments can be defined such as EMS–EPI, CNL–EPI, PC–EPI, and SRM–EPI. EMS–EPI works best for the characterization of high level metabolites from in vitro experiments. This combination is not suited for the screening of low level metabolites in biological samples from in vivo trials even when using an inclusion list, because of the lack of selectivity of the EMS survey scan. In such a case, targeted analysis using EPI by prediction of the metabolites was found to be the most efficient and sensitive approach. Due to the rapid duty cycle up to eight metabolic alterations or predicted metabolites could be screened in one single LC–MS/ MS assay. High selectivity for ‘‘fishing out’’ metabolites can be obtained using CNL or PC as survey scan. Compared to the EPI mode, the sensitivity of CNL and PC remains moderate for the API 2000 Q Trap and has been improved for the API 4000 Q Trap. CNL–EPI is ideal to screen for phase II metabolites such as glucuronide, sulfate, and glutathione conjugates. A key feature of the QqLIT system is that accurate and precise quantitation can be performed with the same instrument. Therefore, once the key metabolites have been characterized their pharmacokinetic profiles can be followed easily without changing the analytical instrument. SRM and EPI also show similar sensitivity making SRM also attractive in a nonconventional fashion as a very selective and sensitive survey scan for metabolites screening. The QqLIT technology is a significant step forward for improving both the quality obtained and the speed required for identifying and quantifying metabolites. However, these versatile and flexible tools require more attention from the analyst and more sophisticated software to exploit the capability to its full potential.

References 1. Hopfgartner, G. and Bourgogne, E., Quantitative high-throughput analysis of drugs in biological matrices by mass spectrometry, Mass Spectrom. Rev., 22(3), 195, 2003. 2. Kostiainen, R., Kotiaho, T., Kuuranne, T., and Auriola, S., Liquid chromatography/atmospheric pressure ionization–mass spectrometry in drug metabolism studies, J. Mass Spectrom., 38(4), 357, 2003. 3. Clarke, N.J., Rindgen, D., Korfmacher, W.A., and Cox, K.A., Systematic LC/MS metabolite identification in drug discovery, Anal. Chem., 73(15), 430A, 2001.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-10.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:35pm Page: 304/304

304

Using Mass Spectrometry for Drug Metabolism Studies

4. Collings, B.A., Campbell, J.M., Mao, D., and Douglas, D.J., A combined linear ion trap time-of-flight system with improved performance and MSn capabilities, Rapid Commun. Mass Spectrom., 15(19), 1777, 2001. 5. Belov, M.E., Nikolaev, E.N., Alving, K., and Smith, R.D., A new technique for unbiased external ion accumulation in a quadrupole two-dimensional ion trap for electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry, Rapid Commun. Mass Spectrom., 15(14), 1172, 2001. 6. Hager, J.W., A new linear ion trap mass spectrometer, Rapid Commun. Mass Spectrom., 16(6), 512, 2002. 7. Schwartz, J.C., Senko, M.W., and Syka, J.E.P., A two-dimensional quadrupole ion trap mass spectrometer, J. Am. Soc. Mass Spectrom., 13, 659, 2002. 8. Hager, J.W. and Le Blanc, Y.J.C., Product ion scanning using a Q-q-Q linear ion trap (Q TRAPTM) mass spectrometer, Rapid Commun. Mass Spectrom., 17, 1056, 2003. 9. McClellan, J.E., Murphy, J.P., III, Mulholland, J.J., and Yost, R.A., Effects of fragile ions on mass resolution and on isolation for tandem mass spectrometry in the quadrupole ion trap mass spectrometer, Anal. Chem., 74(2), 402, 2002. 10. Hopfgartner, G., Husser, C., and Zell, M., Rapid screening and characterization of drug metabolites using a new quadrupole-linear ion trap mass spectrometer, J. Mass Spectrom., 38(2), 138, 2003. 11. Hager, J.W., Product ion spectral simplification using time-delayed fragment ion capture with tandem linear ion traps, Rapid Commun. Mass Spectrom., 17(13), 1389, 2003. 12. Hopfgartner, G. et al. Exact mass measurement of product ions for the structural elucidation of drug metabolites with a tandem quadrupole orthogonal-acceleration time-of-flight mass spectrometer, J. Am. Soc. Mass Spectrom., 10(12), 1305, 1999. 13. Xia, Y.-Q. et al. Use of a quadrupole linear ion trap mass spectrometer in metabolite identification and bioanalysis, Rapid Commun. Mass Spectrom., 17(11), 1137, 2003. 14. LeBlanc, Y.J.C., unpublished data, 2003. 15. Jorga, K., Fotteler, B., Heizmann, P., and Gasser, R., Metabolism and excretion of tolcapone, a novel inhibitor of catechol-O-methyltransferase, Br. J. Clin. Pharmacol., 48(4), 513, 1999. 16. Baillie, T.A. and Davis, M.R., Mass spectrometry in the analysis of glutathione conjugates, Biol. Mass Spectrom., 22(6), 319, 1993. 17. Boelsterli, U.A., Xenobiotic acyl glucuronides and acyl CoA thioesters as proteinreactive metabolites with the potential to cause idiosyncratic drug reactions, Curr. Drug Metab., 3(4), 439, 2002. 18. LeBlanc, Y.J.C., In Proceedings of the 19th Montreux LC/MS Symposium, Montreux, November 4–8, 2002.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 305/328

Chapter 11 MS Imaging: New Technology Provides New Opportunities Michelle L. Reyzer and Richard M. Caprioli

11.1

Introduction

A wide variety of imaging techniques have been developed because of their ability to localize molecules within a given tissue. Recently, mass spectrometry (MS) has emerged as a powerful imaging tool, allowing spatial localization to be achieved with molecular specificity. Two major MS technologies are used for imaging today: SIMS (secondary ion mass spectrometry) and MALDI (matrix-assisted laser desorption/ionization). Compounds including peptides, proteins, and drugs have been imaged directly from mammalian tissue sections using MS. This chapter will describe the use of MALDI mass spectrometric imaging as a new tool for pharmaceutical analysis of drug compounds and metabolites in drug discovery and development processes. This technique offers significant advantages over current technologies, most importantly its ability to distinguish intact drugs from their metabolites without the addition of an isotope label. This allows distribution studies of lead compounds to occur much earlier in the drug discovery process and allows compounds with unfavorable distribution characteristics to be rapidly discarded. In addition the reliance on radioactive isotopes will be minimized, which is advantageous from both an economical and environmental standpoint. 0-8493-1963-3/05/$0.00+$1.50 ß 2005 by CRC Press

Copyright © 2005 CRC Press, LLC

305

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 306/328

Using Mass Spectrometry for Drug Metabolism Studies

306

Distribution studies of drug candidates in animals are crucial in both drug discovery and development. These studies provide information about where the drug accumulates in the body, if it accumulates in the target organ, if it selectively accumulates in other organs or tissues (such as the brain, indicating possible neurotoxicity or other unwanted side effects), and how long the drug remains in the body. Accurate assessment of preclinical ADME (absorption/ distribution/metabolism/excretion) and toxicological parameters of new drug candidates is essential for future successful clinical trials. Techniques currently in use for assessing the distribution of drug candidates in tissues will be discussed, including positron emission tomography (PET), magnetic resonance imaging (MRI), autoradiography, and secondary ion mass spectrometry (SIMS). Their strengths and limitations will be addressed, especially with regard to the spatial analysis of drugs and metabolites in tissues. The technique of MALDI mass spectrometry as applied to both high molecular weight proteins and low molecular weight compounds will be discussed, and examples of its use will be presented. Finally, the further development of the technique will be addressed, focusing on improvements and advances necessary to allow the technology to reach its full potential.

11.2

Current Imaging Techniques

Many analytical techniques exist to image the distribution of compounds in the body. Generally, they can be divided into two groups: non-invasive in vivo techniques and ex vivo/in vitro techniques. In vivo techniques, such as PET1–8 and MRI,8–12 allow the distribution of a drug to be evaluated over time in a living animal. In contrast, the ex vivo/in vitro techniques, such as autoradiography,5,6,13–21 require removal of the tissue of interest and thus can only image the distribution of a drug at a fixed time. One feature common to all of these techniques is the requirement that the drug be labeled. Visualization with PET requires that a drug contain a radioactive positron emitter, such as 11C, 13N, 15O or 18F.8 Similarly, a radioactive isotope, typically 14C, 3H or 125I, is necessary for a compound to be visualized with autoradiography.21 While MRI does not require a radioactive isotope, only isotopes with nuclear spin, such as 1H, 13C, and 19F are visible with MRI.8,9 Because the sensitivity of MRI depends on the magnetic properties of the monitored nucleus and its natural abundance, drugs typically need to contain 19F or be enriched in 13C in order to be effectively monitored in the body. Contrast agents, which include paramagnetic atoms such as gadolinium, iron, and manganese, are often used to increase the contrast in MRI images and are frequently used as models for drugs that cannot be imaged on their own.9,10 The main limitation with using a label or tracer for imaging, especially in terms of drug metabolism, is that only the label and not the parent compound is imaged. Thus, the experimentally determined distribution of a drug in a tissue may be inaccurate if extensive metabolism has occurred. For example, Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 307/328

MS Imaging: New Technology Provides New Opportunities

307

Figure 11.1 PET images of 18F-labeled fluorouracil in a selected transabdominal plane passing through the base of the liver. The upper panel shows the distribution of the 18F tracer after administration of 18F-fluorouracil alone (Period 1). The lower panel shows the distribution of the 18 F tracer after 18F-fluorouracil was administered with eniluracil (Period 3). (Adapted from Saleem, A. et al. Lancet, 355, 2125, 2000. With permission.)

Saleem and colleagues performed a PET imaging study of the anti-cancer drug fluorouracil by labeling the drug with 18F.3 Fluorouracil is ultimately degraded in the body to a-fluoro-b-alanine (which would retain a 18F label). Saleem and colleagues investigated the pharmacokinetics of 18F-fluorouracil in human cancer patients in the presence and absence of eniluracil, a compound that is an inhibitor of dihydropyrimidine dehydrogenase, the rate-limiting catabolic enzyme of fluorouracil degradation. Figure 11.1 shows the PET images over time after the administration of 18F-fluorouracil alone (Period 1) and after the administration of 18F-fluorouracil with eniluracil (Period 3). As shown in Period 1, without eniluracil, there is an intense localization of the radiotracer in the liver, gallbladder, and kidneys over the 255-min experiment. The authors Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 308/328

308

Using Mass Spectrometry for Drug Metabolism Studies

explain, ‘‘This property of liver to take up 18F-fluorouracil has been attributed to rapid intracellular conversion of fluorouracil to its catabolite a-fluoro-balanine . . . The conjugation of a-fluoro-b-alanine to the bile acids and their elimination could result in localization of activity in the gallbladder . . . As the trapped catabolite was eliminated from the liver, the kidneys showed intense activity.’’3 After administration of eniluracil in Period 3, there is a marked decrease in radiotracer intensity in the liver, gallbladder, and kidneys, presumably because, after the inactivation of the dihydropyrimidine dehydrogenase enzyme, there is much less a-fluoro-b-alanine present in those tissues. It is important to note that PET imaging is not able to distinguish 18Ffluorouracil from 18F-a-fluoro-b-alanine. As a result, the authors used highperformance liquid chromatography (HPLC) to separate and identify metabolites from plasma samples from the patients, LC–MS to analyze uracil concentrations in blood, and GC–MS to analyze unlabeled a-fluoro-balanine in urine.3 These additional assays allowed the authors to conclude what compound (fluorouracil or a-fluoro-b-alanine) was actually present in the imaged liver, gallbladder, and kidneys. In vivo imaging techniques have several advantages for drug discovery applications, including the ability to examine a drug’s actions directly in humans and the ability to re-measure the same individual under different conditions (and thus decrease inter-sample variability). However, there are significant limitations. The spatial resolution is limited with both PET and MRI–PET has a resolution of
3–6 mm,2,8,9 while MRI has a resolution of
2 mm,10,11 but can be improved to
700–800 mm12 with some modifications to the instrument used. This limits the size regime in the body in which meaningful distribution data can be acquired. The use of a labeled compound typically occurs late in the drug development process due to the increased cost and time involved to synthesize the labeled compound. Additionally, there are time constraints with PET imaging due to the half-lives of the positron emitters. The half-lives of some commonly used positron emitters are: 15O, 2 min; 13N, 10 min; 11C, 20 min; 18F, 110 min.7,8 Thus a drug must be synthesized, administered, and monitored on the time-scale of the half-life of the radiotracer. Autoradiography is one of the most common techniques used today in the pharmaceutical industry for examining the distribution of a drug candidate in the body ex vivo.21,22 In quantitative whole-body autoradiography (QWBA), a radiolabeled drug is administered to an animal and, after a specified time, the animal is sacrificed, flash-frozen and sectioned. The radioactivity in the sections is then analyzed, and the result is an image showing where the drug has accumulated in various organs. Individual organs may be dissected and analyzed separately as well. This technique is also widely used in psychopharmacology for in vitro experiments, in which a radiolabeled compound is incubated with a section of brain tissue (usually rat or mouse), and the resulting image is used to determine where in the brain the compound is binding in order to locate the specific receptors of the compound.5,16,17,19,20,23 Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 309/328

MS Imaging: New Technology Provides New Opportunities

309

Figure 11.2 Autoradiographic images of the distribution of 14C-labeled estramustine in rat brain (A) 0.5, (B) 2.0, (C) 4.0, (D) 12.0, and (E) 24 h after injection. (F) H & E staining of the 4 h section shown in (C) shows the tumor as a densely stained area in the right hemisphere, which correlates well with the 14C autoradiogram. (Source: Johansson, M. et al. Cancer Chemother. Pharm., 41, 317, 1998. With permission.)

Figure 11.2 presents an autoradiographic study undertaken by Johansson et al. to determine the distribution of estramustine (EaM) in glioma tumors.15 In this study, 14C-labeled estramustine (20 mg/kg) was administered to rats with intracerebral BT4C tumors. The animals were sacrificed 0.5, 2, 4, 12 or 24 h after the 14C-EaM injection. Autoradiograms of brain sections at each time point are shown in Figure 11.2, along with a hematoxylin and eosin (H & E) stained section of the 4-h sample. As shown, the radioactivity is distributed throughout the brain at 0.5 h, is more localized to the glioma at 2, 4, and 12 h, and is markedly decreased at 24 h, thus demonstrating that estramustine selectively accumulates in an experimental glioma.15 However, as with the PET study of fluorouracil, estramustine has several known metabolites, including estromustine (EoM), estradiol, and estrone, which Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 310/328

Using Mass Spectrometry for Drug Metabolism Studies

310

cannot be differentiated in the autoradiograms.15 In order to assess the distribution of the metabolites, blood and tissue homogenates were analyzed by GC or GC/MS. These analyses showed that, at the 12 h time point, 761  237 ng/g EaM was in the tumor, as well as 558  240 ng/g EoM, 9.0  2.8 ng/g estradiol, and 18  3.5 ng/g estrone.15 Thus while EaM was the major source of radiolabel in the glioma (56%), the primary metabolite, EoM, represented
40% of the signal in the tumor. Autoradiography has significant advantages over the non-invasive imaging techniques, especially in terms of drug discovery. As it is typically performed on laboratory animals, it occurs earlier in the drug discovery process. Additionally, the resolution is better than PET and MRI, ranging from a few micrometers for film to
30–50 mm for the b-imager,23–25
70 mm for microchannel plates,26,27 and
25–100 mm for commercial phosphor imaging systems (Fujifilm). In contrast, the time required to acquire an autoradiographic image varies substantially and can be prohibitively long. It often takes weeks or months to acquire an image on film, while the same image may be acquired on the b-imager in 8–12 h.23 Also, because a radiolabel is required, the extra cost and time required for additional synthesis are still limitations. 11.2.1

Mass spectrometric imaging—SIMS technology

Due to its molecular specificity, there is a great deal of interest in using mass spectrometry as an imaging tool. SIMS has been used for imaging surfaces for more than 40 years.28 Briefly, SIMS employs an ion gun, typically O2þ, Csþ or Gaþ, which is focused onto a sample. The primary ion beam has an energy of
25 keV which desorbs ions from the surface of the sample. These ‘‘secondary’’ ions are predominantly elements, atomic clusters, and organic fragments that are typically analyzed in time-of-flight (TOF), quadrupole or magnetic sector instruments. While molecular ions can be formed, for example several analyses have been reported involving the [M þ H]þ ions of cholesterol,29 benzodiazepines,30 and crystal violet,31 the secondary ions formed most abundantly include atomic ions (e.g. Naþ, Kþ) and molecular fragment ions. Thus, its primary use has been for the localization of inorganic, atomic species.28 Applications of SIMS imaging to biological/pharmaceutical analyses have been in two key areas: atomic imaging of drugs32–35 and tissue mapping via molecular imaging of fragment ions.29,36–38 In the first application, the drug of interest must effectively be labeled—it must contain an atom not natively found in cells or tissues, and only that atom is monitored. For example, Smith et al. monitored the 10B distribution in the rat gliosarcoma brain tumor model via SIMS imaging.39 The boron-containing drug p-boronophenylalaninefructose (BPA-F) was injected into rats with brain tumors derived from 9L gliosarcoma cells. BPA-F serves as a source of 10B, a naturally occurring isotope of boron. 10B is used to selectively irradiate tissue via boron neutron capture therapy (BNCT). The goal was to determine if 10B was selectively Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 311/328

MS Imaging: New Technology Provides New Opportunities

311

Figure 11.3 SIMS images of the distribution of 10B in infiltrating tumor cells in the rat brain after injection of p-boronophenylalanine-fructose. (A) and (C) Optical images of H & E stained sections. (B) and (D) SIMS images of 10B from selected regions of adjacent tissue sections to (A) and (C), respectively. The arrows point to neoplastic cell clusters, which show significantly higher uptake of 10 B than the surrounding brain tissue. T ¼ main tumor mass; NB ¼ normal brain; A ¼ artery. (Adapted from Smith, D.R. et al. Cancer Res., 56, 4302, 1996. With permission.)

accumulating in tumor tissue and infiltrating cells as opposed to normal brain tissue, thus indicating the viability of BNCT to selectively treat brain gliomas. Figure 11.3 (A and C) shows two H & E stained sections of cancerous rat brain tissue from rats dosed with BPA-F. The arrows point to clusters of infiltrating neoplastic cells, which show a significantly higher uptake of 10B than the surrounding normal brain tissue (Figure 11.3, B and D).39 The 10B images were obtained with an O2þ ion gun at a spatial resolution of
500 nm.39 As with other labeling techniques, however, the source of the 10B, i.e., whether it was from the parent drug or a metabolite, cannot be determined with this methodology. The other main application of SIMS to biological imaging has focused on tissue mapping. Todd et al. used a Csþ ion gun to create secondary ion images of the rat brain by monitoring the phosphocholine headgroup of phosphatidylcholine (PC) at m/z 184.37 PC is a component of cell membranes and is ubiquitously, but heterogeneously, found throughout the brain. Thus the intensity of m/z 184 from a PC-rich structure, such as the hippocampus, is high, while the intensity from a PC-poor structure, such as the corpus callosum, is low.37 The resulting ion images are similar to optical images of Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 312/328

Using Mass Spectrometry for Drug Metabolism Studies

312

histologically stained brain sections, with different morphological areas being visualized. The authors envision the creation of a rat brain atlas based on m/z 184 secondary ion emission, which would be useful for localizing drugs or toxins in various regions of the brain.37 Compared to the traditional imaging techniques discussed earlier, the benefits of the SIMS imaging techniques include excellent spatial resolution (submicrometer to
1 mm) and high sensitivity and molecular specificity. One of the main drawbacks, however, especially in regards to metabolite localization, is the low efficiency of molecular ionization.31 Thus it is difficult to differentiate a compound and structurally similar metabolites if they share the same label (i.e., a fluorine atom) or if they form the same fragment ion, because that is what is typically analyzed. While advances are being made towards increasing molecular ion yields, especially utilizing cluster ion beams, such as C60þ and SF5þ,31,40 the full potential of this technology for pharmaceutical imaging has not been reached.

11.2.2

Mass spectrometric imaging—MALDI Technology

A more recent mass spectrometric-based approach to tissue imaging, and the subject of this chapter, involves matrix-assisted laser desorption/ionization (MALDI),41,42 which is a less energetic ionization process that produces primarily singly protonated molecules, [M þ H]þ ions. The initial impetus for using a MALDI imaging approach stemmed from the desire to image high molecular weight species, such as proteins, directly from their native biological environment. Over the past several years, investigators have demonstrated that peptide and protein signals can be effectively desorbed directly from cells and tissues using MALDI MS.36,43–55 Intact molecular ions of over 150 kDa have been detected with UV-MALDI,56 and ions of over 750 kDa have been detected with IR-MALDI.57 Two examples of MALDI MS generated protein images are given in Figure 11.4. Figure 11.4(A) shows an optical image of a section of a human glioblastoma xenograft that has been coated with MALDI matrix and two selected mass spectrometric images generated from that tissue section.50 A total of 45 individual protein signals were monitored and imaged in the single acquisition run at a resolution of 100 mm. As shown, a protein of 11,640 Da, subsequently identified as S100 calcium binding protein A4, is localized in the ischemic area of the tumor, between the growing outer periphery and the necrotic center. Thymosin b4, an actin sequestering protein of 4965 Da, is shown to be localized in the periphery of the tumor.50 Figure 11.4(B) shows an optical image of a cauda segment of mouse epididymis along with two selected mass spectrometric images.53 The epididymis contains a long tubule, cross-sections of which have been outlined in the figures, along with an outline of the border of the tissue section. A protein identified as CRISP-1 (cysteine-rich secretory protein-1) of 26,830 Da is localized within the epididymal tubule as shown. In contrast, Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 313/328

MS Imaging: New Technology Provides New Opportunities

313

Figure 11.4 MALDI TOF MS images of protein distributions. (A) From left to right, an optical image of a section of human glioblastoma xenograft tissue coated with sinapinic acid, and MS images of the tissue distribution of the S100 calcium binding protein A4 at m/z 11,640 and thymosin b4 at m/z 4965. (Adapted from Stoeckli, M. et al. Nature Med., 7, 493, 2001. With permission.) (B) From left to right, an optical image of a section of mouse epididymis cauda, and MS images of the tissue distribution of the CRISP-1 protein at m/z 26,830 and thymosin b4 at m/z 4965. (Adapted from Chaurand, P. et al. Proteomics, 3, 2221, 2003. With permission.)

thymosin b4 is not found in the epididymal tubule but rather in the connective tissue surrounding the tubule.53 As Figures 11.4(A and B) illustrate, direct analysis of tissue sections by MALDI MS provides useful biological information. Many hundreds of ion signals over a large mass range, typically
2000–70,000 Da, can be detected. These signals can be spatially localized with a resolution on the order of the diameter of the laser beam, currently
25–50 mm for a focused N2 laser. These images illustrate the vast potential of this technique for biological discovery. The ability to localize a given protein in a tissue sample can lead to insights into its mode of action. Also, determining which proteins co-localize together may also reveal unknown or new functional relationships. One prerequisite for MALDI analysis, however, is the application of a matrix to the tissue sample. Choosing the best matrix and optimizing application parameters are necessary for obtaining high-quality spectra directly from tissue samples and maintaining the spatial integrity of the tissue surface. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 314/328

Using Mass Spectrometry for Drug Metabolism Studies

314

A detailed account of sample preparation protocols for MALDI MS analysis of tissue sections has recently been published.58 Essentially, the application of matrix to the sample serves two main functions: the extraction of analyte from the tissue into the matrix solution and the co-crystallization of analyte and matrix on the surface of the tissue. For successful imaging, the matrix application parameters must be optimized to maximize extraction and co-crystallization and minimize analyte delocalization. 11.2.3

MALDI MS analysis of low MW compounds

In terms of localizing the distribution of low molecular weight pharmaceutical compounds in tissues, MALDI MS offers many advantages over other imaging technologies. The two most significant advantages are that intact drugs may be analyzed directly from tissues with no label required and that metabolites that differ in mass from the parent drug can be differentiated. Thus the distribution of those metabolites can also be ascertained in addition to the distribution of the parent drug. However, one significant limitation of MALDI technology for the analysis of low molecular weight compounds is spectral noise in the low mass region generated from the matrix, matrix clusters, and fragment ions.59 The extent of the spectral interference from matrix-related signals is illustrated in Figure 11.5. As shown, the MALDI mass spectrum (acquired on a linear TOF instrument) of sinapinic acid, a common matrix compound, contains many signals throughout the acquired mass range (10–1000 Da). Three main factors contribute to the intensity of the spectral noise: (1) MALDI matrices are in the same molecular weight range as most organic drug compounds (<1000 Da); (2) matrices are effective at selfprotonation; and (3) the matrix is present in great excess over the analyte (
1000:1). Many attempts have been made to overcome this problem to facilitate the use of MALDI MS for low molecular weight compound analysis. One approach has been to use larger molecular weight compounds as matrices, in order to shift the spectral interferences out of the mass range of the analytes.

Figure 11.5 MALDI TOF mass spectrum of the matrix sinapinic acid (SA) with some added Naþ showing the abundance of signals generated in the low mass range (m/z<1000) from the matrix, matrix fragments, and matrix clusters.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 315/328

MS Imaging: New Technology Provides New Opportunities

315

Figure 11.6 (A) A DIOS plate. (B) DIOS mass spectrum of a mixture of the low molecular weight compounds caffeine (m/z 196), the anti-viral drug WIN (m/z 357), and reserpine (m/z 609), showing virtually no background signals from the silicon surface. The small signal denoted with an asterisk is a contaminant from the caffeine. (Adapted from Wei, J. et al. Nature, 399, 243, 1999. With permission.)

Nonmetallic porphyrins have been used as matrices to successfully analyze mixtures of small nonionic surfactants60 and creatinine,61 while C60 (buckminsterfullerene) has been applied as a matrix for the analysis of diuretic doping agents.62 Small inorganic particles, including Al, Sn, TiO2, ZnO, and porous silicon powder, have also been used as matrices.63,64 Another approach, commonly known as desorption/ionization on silicon (DIOS), involves applying the sample to porous silicon65,66 or silicon films67 without an additional matrix. As shown in Figure 11.6, molecular ions of caffeine (m/z 196), the anti-viral drug WIN (m/z 357), and reserpine (m/z 609) generated with DIOS show virtually no background signals.66 Finally, adding a surfactant to the matrix solution has been shown to suppress matrix signals, but the analyte signal is also somewhat suppressed.68 Despite some successes, these methods do not address further problems that arise when examining drugs directly from tissue. Many endogenous compounds can be desorbed and can either produce interfering signals in the spectra or suppress signals of interest. Spectral interferences from low molecular weight tissue components or fragments may still interfere with the detection of low molecular weight drug compounds. Additional confirmation of the identity of a compound is therefore required for complete and accurate analyses. 11.2.4

Advantages of MALDI MS/MS for analysis of low MW compounds

Tandem mass spectrometry, or MS/MS analysis, is routinely used in the pharmaceutical industry for both quantitative analyses and in-depth structural analyses of drug candidates. It is usually performed via collisionally activated dissociation (CAD) on triple quadrupole, quadrupole ion trap, or quadrupole Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 316/328

316

Using Mass Spectrometry for Drug Metabolism Studies

time-of-flight (QqTOF) analyzers coupled to electrospray ionization (ESI) or atmospheric pressure chemical ionization (APCI) sources. The recent introduction of MALDI sources for both quadrupole ion trap and QqTOF instruments allows CAD experiments to be performed on MALDI-generated low mass ions. MALDI-triple quadrupole instruments are also currently under development for pharmaceutical analysis.69 Troendle et al. reported the use of CAD to distinguish MALDI-generated paclitaxel ions from background signals in a quadrupole ion trap instrument equipped with a custom-built laser microprobe.51 Paclitaxel was directly detected from a section of rat liver tissue that had been incubated with a solution of the drug, as well as from a section of human ovarian tumor xenograft tissue from a mouse that had been dosed with the drug. The concentration of paclitaxel was approximately 50 mg/g in each tissue of interest. In both cases, CAD was performed on an alkali metal adduct, either [M þ Na]þ or [M þ K]þ. Comparison of the resulting fragmentation patterns to those obtained from a paclitaxel standard unambiguously confirmed the presence of paclitaxel in the tissue. Paclitaxel ions could not be differentiated from the background signal in the MS spectrum of the drug prior to ion isolation and CAD.51 A more dramatic example of the utility of CAD is the case of the experimental anti-tumor drug SCH 226374 (Figure 11.7(A)).54 Protonated SCH 226374 has a monoisotopic molecular weight of 695.35. Coincidentally, a sinapinic acid matrix cluster of the type [3  SA þ Na]þ has a monoisotopic molecular weight of 695.20, less than 0.2 amu from the mass of protonated SCH 226374. High-resolution mass analyzers are required to distinguish these signals. A MALDI TOF instrument was used in reflector mode to analyze SCH 226374 in a section of mouse tumor tissue where the mouse had been dosed with the drug at 80 mg/kg.54 Figure 11.7(B) shows an optical image of the section of tumor tissue spotted with sinapinic acid. The MALDI TOF mass spectra obtained from spots #18 and #15 are shown in Figure 11.7(C). As shown, there is a large signal corresponding to the SA matrix cluster ion in both spectra. There is a distinct signal corresponding to the [M þ H]þ of SCH 226374 in spot #18 which is resolved from the matrix signal (Figure 11.7(C), top). However there are no 13C and 37Cl isotope signals discernible to increase confidence that SCH 226374 was detected in the tumor tissue. The spectrum from spot #15 shows the sinapinic acid cluster signal with an unresolved shoulder, which may or may not correspond to SCH 226374.54 In contrast, the same section of tissue was subsequently analyzed in the MS/MS mode on a QqTOF instrument equipped with a MALDI source.54 For these experiments, CAD was performed on the ion packet at m/z 695 and only fragments in the range of m/z 220 to 250 were analyzed in the orthogonal TOF analyzer. The resulting spectra are shown in Figure 11.7(D). As shown, for spots #18 and #15 there are two distinct groups of signals—one at m/z 228.1 corresponding to the primary fragment ion of SCH 226374, and the other at m/z 246.1 corresponding to a fragment of the matrix cluster. Effectively, Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 317/328

MS Imaging: New Technology Provides New Opportunities

317

Figure 11.7 (A) Structure of the anti-tumor drug candidate SCH 226374. (B) Optical image of a section of tumor tissue from a mouse dosed with SCH 226374 at 80 mg/kg. The section has been spotted with sinapinic acid (numbered circles). (C) MALDI TOF mass spectra from spots #15 and #18 on the tissue section. The protonated drug signal is difficult to discern from an interfering matrix cluster signal. (D) MALDI MS/MS QqTOF mass spectra from the same spots (#15 and #18) on the same tissue section shown in (C). CAD was performed on the ion packet at m/z 695, and only fragments in the range m/z 220–250 were detected. As a result, the presence of SCH 226374 is unambiguously confirmed. (Adapted from Reyzer, M.L. et al. J. Mass Spectrom., 38, 1081, 2003. With permission.)

selected reaction monitoring (SRM) is being used to analyze the drug. As a result, the drug is detected with higher sensitivity and the presence of the drug is unambiguously confirmed in the MS/MS experiments as compared to the single-stage TOF MS experiments where confirmation was minimal. 11.2.5

MALDI MS/MS imaging of low MW compounds

Transforming a MALDI QqTOF system (or any MALDI MS system) into an effective imaging instrument is greatly facilitated by specialized software. In general, the software is necessary to define the boundaries of the area to be imaged and the desired resolution, to control the instrument acquisition in an automated fashion, and to display the resulting data mass selectively as two-dimensional images. MDS/Sciex has developed such software for the QStar/QqTOF instrument. This software has been successfully used in our Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 318/328

318

Using Mass Spectrometry for Drug Metabolism Studies

Figure 11.8 General procedure for preparing samples for MALDI MS imaging (left side) and for conventional quantitative HPLC/MS analysis (right side).

laboratory to generate several MALDI MS/MS images of the distributions of various drugs in tissues.54,70 The general procedure for preparing samples for imaging is described below and illustrated on the left side of Figure 11.8. For comparison, the right side of Figure 11.8 depicts the procedure for conventional quantitative analysis of drugs from tissue homogenates. Sample preparation for direct tissue analysis by MALDI involves minimal sample handling and is relatively simple compared to preparing tissue homogenates, precipitating proteins, and extracting drugs of interest. However, it is important to carefully implement tissue preparation methods in order to maintain the spatial integrity of compounds in the tissue. First, in order to maintain the shape of the tissue as well as to protect the tissue from degradation, the tissue should be flash frozen (for example, by immersing the tissue in liquid nitrogen) immediately after surgical removal. Placing freshly excised tissues in small plastic tubes should be avoided, as the tissues may take on the shape of the tube when frozen. Once frozen, the tissues may be kept in a freezer, typically at 80 C, until further processing.58 Frozen tissues are then cut into thin sections (
10–20 mm) in a cryostat for subsequent mounting onto MALDI plates. Figure 11.9 illustrates the cryostat sectioning process. A frozen section of mouse liver is shown on the cryostat stage as it is moving across the microtome blade. As shown, the tissue is attached to the stage with an embedding medium (OCT, optimal cutting temperature polymer) acting as an adhesive. It is important for subsequent mass spectral analysis that there be no contact between the section to be analyzed and the embedding medium as it has been shown to suppress ion formation.58 The resulting section may be gently positioned with a cold, artist’s brush onto a cold MALDI plate that has been sitting in the cryostat chamber (
15 C to 25 C). The tissue is Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 319/328

MS Imaging: New Technology Provides New Opportunities

319

Figure 11.9 The cryostat sectioning process.

thaw-mounted onto the MALDI plate by gently warming the plate and section together. Next the mounted tissue section must be coated with matrix. While many types of matrix and different matrix/solvent combinations have been examined for different purposes, sinapinic acid (SA) made up as a 20 mg/mL solution in 50:50 acetonitrile: 0.1% trifluoroacetic acid (TFA) in water has been found to be a good general matrix for direct tissue analysis.58 For imaging, a homogeneous coating of matrix is necessary to extract the analyte of interest and allow it to co-crystallize with the matrix while maintaining its spatial integrity. Reproducible whole tissue coatings have been achieved using a deactivated glass spray nebulizer (TLC reagent sprayer).58 Typically, a cycle of matrix coatings is performed, where a small volume of matrix is deposited on the tissue surface and the tissue is allowed to dry for 1–2 min in each cycle. This allows a crystal layer to slowly build up on the tissue surface while the amount of liquid present at one time is minimized in order to minimize analyte delocalization. The goal is to achieve a balance between wetting the surface enough for effective analyte solubilization and not having the surface become too wet or too dry. After the tissue section has sufficient crystal coverage, it is put into the mass spectrometer for analysis. Once in the mass spectrometer, software is used to move the sample under the laser in discrete steps and a spectrum is acquired at each spot. The intensities of the ion of interest at each spot are then plotted as a function of the location on the tissue surface, resulting in a two-dimensional ion density map, or image. The distribution of the previously described anti-tumor drug candidate SCH 226374 was examined via MALDI MS/MS imaging.54 The tumor from a mouse dosed with the drug at 80 mg/kg was excised 7 h after dosing. A section of the tumor tissue was coated with sinapinic acid and CAD spectra of the m/z 695 ! 228 reaction were acquired over the tissue section. The relative intensities of the fragment ion at m/z 228.1 were plotted as shown in Figure 11.10. The resulting image shows that the drug has clearly reached its Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 320/328

Using Mass Spectrometry for Drug Metabolism Studies

320

Figure 11.10 (A) Optical image of a section of tumor tissue from a mouse dosed with SCH 226374 at 80 mg/kg and coated with sinapinic acid. (B) MALDI MS/MS image of the distribution of SCH 226374 in tumor tissue via CAD of m/z 695 ! 228. (Adapted from Reyzer, M.L. et al. J. Mass Spectrom., 38, 1081, 2003. With permission.)

Figure 11.11 (A) Optical image of a section of brain tissue from a rat dosed with the discovery compound compound A at 5 mg/kg. (B) MALDI MS/MS image of the distribution of compound A in rat brain tissue via CAD of m/z 466 ! 225. (Adapted from Reyzer, M.L. et al. J. Mass Spectrom., 38, 1081, 2003. With permission.)

target tissue, and that while the drug is present over most of the tumor section it is present in a higher concentration in the outer periphery.54 Another example is the distribution of a discovery compound (compound A) in rat brain.54 A mass spectral image was obtained from a section of rat brain tissue from an animal that had been intravenously dosed with compound A at 5 mg/kg and the brain removed 1 h after dosing. The brain section was analyzed in a 30  15 spot grid, with spots being 500 mm apart in both the x and y directions. The precursor ion at m/z 466 was dissociated and the dominant fragment ion at m/z 225 was monitored at each spot. The resulting MS/MS image is shown in Figure 11.11, along with an optical image of the uncoated brain section. As shown, the compound appears to be present to a greater extent in the cortex than in the striatum.54 11.2.6

Current developments and future applications

Recently, our laboratory has been evaluating the use of drug imaging in parallel with protein imaging to examine drug-treated versus untreated Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 321/328

MS Imaging: New Technology Provides New Opportunities

321

Figure 11.12 (A) Optical image of a section of tumor tissue from a mouse dosed with the antitumor drug OSI-774 at 100 mg/kg. (B) MALDI MS/MS image of the distribution of OSI-774 in mouse tumor tissue via CAD of m/z 394 ! 278.

samples.70 It is expected that as a drug is administered and accumulates in a tumor, changes will occur to the proteome of the tumor tissue. Some proteins may be upregulated while others may be downregulated. Presumably, these molecular changes may be observed much earlier than any physiological changes, such as tumor shrinkage, and thus may be useful predictors of the effectiveness of a given therapy. MALDI imaging techniques make it possible to monitor both drug accumulation and protein distribution in the same tissue. Consequently, the relationship between a drug and its resulting protein changes may be readily observed. OSI-774 is a small molecule tyrosine kinase inhibitor of the epidermal growth factor (EGF) receptor,71 which is highly expressed in many forms of human cancer. It has been observed that MMTV/HER2 tumors in mice show significant reduction in tumor volume after being dosed with OSI-774 at 100 mg/kg compared to untreated tumors. The distribution of OSI-774 in a section of mouse tumor removed 16 h after dosing with 100 mg/kg OSI-774 was determined by imaging MS/MS analysis. The CAD transition m/z 394 ! 278 was monitored, and the intensity of the main fragment ion at m/z 278 was plotted as shown in Figure 11.12. As shown, the drug appears to be present throughout the tumor section.70 (No drug was observed in untreated tumor tissue.) Subsequently, the protein distributions in a section of untreated tumor tissue and a section of tumor tissue treated with OSI-774 (100 mg/kg, removed 16 h after dosing) were determined by MALDI TOF MS analysis.70 Four selected ion images, along with an optical image of the uncoated tissue sections are shown in Figure 11.13. As shown, the four selected signals are present fairly homogeneously across the untreated tumor section (Figure 11.13, top row). The histone signal at m/z 11,344 and the signal at m/z 4747 are also homogeneously distributed across the OSI-774 treated tumor section (Figure 11.13, bottom row). However, the intensities of thymosin b4 at m/z 4965 and ubiquitin at m/z 8562 are significantly decreased in the dosed tumor compared to the non-dosed tissue, indicating the drug is having a significant effect on the proteome of the tissue. While it may take days to ascertain the Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 322/328

322

Using Mass Spectrometry for Drug Metabolism Studies

Figure 11.13 MALDI TOF MS images of protein distributions in mouse tumor tissues (A) nondosed and (B) dosed with OSI-774 at 100 mg/kg. The four selected ion images show fairly homogeneous distribution across the untreated tumor section. The signals at m/z 11,344 (histone) and m/z 4,747 are also homogeneously distributed across the dosed tumor section; but thymosin b4 and ubiquitin are significantly decreased in the tumor tissue dosed with OSI-774.

effectiveness of drug treatment by measuring changes in tumor volume over time, these proteomic changes observed between 8 and 16 h after treatment may allow the effectiveness of the drug treatment to be determined much earlier. Thus this application may have great clinical utility and importance. The ability to determine the distribution of a drug, especially in relation to its target protein, and then be able to detect subsequent changes in the proteins where the drug is actually located in the target tissue will become very important as molecularly targeted therapies are increasingly developed. In addition, the application of this technology to metabolite determination will be significant. Especially when the metabolic processes of drugs are known, metabolites that differ in mass from the parent drug (which is generally the case) can readily be differentiated by mass spectrometry. The distribution of those metabolites in addition to the distribution of the parent drug can be determined directly in tissues of interest. This type of information is not readily obtained by any other methodology. In order to become a routine tool in pharmaceutical research and development, however, the technology must advance in several areas. First, the imaging resolution is currently limited by the size of the laser spot focused on the sample. Optical lenses can reduce the diameter of an N2 laser on a MALDI TOF instrument to
25–50 mm, which is on the order of digital autoradiography, and certainly sufficient for screening whole tissue sections for drug distribution. The QStar Pulsar iÕ (MDS/Sciex) QqTOF instrument currently uses a fiber optic cable with a 200-mm diameter to deliver laser light to the sample, and it is oriented at an extreme angle to the sample stage. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 323/328

MS Imaging: New Technology Provides New Opportunities

323

Thus the resulting laser spot is elliptical, with diameters of
200 mm 
400 mm in the x and y directions, respectively. Utilizing smaller diameter fiber optics and adjusting the alignment of the fiber with the sample stage should allow the resolution to approach that of optically focused N2 lasers. Additionally, as with all imaging techniques, there are trade-offs between resolution, acquisition time, and sensitivity. For example, imaging a 10 mm  10 mm tissue section at 1 mm intervals compared to 100 mm intervals increases the number of discrete spots from 10,000 to 100,000,000! The total acquisition time would increase accordingly. This increase in acquisition time can be partially offset by increasing the frequency of the laser. Most N2 lasers (337 nm) can be run at up to 40 Hz, while newer pulsed Nd:YAG lasers (355 nm) can be run at up to 1000 Hz. Thus, analyses run with a 1000 Hz laser can be run 25 faster than those with a 40 Hz laser, assuming that everything else remains constant. However, imaging at very high resolution leads to a decrease in sensitivity. This is because the total amount of analyte present under a 1 mm diameter laser spot is much less than that present under a 100 mm diameter laser spot. In addition, computer storage and data processing requirements increase as the resolution increases, and advanced bioinformatic algorithms (including baseline subtraction, normalization, and sample comparisons) may be required to extract more biologically relevant information. In summary, the usefulness of this technology and how it is applied must ultimately be determined by the goal of individual applications. In its current form, it is well suited to determining the localization of drug compounds and their metabolites in whole tissue sections. It is also an appropriate tool for screening receptor selectivities of psychopharmacological drug candidates without having to use radiolabeled compounds. However, it is not suitable for the subcellular localization of drugs, as resolution in the submicron range is necessary. Ultimately, this technology is not foreseen as a replacement for any of the other established imaging techniques mentioned in this chapter, rather it is complementary to them. It is most likely that the combined use of several techniques will fully describe the action of a drug or protein in the body.

11.3

Conclusions

The relatively new technology of MALDI MS imaging has been described. It has been shown that the distribution of biological signals of interest, including peptides, proteins, and drugs, can be obtained directly from tissue sections with the molecular specificity not available with any other technique. The opportunities that this new technology provides are many and varied— from drug discovery and development, to improved biochemical understanding of disease progression, to clinical assessment of the effectiveness of drug therapy. While the technology is still developing, as improved commercial Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 324/328

Using Mass Spectrometry for Drug Metabolism Studies

324

instruments and imaging software become more widely available, the applications and opportunities afforded by this technique will only increase.

11.4

Acknowledgments

The authors acknowledge support from the National Institutes of Health (NIH/NIGMS 5R01 GM 58008). MLR acknowledges Philip Morris Inc. for a post-doctoral research fellowship.

References 1. Boy, C. et al. Imaging dopamine D4 receptors in the living primate brain: A positron emission tomography study using the novel D1/D4 antagonist [11C]SDZ GLC 756, Synapse, 30, 341, 1998. 2. Ekesbo, A. et al. Effects of the substituted (S)-3-phenylpiperidine ()-OSU6162 on PET measurements of [11C]SCH23390 and [11C]raclopride binding in primate brains, Neuropharmacology, 38, 331, 1999. 3. Saleem, A. et al. Modulation of fluorouracil tissue pharmacokinetics by eniluracil: In-vivo imaging of drug action, Lancet, 355, 2125, 2000. 4. Moresco, R.M. et al. PET in psychopharmacology, Pharmacol. Res., 44(3), 151, 2001. 5. Ishiwata, K. et al. Positron emission tomography and ex vivo and in vitro autoradiography studies on dopamine D2-like receptor degeneration in the quinolinic acid-lesioned rat striatum: Comparison of [11C]raclopride, [11C]nemonapride, and [11C]n-methylspiperone, Nucl. Med. Biol., 29, 307, 2002. 6. Kassiou, M. et al. (þ)-[76Br]A-69024: A non-benzazepine radioligand for studies of dopamine D1 receptors using PET, Nucl. Med. Biol., 29, 295, 2002. 7. Aboagye, E.O. and Price, P.M., Use of positron emission tomography in anticancer drug development, Invest. New Drugs, 21, 169, 2003. 8. Singh, M. and Waluch, V., Physics and instrumentation for imaging in-vivo drug distribution, Adv. Drug Delivery Rev., 41, 7, 2000. 9. Port, R.E. and Wolf, W., Noninvasive methods to study drug distribution, Invest. New Drugs, 21, 157, 2003. 10. Faas, H. et al. Monitoring the intragastric distribution of a colloidal drug carrier model by magnetic resonance imaging, Pharm. Res., 18(4), 460, 2001. 11. Kupriyanov, V.V. et al. The effects of drugs modulating Kþ transport on Rbþ uptake and distribution in pig hearts following regional ischemia: 87Rb MRI study, NMR Biomed., 15, 348, 2002. 12. Noworolski, S.M. et al. High spatial resolution 1H-MRSI and segmented MRI of cortical gray matter and subcortical white matter in three regions of the human brain, Magnet. Reson. Med., 41, 21, 1999. 13. Bouchard, P. and Quirion, R., [3H]1,3-di(2-tolyl)guanidine and [3H](þ)pentazocine binding sites in the rat brain: Autoradiographic visualization of the putative sigma1 and sigma2 receptor subtypes, Neuroscience, 76(2), 467, 1997. 14. Goldberg, I.E. et al. Pharmacological characterization of endomorphin-1 and endomorphin-2 in mouse brain, J. Pharmacol. Exp. Ther., 286(2), 1007, 1998.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 325/328

MS Imaging: New Technology Provides New Opportunities

325

15. Johansson, M. et al. Distribution of estramustine in the BT4C rat glioma model, Cancer Chemother. Pharm., 41, 317, 1998. 16. Joyce, J.N., D2 but not D3 receptors are elevated after 9 or 11 months chronic haloperidol treatment: Influence of withdrawal period, Synapse, 40, 137, 2001. 17. Kaichi, Y. et al. Dopamine D3 receptor binding by D3 agonist 7-OH-DPAT (7-hydroxy-dipropylaminotetralin) and antipsychotic drugs measured ex vivo by quantitative autoradiography, Can. J. Physiol. Pharm., 78, 7, 2000. 18. Li, C. et al. Biodistribution of paclitaxel and poly(l-glutamic acid)–paclitaxel conjugate in mice with ovarian OCa-1 tumor, Cancer Chemother. Pharm., 46, 416, 2000. 19. Schotte, A. et al. Endogenous dopamine limits the binding of antipsychotic drugs to D3 receptors in the rat brain: A quantitative autoradiographic study, Histochem. J., 28, 791, 1996. 20. Schotte, A. et al. Risperidone compared with new and reference antipsychotic drugs: In vitro and in vivo receptor binding, Psychopharmacology, 124, 57, 1996. 21. Solon, E.G. and Kraus, L., Quantitative whole-body autoradiography in the pharmaceutical industry: Survey results on study design, methods, and regulatory compliance, J. Pharmacol. Toxicol., 46, 73, 2002. 22. Coe, R.A.J., Quantitative whole-body autoradiography, Regul. Toxicol. Pharm., 31, S1, 2000. 23. Langlois, X. et al. Use of the beta-imager for rapid ex vivo autoradiography exemplified with central nervous system penetrating neurokinin 3 antagonists, J. Pharmacol. Exp. Ther., 299(2), 712, 2001. 24. Tribollet, E. et al. Localization and quantitation of tritiated compounds in tissue sections with a gaseous detector of beta particles: Comparison with film autoradiography, Proc. Natl. Acad. Sci., 88, 1466, 1991. 25. Charpak, G., Dominik, W., and Zaganidis, N., Optical imaging of the spatial distribution of beta-particles emerging from surfaces, Proc. Natl. Acad. Sci., 86, 1741, 1989. 26. Lees, J.E. et al. An MCP-based system for beta autoradiography, IEEE Trans. Nucl. Sci., 46(3), 636, 1999. 27. Lees, J.E., Fraser, G.W., and Carthew, P., Microchannel plate detectors for 14C autoradiography, IEEE Trans. Nucl. Sci., 45(3), 1288, 1998. 28. Pacholski, M.L. and Winograd, N., Imaging with mass spectrometry, Chem. Rev., 99, 2977, 1999. 29. Pacholski, M.L. et al. Static time-of-flight secondary ion mass spectrometry imaging of freeze-fractured, frozen-hydrated biological membranes, Rapid Commun. Mass Spectrom., 12, 1232, 1998. 30. Audinot, J.-N. et al. Detection and quantification of benzodiazepines in hair by TOF-SIMS: Preliminary results, Appl. Surf. Sci., 203–204, 718, 2003. 31. Winograd, N., Prospects for imaging TOF-SIMS: From fundamentals to biotechnology, Appl. Surf. Sci., 203–204, 13, 2003. 32. Guerquin-Kern, J.-L. et al. Complementary advantages of fluorescence and SIMS microscopies in the study of cellular localization of two new antitumor drugs, Microsc. Res. Techniq., 36, 287, 1997. 33. Chandra, S., Lorey II, D.R., and Smith, D.R., Quantitative subcellular secondary ion mass spectrometry (SIMS) imaging of boron-10 and boron-11 isotopes in the same cell delivered by two combined BNCT drugs: In vitro studies on human glioblastoma T98G cells, Radiat. Res., 157, 700, 2002.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 326/328

326

Using Mass Spectrometry for Drug Metabolism Studies

34. Bennett, B.D. et al. Subcellular localization of p-boronophenylalanine-delivered boron-10 in the rat 9L gliosarcoma: Cryogenic preparation in vitro and in vivo, Radiat. Res., 140, 72, 1994. 35. Fragu, P. and Kahn, E., Secondary ion mass spectrometry (SIMS) microscopy: A new tool for pharmacological studies in humans, Microsc. Res. Techniq., 36, 296, 1997. 36. Todd, P.J. et al. Organic ion imaging of biological tissue with secondary ion mass spectrometry and matrix-assisted laser desorption/ionization, J. Mass Spectrom., 36, 355, 2001. 37. McCandlish, C.A., McMahon, J.M., and Todd, P.J., Secondary ion images of the rodent brain, J. Am. Soc. Mass Spectrom., 11, 191, 2000. 38. Todd, P.J. et al. Organic SIMS of biologic tissue, Anal. Chem., 69, 529A, 1997. 39. Smith, D.R. et al. Ion microscopy imaging of 10B from p-boronophenylalanine in a brain tumor model for boron neutron capture therapy, Cancer Res., 56, 4302, 1996. 40. Wong, S.C.C. et al. Development of a C60þ ion gun for static SIMS and chemical imaging, Appl. Surf. Sci., 203-204, 219, 2003. 41. Karas, M. et al. Matrix-assisted ultraviolet laser desorption of non-volatile compounds, Int. J. Mass Spectrom. Ion Proc., 78, 53, 1987. 42. Karas, M. and Hillenkamp, F., Laser desorption ionization of proteins with molecular masses exceeding 10,000 daltons, Anal. Chem., 60(20), 2299, 1988. 43. Li, L., Garden, R.W., and Sweedler, J.V., Single-cell MALDI: A new tool for direct peptide profiling, Trends Biotechnol., 18(4), 151, 2000. 44. Caprioli, R.M., Farmer, T.B., and Gile, J., Molecular imaging of biological samples: Localization of peptides and proteins using MALDI-TOF MS, Anal. Chem., 69(23), 4751, 1997. 45. Chaurand, P., Stoeckli, M., and Caprioli, R.M., Direct profiling of proteins in biological tissue sections by MALDI mass spectrometry, Anal. Chem., 71(23), 5263, 1999. 46. Dreisewerd, K. et al. Direct mass spectrometric peptide profiling and sequencing of nervous tissues to identify peptides involved in male copulatory behavior in Lymnaea stagnalis, Int. J. Mass Spectrom. Ion Proc., 169/170, 291, 1997. 47. Garden, R.W. et al. Excess salt removal with matrix rinsing: Direct peptide profiling of neurons from marine invertebrates using matrix-assisted laser desorption/ ionization time-of-flight mass spectrometry, J. Mass Spectrom., 31(10), 1126, 1996. 48. Palmer-Toy, D.E. et al. Direct acquisition of matrix-assisted laser desorption/ ionization time-of-flight mass spectra from laser capture microdissected tissues, Clin. Chem., 46(9), 1513, 2000. 49. Redeker, V. et al. Combination of peptide profiling by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and immunodetection on single glands or cells, Anal. Chem., 70(9), 1805, 1998. 50. Stoeckli, M. et al. Imaging mass spectrometry: A new technology for the analysis of protein expression in mammalian tissues, Nature Med., 7(4), 493, 2001. 51. Troendle, F.J., Reddick, C.D., and Yost, R.A., Detection of pharmaceutical compounds in tissue by matrix-assisted laser desorption/ionization and laser desorption/chemical ionization tandem mass spectrometry with a quadrupole ion trap, J. Am. Soc. Mass Spectrom., 10, 1315, 1999. 52. van Veelen, P.A. et al. Direct peptide profiling of single neurons by matrix-assisted laser desorption–ionization mass spectrometry, Org. Mass Spectrom., 28(12), 1542, 1993.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 327/328

MS Imaging: New Technology Provides New Opportunities

327

53. Chaurand, P. et al. Profiling and imaging proteins in the mouse epididymis by imaging mass spectrometry, Proteomics, 3(11), 2221, 2003. 54. Reyzer, M.L. et al. Direct analysis of drug candidates in tissue by matrix-assisted laser desorption/ionization mass spectrometry, J. Mass Spectrom., 38(10), 1081, 2003. 55. Spengler, B. and Hubert, M., Scanning microprobe matrix-assisted laser desorption ionization (SMALDI) mass spectrometry: Instrumentation for sub-micrometer resolved LDI and MALDI surface analysis, J. Am. Soc. Mass Spectrom., 13, 735, 2002. 56. Berkenkamp, S. et al. Performance of infrared matrix-assisted laser desorption/ ionization mass spectrometry with lasers emitting in the 3 mm wavelength range, Rapid Commun. Mass Spectrom., 11, 1399, 1997. 57. Menzel, C., Berkenkamp, S., and Hillenkamp, F., Infrared matrix-assisted laser desorption/ionization mass spectrometry with a transversely excited atmospheric pressure carbon dioxide laser at 10.6 mm wavelength with static and delayed ion extraction, Rapid Commun. Mass Spectrom., 13, 26, 1999. 58. Schwartz, S.A., Reyzer, M.L., and Caprioli, R.M., Direct tissue analysis using matrix-assisted laser desorption/ionization mass spectrometry: Practical aspects of sample preparation, J. Mass Spectrom., 38(7), 699, 2003. 59. Krutchinsky, A.N. and Chait, B.T., On the nature of chemical noise in MALDI mass spectra, J. Am. Soc. Mass Spectrom., 13, 129, 2002. 60. Ayorinde, F.O. et al. Use of meso-tetrakis(pentafluorophenyl)porphyrin as a matrix for low molecular weight alkylphenol ethoxylates in laser desorption/ ionization time-of-flight mass spectrometry, Rapid Commun. Mass Spectrom., 13, 2474, 1999. 61. Jones, R.M., Lamb, J.H., and Lim, C.K., 5,10,15,20-meso-tetra(hydroxyphenyl)chlorin as a matrix for the analysis of low molecular weight compounds by matrixassisted laser desorption/ionization time-of-flight mass spectrometry, Rapid Commun. Mass Spectrom., 9(10), 968, 1995. 62. Huang, J.-P. et al. Rapid screening for diuretic doping agents in urine by C60assisted laser-desorption-ionization-time-of-flight mass spectrometry, J. Anal. Toxicol., 23, 337, 1999. 63. Kinumi, T. et al. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry using an inorganic particle matrix for small molecule analysis, J. Mass Spectrom., 35, 417, 2000. 64. Zhang, Q. et al. Matrix-assisted laser desorption/ionization mass spectrometry using porous silicon and silica gel as matrix, Rapid Commun. Mass Spectrom., 15, 217, 2001. 65. Shen, Z. et al. Porous silicon as a versatile platform for laser desorption/ionization mass spectrometry, Anal. Chem., 73(3), 612, 2001. 66. Wei, J., Buriak, J.M., and Siuzdak, G., Desorption–ionization mass spectrometry on porous silicon, Nature, 399, 243, 1999. 67. Cuiffi, J.D. et al. Desorption–ionization mass spectrometry using deposited nanostructured silicon films, Anal. Chem., 73(6), 1292, 2001. 68. Guo, Z. et al. A method for the analysis of low-mass molecules by MALDI-TOF mass spectrometry, Anal. Chem., 74, 1637, 2002. 69. Corr, J.J. et al. MALDI MS/MS on a triple quadrupole mass spectrometer: A new technology for high throughput small molecule quantitation, In Proc. 51st ASMS Conference, Montreal, Quebec, Canada, 2003.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-11.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 328/328

328

Using Mass Spectrometry for Drug Metabolism Studies

70. Reyzer, M.L. et al. Parallel monitoring of protein and drug expression in tissues by MALDI MS, In Proc. 51st ASMS Conference, Montreal, Quebec, Canada, 2003. 71. Hidalgo, M. et al. Phase I and pharmacologic study of OSI-774, and epidermal growth factor receptor tyrosine kinase inhibitor, in patients with advanced solid malignancies, J. Clin. Oncol., 19(13), 3267, 2001.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 329/356

Chapter 12 Understanding the Role and Potential of Infusion Nanoelectrospray Ionization for Pharmaceutical Bioanalysis Bradley L. Ackermann and Jean-Marie Dethy

12.1

Introduction

The position of liquid chromatography–tandem mass spectrometry (LC–MS/ MS) as the default method for pharmaceutical bioanalysis is well established. As described in previous review articles [1–4], LC–MS/MS derives its power by coupling the versatility of reversed-phase HPLC with the unique combination of selectivity and sensitivity afforded by tandem MS (MS/MS) detection. These combined advantages have had a profound impact on every major step of the bioanalytical process (i.e., method development, sample preparation and chromatography) leading to enhanced throughput compared to more conventional forms of on-line LC detection. The net result is that it is literally possible to perform in hours what once took days a decade ago. The throughput experienced in today’s bioanalytical laboratory was largely driven by necessity, given the vast increase in demand for sample analysis that occurred over the same time period. This shift in demand can be correlated with the increased production of chemical leads resulting from the introduction of techniques such as high-throughput screening (HTS) and combinatorial chemistry. Higher demand for bioanalysis also resulted from the widespread implementation of MS-based methods to assess the in vitro ADME 0-8493-1963-3/05/$0.00+$1.50 ß 2005 by CRC Press

Copyright © 2005 CRC Press, LLC

329

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 330/356

Using Mass Spectrometry for Drug Metabolism Studies

330

(absorption, distribution, metabolism, excretion) properties of lead molecules. To keep pace with this demand, a steady evolution in bioanalytical technology occurred encompassing virtually every step imaginable in the bioanalytical process. A detailed review of these technological advances is unfortunately beyond the scope of this chapter, but readers interested in this subject are referred to other chapters of this book as well as the review articles cited above. As LC–MS/MS technology matured over the past decade, a noteworthy trend occurred regarding its use. In addition to its more traditional role as a tool for dedicated bioanalytical assays, LC–MS/MS began to be deployed as a moderate throughput screening technology. Important illustrations include the now pervasive use of LC–MS/MS for in vitro ADME screens (e.g., metabolic stability, Caco-2) [5, 6] and the well-documented role of LC–MS/MS for in vivo exposure screening [7, 8]. Two factors are essential for successful application of LC–MS/MS as a screening tool: (1) high sample throughput and (2) the ability to rapidly achieve LC–MS/MS conditions for a diverse array of new molecular entities (NME). Unfortunately, LC contributes significant overhead to each of these categories. Even with the use of fast gradient elution techniques, chromatographic run times are on the order of 1 to 5 min per sample, depending on the application. In addition, time must also be invested to achieve suitable LC conditions prior to analysis. As a result of these factors, researchers have recently turned to approaches that do not require on-line LC. For the sake of this discussion, these techniques will be referred to as direct bioanalysis methods.

12.2

Review of Recent Literature

Admittedly, there are a number of potential pitfalls associated with direct bioanalysis, particularly surrounding concerns about assay sensitivity and selectivity. Despite these challenges, several methods continue to be pursued driven by the potential for increased throughput and reduced cost per sample. Perhaps the simplest form of direct bioanalysis is flow injection analysis (FIA). FIA simply refers to the practice of direct loop injection following some method for off-line sample cleanup. A published example is the work of Chen and Carvey who used FIA with liquid–liquid extraction (LLE) for the clinical bioanalysis of topiramate [9]. One of the drawbacks to FIA is dilution of the analyte by the injection stream, which is not preferred given the concentration dependence of ESI [10]. In the case of topiramate, the lower limit of quantitation (LLOQ) was only 2 mg/mL. Another example of FIA, published by Zheng and co-workers [11], employed FIA with generic off-line solid-phase extraction (SPE) for metabolic stability analysis. In this work, the rate of disappearance of 20 NMEs incubated with human liver microsomes was studied using two bioanalytical techniques: (1) acetonitrile precipitation followed by on-line LC-MS/MS, and (2) off-line OasisTM SPE followed by FIA-MS/MS. The authors concluded that both techniques gave comparable Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 331/356

Role and Potential of Infusion Nanoelectrospray Ionization

331

results for metabolic stability and that both sample preparation methods exhibited similar matrix effects on ESI. A commercially available method for direct bioanalysis, based on SPE, has recently been introduced. This method, referred to as the SPExpressTM [12], incorporates generic off-line extraction using 96-disk membrane-based SPE. In this technique, biological samples are first extracted by a high performance extraction card (HPEC) using a dedicated manifold. Following extraction, the HPEC is inserted into a second device that performs direct serial elution into the mass spectrometer for analysis. This approach, based on the pioneering work of Olech and co-workers [13], has been successfully applied for the bioanalysis of small molecules in plasma [14]. Other examples of direct bioanalysis have explored the potential of laser ionization techniques. Recently, Cole et al. demonstrated the high-throughput potential of matrix-assisted laser desorption/ionization (MALDI) for in vitro ADME screens by combining MALDI with MS/MS detection by selected reaction monitoring (SRM) on a triple quadrupole mass spectrometer [15]. While this technique shows great promise as a screening tool, fairly extensive sample clean-up is necessary to achieve good results due to the need to achieve effective crystallization of the MALDI sample matrix. A matrix-less version of MALDI known as desorption/ionization on silicon (DIOS) has also been used to obtain quantitative results for small molecules [16]. As with MALDI, further investigation will be needed to see if these methods can be effectively implemented as viable tools for direct bioanalysis in the pharmaceutical laboratory. This subject of this chapter is the potential of an emerging technology for direct bioanalysis, namely automated chip-based infusion nanoelectrospray ionization (nanoESI). In 2000, Schultz and co-workers succeeded in developing the first commercially available interface capable of incorporating a nanoESI array onto a silicon chip [17]. Since this time, this technology referred to as the ESI-ChipTM has been used primarily for large molecule applications including proteomics [18] and noncovalent interactions [19]. More recently, direct bioanalytical applications using the ESI-ChipTM have appeared [20–28]. Although true acceptance of this technology as a bioanalytical tool has not yet occurred, investigators hope to exploit the inherent advantages of this technology including throughput, increased sensitivity relative to FIA, low sample and reagent consumption, and the elimination of system carry-over. This chapter is organized in the following manner. In the section that follows, a description of the ESI-ChipTM technology is given along with the operational details of the Nanomate 100TM, a commercially available robotic unit which performs automated infusion nanoESI using a pipette tip interface. This section is followed by a review of recent applications of nanoESI for bioanalysis. The examples reviewed begin with screening applications found in drug discovery (in vivo and in vitro) and concludes with an example of a more rigorous method validation, typical of bioanalysis performed in support of drug development. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 332/356

Using Mass Spectrometry for Drug Metabolism Studies

332

The final section of this chapter addresses questions concerning the future direction of this technology. Since the application of automated infusion nanoESI is quite new, a number of fundamental and practical issues have yet to be addressed. This section discusses the potential and limitations of the current technology along with some current developments. The chapter concludes by offering a perspective on the importance of nanotechnology to future applications involving small molecule pharmaceutical analysis.

12.3

Instrumentation

The ESI-ChipTM (Advion Biosciences, Ithaca, NY) consists of a 10
10 array of nanoESI nozzles (10 mm i.d./20 mm o.d.) microfabricated on a silicon chip. Details regarding the design and production of the chip have been reported elsewhere [17]. A series of pictorial representations of the chip appears in Figure 12.1, beginning with a macroscopic view of an entire chip and consecutively scaled down in size to reveal an electron micrograph of a single nozzle. Figure 12.2 is a schematic side view of the chip illustrating the mechanism for sample delivery via a pipette tip interface. As shown, the sample is introduced to the back plane and flows through a 10-mm i.d. conduit, which terminates as a nanoESI nozzle on the front plane of the chip. A potential is applied from the robotic probe to the sample solution via the pipette tip, which contains graphite. Typical operating voltages are in the range of 1.3 to 1.6 kV. To achieve greater control over the flow rate of liquid through the chip, a slight positive pressure (0.1 to 4 psi N2) is applied through the probe. Operational flow rates are typically in the range of 50 to 500 nL/min. As indicated in Figure 12.2, the applied voltage induces an ESI plume from the chip nozzle. The high electric fields necessary for ESI are produced from the action of the charged liquid relative to an internal ground inside the chip serving as a counter electrode.

Figure 12.1 Sequential photographs of the ESI-ChipTM showing the array of microfabricated nanoESI nozzles with successive enlargements of an individual nozzle. This final scanning electron micrograph (SEM) shows a single nanoESI emitter with dimensions of 10 mm i.d. and 20 mm o.d. (Source: Van Pelt C.K. et al. Am. Lab., 35, 14, 2003. With permission.)

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 333/356

Role and Potential of Infusion Nanoelectrospray Ionization

333

Figure 12.2 Illustration showing the interface between the pipette tip sample delivery system and the ESI Chip. A robotic probe delivers sample (up to 10 mL) through a conductive pipette tip, which interfaces directly to the back plane of the ESI Chip. Voltage required for nanoelectrospray along with a slight positive pressure (N2) is delivered to the sample through the robotic probe. The ESI Chip was positioned near the atmospheric pressure ionization (API) sampling orifice of a triple quadrupole mass spectrometer. Reproduced from reference 20 with the permission of the American Chemical Society.

Figure 12.3 The Nanomate 100TM interfaced to the atmospheric pressure ionization interface of a commercial mass spectrometer. In this photograph the robotic arm is transferring a pipette tip loaded with sample to the back plane of the ESI-ChipTM (not visible). A rack holding 96 conductive pipette tips (black) as well as 96-well sample plate appear in the foreground of the photograph. (Source: Van Pelt C.K. et al. Rapid Commun. Mass Spectrom. 17, 2019, 2003. With permission.)

Robotic sample delivery and automated infusion nanoESI is performed using the Nanomate 100TM (Advion Biosciences, Ithaca, NY). A photograph of the Nanomate 100TM appears in Figure 12.3. Using appropriate mounting brackets, the Nanomate 100TM can be mounted in the atmospheric pressure ionization (API) interface region of several different mass spectrometers. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 334/356

Using Mass Spectrometry for Drug Metabolism Studies

334

As shown, the Nanomate 100TM contains a rack of 96 disposable pipette tips as well as a 96-well plate of samples to be analyzed. Plates are typically sealed with a thin grade Al foil to limit evaporation. To perform an analysis, the robotic arm of the Nanomate 100TM picks up a pipette tip and aspirates a sample from the 96-well plate. After pulling a sample volume between 2 and 10 mL, a user-defined air gap is aspirated to avoid leakage of sample from the tip during transit to the back plane of the chip. Next, the pipette tip is transferred by robotic arm to a specified location on the chip. Approximately 3 s before the initiation of flow through the chip, a contact closure occurs to initiate MS acquisition. Data are typically acquired for a period of 5 to 10 s after which the voltage is turned off and the analyte signal returns to baseline. This process results in an analyte signal having the appearance of a square wave. Peak areas are integrated using peak detection software supplied by the MS vendor allowing quantitative analysis to occur using standard vendorsupplied software. In all cases presented, an internal standard (IS) was co-analyzed and the peak area ratio (analyte:IS) was used for quantification. The total time for acquisition varies according to specifications supplied by the user, but the maximum sampling rate between consecutive infusions is currently 40 s. Additional experimental details are given as needed with the examples shown.

12.4

Current Uses of Technology

In this section, four recent bioanalytical applications of infusion nanoESI are presented. The examples selected give an indication of the range of potential applications, including in vitro and in vivo uses as well as applications to research and development. 12.4.1

In vivo bioanalysis of plasma following protein precipitation

An initial study testing the feasibility of infusion nanoESI for direct bioanalysis was undertaken by our laboratory [20]. For this investigation, protein precipitation (PPT) without further sample clean-up was selected to present a challenging test for this new technology. Moreover, the compatibility of this technology with PPT is important for drug discovery applications, which seek to avoid the time, and cost associated with formal extraction techniques, such as solid-phase extraction (SPE) and liquid–liquid extraction (LLE). For this investigation all data were obtained using a prototype of the Nanomate 100TM interfaced to a Micromass Quattro II triple quadrupole mass spectrometer. Two analytes were studied, the drug verapamil and its desmethyl metabolite, norverapamil (Figure 12.4). Each compound, purchased as a commercial standard, was spiked into control (drug-free) human plasma to prepare a series of standard curves. In each case, plasma aliquots (100 mL) were mixed with 100 mL of internal standard solution containing 50 ng gallopamil (Figure 12.4) followed by the addition of 400 mL acetonitrile/ethanol/acetic Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 335/356

Role and Potential of Infusion Nanoelectrospray Ionization

335

Figure 12.4 Chemical structures and nominal molecular weights for verapamil, its active metabolite norverapamil and the internal standard, gallopamil. (Source: Dethy, J.M. et al. Anal. Chem. 75, 805, 2003. With permission.)

acid (90/10/0.1, v/v/v). After vortexing for 30 s, the samples were centrifuged at 10,000
g for 10 min. The supernatant was transferred to clean glass tubes and evaporated under nitrogen. Samples were reconstituted in 200 mL of acetonitrile (0.1% acetic acid) and re-centrifuged (10,000
g for 10 min) to remove particulate matter. Ten-mL aliquots were sampled for bioanalysis by the Nanomate 100TM. Data acquisition occurred by SRM over a period of 30 s using a 400 ms dwell time for each SRM channel and a collision energy of 35 eV for all analytes. The overall sampling time between injections was approximately 1 min. A standard curve consisting of a series of nanoESI infusions from the analysis of verapamil and norverapamil appears in Figure 12.5. The square wave-like appearance of nanoESI infusion profile is readily apparent from this data set. It should be noted that each rectangular offset in the SRM mass chromatograms represents a single injection from a separate, consecutive nozzle on the chip. The upper portion of Figure 12.5 contains three SRM mass chromatograms for gallopamil (m/z 485.1 to 164.8), verapamil (m/z 455.0 to 164.8) and norverapamil (m/z 441.0 to 164.8). A total of eight standard concentrations were analyzed ranging from 2.5 to 500 ng/mL. An expanded Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 336/356

336

Using Mass Spectrometry for Drug Metabolism Studies

Figure 12.5 (a) Series of eight nanoelectrospray infusion ion current profiles representing a single standard curve prepared by spiking drug-free human plasma with the internal standard, gallopamil (upper), verapamil (middle) and norverapamil (lower). Each flat-top deflection in the SRM ion current profiles corresponds to a single sample analyzed from a different ESI nozzle. The standard concentrations represented for verapamil and norverapamil are 2.5, 5.0, 10, 25, 50, 100, 250, and 500 ng/mL. The internal standard concentration was 500 ng/mL. (b) Expanded view of the lowest four standards analyzed in panel. (Source: Dethy, J.M. et al. Anal. Chem. 75, 805, 2003. With permission.)

view at the bottom of Figure 12.5 was included to allow better observation of the four lowest standards. The bioanalytical precision and accuracy of the ESI ChipTM technology were assessed through the analysis of multiple standard curves for verapamil Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 337/356

Role and Potential of Infusion Nanoelectrospray Ionization

337

Table 12.1 Precision and accuracy data obtained from the nanoelectrospray infusion determination of verapamil and norverapamil in human plasma Verapamil Standard (ng/mL) 2.5 5.0 10 25 50 100 250 500

Norverapamil

Mean (ng/mL)

%RSD

%Accuracy

Mean (ng/mL)

%RSD

%Accuracy

n

2.6 4.6 9.8 24.2 51.0 99.4 252 497

33 11 7 9 9 7 7 4

102 93 98 97 102 99 101 99

2.7 4.9 8.9 20.6 43.9 92.9 234 445

27.7 19.6 5.7 18.7 16.8 14.1 9.7 6.3

109 98 89 83 88 93 93 89

9 8 9 8 9 6 7 10

Source: Dethy, J.M. et al. Anal. Chem., 75, 805, 2003. With permission.

and norverapamil. In this experiment, the first set of standards analyzed was used to define the calibration curves for each analyte. Subsequent analysis of replicate standards resulted in the precision and accuracy data found in Table 12.1. For both analytes the precision was under 20% relative standard deviation, except for the lowest standard (2.5 ng/mL). Due to the high degree of imprecision at this level, the lower limit of quantitation (LLOQ) was assigned as 5 ng/mL for both verapamil and norverapamil. Overall the precision ranged from 4 to 11% RSD (relative standard deviation) for verapamil and from 5.7 to 19.6% RSD for norverapamil. Accuracy values shown in Table 12.1 represent mean values for the replicates at a given concentration following interpolation of individual concentrations from the calibration curve. The accuracy values for verapamil ranged from 93 to 102% and from 83 to 98% for norverapamil. In evaluating these data, it is acknowledged that overall precision and accuracy found in Table 12.1 would not meet the more rigorous acceptance criteria associated with GLP (good laboratory practice) validation [29]. Nonetheless, these data are consistent with the expectations of discovery bioanalysis. Calibration curves for verapamil and norverapamil were constructed by plotting the peak area ratio of analyte to internal standard versus analyte plasma concentration. The curves, fit using linear regression with 1/X weighting, were linear over the range tested (2.5–500 ng/mL). The following straight-line equations and correlation coefficients were obtained: for verapamil, y ¼ 0.00180x þ 0.00141 (r2 ¼ 0.999); and for norverapamil, y ¼ 0.00105x þ 0.00017 (r2 ¼ 0.9998). Prior to assessing system carry-over, the selectivity of the method was first established for both verapamil and norverapamil through the analysis of blank (drug-free) human plasma. Having demonstrated selectivity for both analytes, the question of system carry-over was investigated. Figure 12.6 displays SRM ion current profiles for verapamil (top) and the internal standard gallopamil (bottom) for a series of three consecutive nanoESI infusions. The first infusion period (12.5 to 13.3 min) indicates the signal observed from a 500 ng/mL Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 338/356

338

Using Mass Spectrometry for Drug Metabolism Studies

Figure 12.6 SRM ion current profiles for verapamil (upper) and gallopamil (lower) indicating the signal obtained from three sequential nanoelectrospray infusions used to assess system carryover. The first infusion (12.5 to 13.3 min) shows the signal observed from a 500 ng/mL verapamil human plasma standard. This fusion was immediately followed by the analysis of a blank human plasma sample. The analysis period for this sample (14.0 to 14.8 min) is delineated by two dotted lines. The final infusion (15.5 to 16.2 min) corresponds to the analysis of a blank plasma sample containing internal standard. (Source: Dethy, J.M. et al. Anal. Chem. 75, 805, 2003. With permission.)

verapamil plasma standard. Immediately after this high standard a drug-free blank plasma sample was infused. Data from this second infusion appear in the period from 14.0 to 14.8 min (defined by the two dotted lines in Figure 12.6). It is noteworthy that the signal observed during this period did not exceed the level of background noise present during sample loading (i.e., no spray; 13.3 to 14.0 min). This infusion was followed by the analysis of a blank plasma sample containing the internal standard (15.5 to 16.2 min). The results from this experiment document the complete elimination of system carry-over and are representative of the standard performance of this system. As expected, no carry-over was detected in the concomitant analysis of norverapamil (data not shown). One of the advantages of direct bioanalysis by infusion nanoESI is that the infused solution can contain a high organic solvent content. This not only leads to higher analyte signal through improved desolvation, but is also likely to limit salt content in the infused solution. The effect of the composition of the infused solution was investigated by using two schemes for protein precipitation. In the first scheme (process 1), a 100-mL plasma sample fortified with 100 mL of internal standard solution was precipitated using 200 mL acetonitrile/ ethanol/acetic acid (90/10/0.1, v/v/v). In this case, the supernatant was infused immediately after the centrifugation step. process 2 was similar to process 1, Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 339/356

Role and Potential of Infusion Nanoelectrospray Ionization

339

Figure 12.7 Comparison of the sensitivity for verapamil human plasma standards (2.5, 5.0, and 10 ng/mL) obtained using two sample preparation schemes. Process 1: 100 mL plasma sample plus 100 mL internal standard was precipitated using 200 mL acetonitrile/ethanol/acetic acid (90/10/0.1, v/v/v), centrifuged and directly infused using the Nanomate 100. Process 2: an expanded version of process 1 involving an evaporation of the original supernatant followed by reconstitution in 200 mL acetonitrile (0.1% acetic acid) and re-centrifugation. The sample was infused under the same analysis conditions as process 1. (Source: Dethy, J.M. et al. Anal. Chem. 75, 805, 2003. With permission.)

except that the supernatant from precipitation was dried down under nitrogen, reconstituted in 200 mL acetonitrile/ethanol/acetic acid (90/10/0.1, v/v/v) and re-centrifuged as described previously. Although process 1 leads to greater overall throughput, process 2 was found to yield superior data as well as greater robustness. Process 1 and 2 are compared in Figure 12.7, which displays a series of standards at the low end of the calibration curve for verapamil. An approximate 5-fold enhancement in signal-to-noise was observed using the expanded procedure (process 2), which was greater than the effect predicted from sample concentration alone (i.e., 2-fold). An obvious explanation to account for the signal difference observed is the different water content of the two samples. However, this would not explain the more erratic signal since the ESI-ChipTM is readily capable of spraying 100% aqueous solutions. It is believed that the added steps introduced in process 2 improve robustness by limiting both the amount of salt and suspended particulate matter in the infused solution. 12.4.2

In vitro bioanalysis: Caco-2 permeation screening

Caco-2 is a human intestinal epithelial cell line derived from a human colorectal carcinoma. This cell line has been extensively used as a model of drug absorption since permeability across a Caco-2 monolayer has been shown to correlate with in vivo human absorption [30]. LC–MS/MS is widely used to support Caco-2 permeation studies, but often has run times in the range of 2 to 5 min per sample. In addition, a finite time is required to achieve suitable conditions for LC–MS/MS. Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 340/356

340

Using Mass Spectrometry for Drug Metabolism Studies

Figure 12.8 Diagram of a well used for Caco-2 experiments. A confluent monolayer of Caco-2 cells is grown on a PET membrane. In the experiment, the cells are submerged in HBSS buffer, making an apical (donor) reservoir and a basolateral (receiver) reservoir, which are divided only by the monolayer of Caco-2 cells. The drug candidate to be tested is dosed into the apical reservoir. Aliquots are removed from the apical reservoir at 0 min, and then from both the apical and basolateral reservoirs at 120 min. (Source: Van Pelt, C.K. et al. Rapid Commun. Mass Spectrom. 17, 1573, 2003. With permission.)

A recent publication by Van Pelt et al. described an investigation that compared an existing LC–MS/MS procedure with the ESI-ChipTM for analysis of Caco-2 samples [22]. In this investigation two proprietary compounds synthesized at Schering-Plough (Kenilworth, NJ) were tested for Caco-2 permeability using standard methodology. For reasons of confidentiality the structures for these compounds, referred herein as A and B, were not disclosed. Aliquots of the samples derived from these transport experiments were divided and analyzed by the two methods of analysis. A diagram of the apparatus used to conduct the Caco-2 transport studies related to this investigation is shown in Figure 12.8. As indicated in this diagram, a confluent monolayer of Caco-2 cells were grown on a porous polyethylene terephthalate (PET) filter connected to the upper (donor) chamber. The donor reservoir is often referred to as the apical side referring to the orientation of the Caco-2 cells, which are asymmetric and contain microvilli on the apical side to promote absorption. These microvilli are directed towards the donor chamber. The lower (receiver) chamber is referred to as the basolateral reservoir in reference to the orientation of the cells on the filter consistent with physiological transport towards the mesenteric circulation. The permeability of compounds A and B was measured in duplicate (i.e., two Caco-2 filters). In each case, 10 mM of the test compound was placed in the upper chamber (0.4 mL) in HBSS (Hanks’ balanced salt solution) containing 10 mM MES (2-morpholinoethanesulfonic acid) and 10 mM d-glucose at pH 6.5. The basolateral wells contained 1.0 mL HBSS buffer containing 10 mM HEPES (N0 -(2-hydroxyethyl)piperazine-N-ethanesulfonic acid), 10 mM d-glucose, and 4% BSA (bovine serum albumin) at pH 7.4. Aliquots were removed for analysis from the donor well at 0 and 120 min and the basolateral Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 341/356

Role and Potential of Infusion Nanoelectrospray Ionization

341

Table 12.2 Summary of standard curve reproducibility from the Caco-2 analysis of two proprietary compounds (A and B). The standards were analyzed by infusion nanoESI/MS/MS following C18 SPE Standard concentration (nM) 20 50 100 300 500

Mean ratio of A to IS (n ¼ 3)

%CV (A/IS)

Mean ratio of B to IS (n ¼ 3)

%CV (A/IS)

0.795 1.87 5.12 12.6 23.7

26.8 7.18 0.45 8.26 2.81

0.608 2.29 2.59 12.8 25.0

6.91 7.52 12.1 9.55 6.35

Adapted from Van Pelt, C.K. et al. Rapid Commun. Mass Spectrom., 17, 1573, 2003. With permission.

well at 120 min. The apical aliquots were diluted 40-fold with HBSS buffer prior to analysis. One-half of each aliquot was analyzed by LC–MS/MS at the Schering-Plough Research Institute (Kenilworth, NJ) and the other half was analyzed by nanoESI-MS/MS at Advion BioSciences (Ithaca, NY). For logistical reasons, different internal standards were used. LC–MS/MS analysis used alprazolam, while infusion nanoESI–MS/MS used corticosterone. Due to the presence of protein in the Caco-2 samples (i.e., 4% BSA), an acetonitrile PPT step was used with both methods of analysis. In the case of infusion nanoESI an additional SPE desalting step was incorporated due to the high salt content in the samples. SPE was conducted with C18 ZipTipsTM (Millipore, Bedford, MA), which are individual pipette tips filled with stationary phase. This format is well suited for use with infusion nanoESI because relatively small elution volumes may be used (5–20 mL). To verify the capability of the ZipTipTM procedure with infusion nanoESI/MS/MS, a series of standard curves were prepared by spiking compounds A and B into control Caco-2 buffer and analyzed. For this experiment five-point standard curves were prepared in triplicate spanning a range in concentration from 20 to 500 nM. Table 12.2 contains data from the calibration standards run for each compound and gives an idea of the precision obtained. With the exception of one standard level in each curve, the precision was <10% CV (n ¼ 3) in all cases. A significant outcome from this investigation was the close correspondence in the results derived for permeability and recovery between the two assays. The equations used to calculate these terms can be found in the publication by Van Pelt et al. [22]. Permeability is essentially calculated by comparing the amount of compound in the basolateral side at 2 h relative to the total compound in the apical side at the beginning of the experiment. The percent recovery, on the other hand, sums the compound observed in the upper and lower chambers at 2 h and divides by the amount measured in the donor chamber at the start of the experiment. Table 12.3 shows a comparison of the results calculated for the two independent methods. It is clear from these data that compound A has a much higher permeability than compound B. The data also show that Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 342/356

Using Mass Spectrometry for Drug Metabolism Studies

342

Table 12.3 Comparision of Caco-2 permeability and percent recovery data for proprietaty compounds A and B analyzed using two independent analytical techniques. The results presented represent the mean of two separate permeability determinations for each compound Compound Compound A Permeability (nm/s) Recovery (%) Compound B Permeability (nm/s) Recovery (%)

On-line LC-MS/MS 135 29 15.0 81

Off-line nanoESI/SM/MS with SPE de-salting 128 24 17.5 90

Adapted from Van Pelt, C.K. et al. Rapid Commun. Mass Spectrom., 17, 1573, 2003. With permission.

compound A had a much lower percent recovery than compound B. The close agreement in the permeation results as well as the percent recoveries attests to the validity of infusion nanoESI for quantitative determination. 12.4.3

In vitro bioanalysis: hepatic microsomal metabolic stability

One of the most commonly applied in vitro ADME screens is hepatic metabolic stability. In this screen NMEs are incubated with hepatic media, such as microsomes or hepatocytes, to assess their overall susceptibility towards hepatic metabolism. For this work, LC–MS/MS is typically used to determine either a percent metabolism (i.e., 100% disappearance) or a disappearance half-life. Because initial NME concentrations tend to be in the 1 to 5 mM range, sensitivity is typically not a major issue. The main difficulty lies in the need to develop a single robust set of LC–MS/MS conditions that apply to the multitude of chemical diversity encountered in drug discovery. In addition, MS/MS conditions must be obtained for each molecule. Fortunately, this latter issue has been addressed using automated acquisition software [31]. For years in our laboratory, we have used LC–MS with selected ion monitoring (SIM) on a single quadrupole MS for metabolic stability determination. We have found that MS/MS detection is not needed owing to extensive on-line clean-up that occurs via alternate–regenerate column switching [32]. While this method has been shown to be extremely robust, some classes of molecules are not readily analyzed due to low ESI signal or poor chromatography. As mentioned previously, Zheng and co-workers demonstrated the use of FIA with off-line SPE as a viable approach for metabolic stability determination [11]. Based on our initial success in performing verapamil determination in plasma [20], we decided to test the ability of the ESI-ChipTM for use with metabolic stability using only PPT as the means of sample preparation. While a desalting step certainly could have been incorporated, it adds additional time and expense, which are important considerations when performing moderate throughput screening. The conditions used for microsomal metabolic stability involve automated incubation in a 96-well format. Briefly, NMEs (4 mM) were incubated at 37 C Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 343/356

Role and Potential of Infusion Nanoelectrospray Ionization

343

with human liver micosomes (XenoTech, Lenexa, KS) at 1 mg/mL (total protein) with or without the addition of NADPH (2 mM), a co-factor needed for phase I hepatic oxidation. The incubation was buffered at pH 7.4 using 50 mM sodium phosphate and had a total incubation volume of 100 mL. Following a pre-incubation period to bring the reagents to 37 C, the reaction was initiated by addition of the NME-containing solution. Incubation occurred for 30 min and was stopped with the addition of 100 mL acetonitrile/methanol/water/acetic acid (25/25/50/0.5, v/v/v/v). The supernatant obtained after centrifugation was injected for LC–MS analysis. For infusion nanoESI, the microsomal supernatant (100 mL) was mixed with 200 mL of internal standard solution containing 100 ng gallopamil (Figure 12.4) in acetonitrile/water/acetic acid (50/50/0.1, v/v/v). The final solution was centrifuged prior to infusion nanoESI using the Nanomate 100TM. The operating conditions used were similar to those applied previously for plasma analysis [20] with the exception that SIM detection was used instead of SRM. This decision was made to allow direct comparison to the LC–MS results, which also used SIM. Table 12.4 contains the results for 12 marketed drugs studied in this preliminary comparison. The data indicate that, in general, a high correlation was found between the two methods, although the data set obtained by nanoESI was unfortunately incomplete. While all 12 drugs were detected by positive ion ESI using the column switching method, only 11 compounds were detected by nanoESI. It is noted that the single compound not detected by

Table 12.4 Comparison of metabolic stability data for 12 drugs analyzed by two separate analytical techniques Drug Carbamazepine Propranolol Dextromethorphan Promethazine Imipramine Bufuralol Diltiazem Tolbutamide Erythromycin Propafenone Verapamil Diclofenac

Percent metabolism LC–ESI/MS

Percent metabolism Infusion nanoESI/MS

10.9 20.9 25.0 28.1 31.4 32.1 34.3 36.4 41.1 59.0 62.9 89.5

0.0* 10.3 31.0 0.0* 0.0* 32.5 40.7 0.0* 39.5 58.7 63.6 n.d.

In both cases drugs (4 mM) were incubated with human liver microsomes and the percent metabolism after 30 min was determined either by LC–ESI/MS or by infusion nanoESI/MS. The MS detection scheme used in both cases was selected ion monitoring (SIM). The protonated parent molecule was monitored in all cases. *No metabolism evident; high matrix background in SIM mode too high to observe signal difference related to metabolism. n.d., not detected. Table Adapted from Dethy, J.M. et al. Proc. 51st Conf. Mass Spectrom. and Allied Topics. With permission.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 344/356

Using Mass Spectrometry for Drug Metabolism Studies

344

nanoESI, diclofenac, is often analyzed under negative ion conditions and that negative ion conditions were not employed in the existing study. Another recognized difference between the two data sets is that four of the 12 compounds analyzed by nanoESI exhibited a spurious value of zero percent metabolism. This phenomenon was attributed to high matrix background, since all compounds, with the exception of diclofenac, were readily detected as neat solutions. SIM conditions were employed in this study to allow direct comparison to the column-switching LC–MS approach. It is clear from these results that MS/MS detection is a prerequisite for successful bioanalysis by infusion nanoESI. The incorporation of MS/MS detection with metabolic stability screening is currently being investigated. In addition to matrix interference, matrix-related ion suppression also affects the observed analyte signal (see Chapter 4 for more on this topic). To investigate this phenomenon, three of the 12 compounds listed in Table 12.4 were subjected to a formal assessment of ion suppression. In this experiment, replicate infusion of a neat solution was compared to replicates obtained from spiking the same amount of neat compound into control matrix that had not been extracted. The method cited above for PPT was applied to both sample sets. The overall matrix ion suppression observed for erythromycin, bufuralol, and diltiazem was 75, 84, and 73%, respectively. While this level of ion suppression is significant, it should be noted that strong agreement was still observed between the two methods. The following conclusions can be drawn from this investigation. First, ion suppression by NADPH did not seem to play a major role in this investigation. Since one-half of the samples did not contain NADPH, there was concern about ionization suppression affecting the results. The close correlation between the metabolic stability results for compounds not affected by matrix interference suggests that this was not the case. One explanation is that the NADPH was largely insoluble in the final solution taken for infusion. Ultimately, this investigation showed the possibility of infusion nanoESI for metabolic stability assessment without the need for sample clean-up by SPE. Although not rigorously established in this limited study, the likelihood of instrument robustness is high, despite the lack of sample clean-up, due to the finite sample volume used per analysis. Finally, it is fully acknowledged that an understanding of the true utility of this approach will require a vastly expanded investigation and will need to incorporate MS/MS detection.

12.4.4

In vivo bioanalysis: expanded method validation and sample clean-up

The final example is an illustration of the potential use of infusion nanoESI for clinical bioanalysis. In contrast to the discovery-based applications presented to this point, clinical applications require a higher level of validation, similar to what is expected for GLP–toxicology assays [29]. In this particular example, Kapron and co-workers quantified the drug midazolam in human plasma by Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 345/356

Role and Potential of Infusion Nanoelectrospray Ionization

345

Figure 12.9 Structure, formula, molecular weight, and transitions monitored for midazolam and the internal standard alprazolam. (Source: Kapron, J.T. et al. Rapid commun. Mass Spectrom. 17, 2019, 2003. With permission.)

infusion nanoESI/MS/MS using the structural analog alprazolam as the internal standard [23]. Midazolam is well recognized in drug development as a selective substrate for cytochrome P450 isoform 3A4. Not surprisingly, several assays have been reported for midazolam [33, 34], which is routinely co-administered with drug candidates in controlled clinical studies to assess drug–drug interaction potential. Structures for midazolam and alprazolam appear in Figure 12.9 along with the positive ion SRM transitions used for each molecule. Representative SRM infusion profiles for the upper limit of quantitation (500 ng/mL) appear in Figure 12.10. As part of this study, three variations of sample preparation were compared: (1) PPT, (2) direct SPE, and (3) PPT followed by SPE. In all cases 30-mL aliquots of human plasma were taken for analysis. For methods involving PPT, acetonitrile (100 mL) containing alprazolam was used. Both variations of SPE were performed off-line using individual C18 ZipTipTM cartridges. The conditions applied for the final reported method incorporated both PPT and SPE. This combined approach was used since it yielded greater overall signal for midazolam than was observed for PPT only (2.5-fold) or SPE only (2-fold). This method was subsequently validated over a range of 1.5 to 500 ng/mL using the following standard curve points; 1.5, 3.0, 10, 25, 100, 250, and 500 ng/mL. Quality control (QC) samples were analyzed at three concentrations: 3, 250, and 400 ng/mL. Three runs were performed to assess the precision and accuracy of the method. Table 12.5 shows results for the precision and accuracy obtained based on QC samples prepared independently of the standard samples. The intra-assay precision (n ¼ 5) was 16% and the inter-assay precision was 5%, as determined by ANOVA. Using mean values for the QC samples (n ¼ 15) the Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 346/356

346

Using Mass Spectrometry for Drug Metabolism Studies

Figure 12.10 Representative ion current profiles for midazolam (a) at the ULOQ (500 ng/mL) and the internal standard alprazolam (b, 4070 ng/mL) extracted from human plasma. (Source: Kapron, J.T. et al. Rapid Commun. Mass Spectrom. 17, 2019, 2003. With permission.)

Table 12.5 Precision and accuracy data for the determination of midazolam in human plasma by infusion nanoESI/MS/MS as assessed from QC samples prepared independently from standard samples Midazolam concentration Run number Run 1

Run 2

Run 3

Overall Mean Overall Accuracy (% dev) Intra-assay precision (%)b Inter-assay precision (%)b a

QC-1 3 ng/mL 3.14 2.78 3.03 2.94 2.85 3.04 3.08 2.41 2.83 5.14a 3.13 3.14 2.94 3.10 2.54 2.93 2.5 8.1 NV

QC-2 250 ng/mL

QC-3 400 ng/mL

295 268 307 265 264 237 222 215 229 266 262 256 233 226 219

388 505 521 428 392 402 403 572 442 333 401 482 411 452 384

251 0.4 7.8 4.2

434 8.6 15.4 NV

Low IS response, eliminated using Q-test and not used in calculations. Intra- and inter-assay precision determined by ANOVA. NV: no significant additional variation was observed as a result of performing the assay on different days. Source: Kapron, J.T. et al. Rapid Commun. Mass Spectrom., 17, 2014, 2003. With permission. b

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 347/356

Role and Potential of Infusion Nanoelectrospray Ionization

347

Table 12.6 Inter-chip variability observed for the determination of midazolam standards spiked into control human plasma. Samples were prepared by protein precipitation followed by SPE. Analysis was conducted by nanoESI/MS/MS as described in Reference 23

Chip number 1 2 3 4 5 Mean Accuracy (% dev) Precision (%CV)

STD 1 1.5 (ng/mL)

STD 2 3.0 (ng/mL)

STD 3 10 (ng/mL)

STD 4 25 (ng/mL)

STD 5 100 (ng/mL)

STD 6 250 (ng/mL)

STD 7 500 (ng/mL)

1.22 1.29 1.22 1.52 1.53

2.81 2.94 3.11 3.08 3.30

10.3 9.62 10.4 10.4 10.9

26.1 26.4 25.1 27.1 27.2

95.3 103 103 109 107

239 212 245 261 246

437 504 537 498 548

1.36 9.6 11.6

3.05 1.6 6.1

10.3 3.2 4.4

26.4 5.5 3.2

104 3.5 5.0

241 3.8 7.5

505 1.0 8.6

Source: Kapron, J.T. et al. Rapid Commun. Mass Spectrom., 17, 2019, 2003. With permission.

overall accuracy of the method was found to be within 9% deviation from theoretical at each concentration. To demonstrate post-preparative stability as well as the reproducibility of the method, prepared samples from run 1 were stored at room temperature for 24 h. Re-analysis of the samples yielded a precision of 15% CV and accuracy within 15% deviation from theoretical at each QC concentration [23]. Since multiple chips were used during method validation, the issue of inter-chip variability was investigated by infusing single replicates of the seven standard concentrations using five different chips. The combined data from this experiment appear in Table 12.6 At least 75% of the individual backcalculated concentrations were within 15% of theoretical and within 20% at the LLOQ. The mean accuracy values were within 10% deviation from theoretical and the precision was 12% CV at each standard concentration. It can be concluded from this experiment that high chip-to-chip reproducibility has been achieved using the current process for microfabrication. An investigation using six different lots of human plasma, chosen at random, was also conducted. For this experiment, individual plasma standards were prepared from each lot at both the LLOQ and the ULOQ (upper limit of quantitation). A summary of the results appears in Table 12.7 Determination of midazolam at the LLOQ in five of the six lots resulted in concentrations within 20% of the theoretical concentration (Table 12.7). Although one of the determinations was outside of the expected range (LLOQ, lot 3), the %CV of the six determinations was 12.7% and 8.4%, respectively, at the LLOQ and ULOQ. In addition, the mean accuracy of the six determinations was within 3% deviation from theoretical at the LLOQ and within 9% at the ULOQ. The issue of system carry-over was also investigated by Kapron et al. [23]. The results of their investigation appear in Figure 12.11, which shows a series of infusion chromatograms for midazolam (Figure 12.11(A)) and alprazolam (Figure 12.11(B)) acquired at the LLOQ. In Figure 12.11(A), three profiles are shown representing the following sequence of analysis: zero sample (matrix Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 348/356

Using Mass Spectrometry for Drug Metabolism Studies

348

Table 12.7 Results from the infusion nanoESI/MS/MS determination of midazolam using six different lots of human control plasma selected at random Midazolam concentration Matrix lot Lot Lot Lot Lot Lot Lot

1 2 3 4 5 6

Overall mean Overall accuracy (%Dev) Variability (%CV)

LLOQ (1.5 ng/mL)

Individual accuracy (%)

1.74 1.37 1.82 1.47 1.37 1.44

16.0 8.7 21.3 2.0 8.7 4.0

1.54 2.3 12.7

ULOQ (500 ng/mL) 466 486 509 435 411 425

Individual accuracy (%) 6.8 2.8 1.8 13.0 17.8 15.0

455 8.9 8.4

Source: Kapron, J.T. et al. Rapid Commun. Mass Spectrom., 17, 2019, 2003. With permission.

Figure 12.11 Representative ion current profiles for three different samples demonstrate no carryover and define the background signal before and after the standard samples. (A) Midazolam in a zero sample infused before the LLOQ, in a sample at the LLOQ (1.5 ng/mL), and in a zero sample following the ULOQ (carryover sample). The SRM signal for midazolam in the carryover sample is essentially unchanged from the zero sample before the standards, even when infused after a high concentration sample. (B) The alprazolam traces demonstrate consistent abundance for these three samples indicating comparable sensitivity for each of the samples. (Source: Kapron, J.T. et al. Rapid commun. Mass Spectrom. 17, 2019, 2003. With permission.)

blank þ IS); LLOQ (after zero sample); LLOQ (after ULOQ). As can be seen in Figure 12.11(A), the blank signal in the midazolam SRM channel was not increased by injection immediately after the injection of the ULOQ standard. This result, when combined with the data in Figure 12.11(B) showing Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 349/356

Role and Potential of Infusion Nanoelectrospray Ionization

349

consistent response for the internal standard, confirms the avoidance of system carryover. The midazolam application by Kapron et al. indicates the potential of infusion nanoESI for applications in drug development. The elimination of system carryover is a powerful advantage of this technology, particularly for validated applications, where a considerable fraction of method development time is devoted to this issue. Another potential use of this technology is for multi-analyte assays, such as drugs and metabolites, or parent and pro-drug combinations. Such applications require additional chromatographic methods development and require extractions to be less selective than single analyte assays. Infusion nanoESI would appear well suited to such situations, provided cases are selected that do not need LC separation for selectivity. A recent example of a multianalyte assay was reported by Leuthold et al. [24]. This work, which was conducted on a linear ion trap instrument, used infusion nanoESI/ MS/MS to quantify a drug and its desethyl metabolite in human plasma. The method, which involved LLE and used a stable labeled isotope internal standard for the parent drug, was validated over a range from 2.5 to 1000 ng/mL. Although these preliminary investigations appear promising, further investigations involving direct comparisons to existing LC–MS/MS methods will be needed to understand the role and potential of infusion nanoESI/MS/MS for validated assays and before this work can truly be applied for GLP bioanalysis.

12.5 12.5.1

Future Work Nano ESI

As indicated by the four preceding examples, automated infusion nanoESI has been demonstrated as a viable technique for several forms of pharmaceutical bioanalysis. However, despite the initial excitement surrounding this technology, it is important to acknowledge that infusion nanoESI has not been fully reduced-to-practice for routine bioanalytical applications. In the section that follows, the promise and potential pitfalls of this technology are addressed based on current knowledge and experience. How this technology ultimately fares compared to existing methods will depend on several factors such as robustness, reliability (quality) and cost effectiveness. These issues are discussed along with some fundamental experiments that remain to be performed. Recent or ongoing upgrades to the Nanomate 100TM will also be mentioned. Depending on the method used for sample preparation, nanoESI would appear to be robust enough for routine use. Based on our own experience, care must be taken to avoid particulate matter, which can clog the ESI nozzles on the chip. Nevertheless, good precision and accuracy data can be derived in biological matrices using only PPT when a suitable internal standard is Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 350/356

350

Using Mass Spectrometry for Drug Metabolism Studies

employed. As cited earlier, MS robustness is not an issue, even without sample cleanup, given the finite sample volumes used with nanoESI. A key issue surrounding robustness is nozzle-to-nozzle failure rate. Even when care is taken to remove particulate matter, a small percentage of nozzles fail to spray. Advion currently claims a success rate of 97% and is actively inserting greater quality control in the manufacturing processes for both chips and pipette tips to reduce the number of failed infusions. A failure rate of 3% is still not desirable since sample re-injection would almost always be necessary for most sample batches. To avoid this problem, software controls are being incorporated to block the use of nozzles on a chip deemed to be suspect from post-manufacturing inspection. In addition, feedback software is being written to automatically schedule a re-infusion for samples where no spray was observed. With implementation of these efforts, it is believed that the issue of failed infusions will not be a major factor in the use of this technology. An important issue, which has not yet been fully addressed, relates to ion suppression. This was first described for bioanalysis by Buhrman et al. [35], and relates to a decrease in analyte signal resulting from the competition for ionization from either matrix-related components or other analytes. In recent years, the influence of ion suppression has been widely studied due to its negative impact on bioanalytical performance [36]. It is generally accepted that ion suppression affects ESI to a greater extent than atmospheric pressure chemical ionization (APCI) [37] and that it is more problematic for weakly retained analytes (low k0 ) owing to the competition from salts [36]. More recently, it has been shown that ion suppression can arise from sources not directly related to the biological sample matrix [38], including the dosing vehicle [39, 40]. Obviously, without prior sample desalting by SPE or LLE, infusion nanoESI is directly exposed to the influence of any co-infused sample components. One could ask, why then would anyone consider direct bioanalysis by infusion nanoESI using only PPT as the method for sample preparation? To answer this question, the unique attributes of nanoESI as an ionization method must be considered. Because nanoESI is believed to be less susceptible to ion suppression than ESI at conventional flow rates [41], it is hoped that this effect can be exploited to permit direct bioanalysis for screening applications using minimal sample preparation, thereby lowering cost. The exact magnitude of this advantage has yet to be fully studied using the ESI-ChipTM and certainly warrants further investigation. In our initial work involving the bioanalysis of verapamil in human plasma, matrix-related ion suppression was estimated to be as high as 80% using PPT. Unfortunately, because a direct comparison to FIA at higher flow rates was not conducted, the true impact of nanoESI was not assessed. The relevant question to be asked is not whether nanoESI suffers from ion suppression, but can adequate sensitivity and robustness be obtained using PPT without additional sample preparation? Although additional sample clean-up can be implemented, it requires additional time and expense. From this perspective, the results that we obtained for metabolic stability, although limited, were compelling. Entering Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 351/356

Role and Potential of Infusion Nanoelectrospray Ionization

351

into the investigation, we fully expected that generic SPE would be needed similar to the FIA study reported by Zheng et al. [11]. As reported earlier in this chapter, reasonable data were obtained by nanoESI despite the high salt concentration present in the microsomal buffer used. This observation leads to a key question that has not yet been fully addressed about the viability of the ESI-ChipTM for drug discovery applications. Namely, how often is sample clean-up (SPE, LLE, etc.) required for successful bioanalysis? While an informed answer to this question awaits further testing, it is a critical issue since it governs two key determinants of successful discovery bioanalysis: cost and speed. An important fact about LC–MS/MS based ion suppression is that it is time dependent. It is widely known that ion suppression often varies considerably over the course of a chromatogram and in many cases these changes occur over the time frame of a chromatographic peak. This issue, often cited as a reason for poor IS tracking, ultimately leads to poor precision and accuracy. Regardless of the level of ion suppression observed with infusion nanoESI, it has the distinct advantage of remaining constant over the course of analysis. This factor is significant, since it may lead to improved IS tracking for infusion nanoESI relative to LC–MS/MS. In our opinion, this is another attribute that merits detailed investigation. In addition to the advantage of constant ion suppression, IS tracking might also benefit from the use of nanoESI since by default the IS is always co-ionized with the analyte. Recent reports in the literature, such as the work of Shi [42], confirm the widely held belief that superior bioanalytical performance results when an IS co-elutes with the analyte (for cases when a structural analog IS is used). Among other effects, a wider dynamic range was observed in the case when co-elution occurred. Nevertheless, because stable isotope-labeled internal standards are rarely available for discovery applications, the impact of ion suppression from components not present in the sample matrix is of major concern. Examples of this problem include the dosing vehicle, other analytes and drug metabolites. The degree to which analog internal standards can compensate for these effects in nanoESI remains to be determined. Needless to say, this is an important issue since the agents listed above (i.e., vehicle, analytes, metabolites) all have the potential to remain in the sample even after deliberate clean-up (e.g., SPE). It is important to note these situations can occur during LC–MS/MS, albeit they are less likely to do so. Another issue regarding the ESI-ChipTM that must be addressed is the potential loss in selectivity owing to the lack of on-line chromatography. In addition to the obvious inability to analyze isomers, another potential issue arises from what is typically referred to as ‘metabolite cross-talk.’ A common example of this effect occurs when drug conjugates, such as sulfates and glucuronides, undergo in-source collision-induced dissociation (CID) to generate alternate sources of precursor ions for the drug prior to mass selection by the triple quadrupole (see Chapter 1 for more on this topic), this problem is sometimes referred to as metabolite cross-talk. Because these Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 352/356

Using Mass Spectrometry for Drug Metabolism Studies

352

factors can also occur during LC–MS/MS, bioanalysts have devised strategies to address the issue of metabolite cross-talk. A recent paper by Jemal is recommended reading for those interested in this topic [43]. Again, while this issue does not solely pertain to infusion nanoESI, its potential is exacerbated by the lack of on-line chromatography. 12.5.2

Future modifications to existing technology

Although the potential of the Nanomate 100TM for bioanalysis has been demonstrated, the current design of this instrument is somewhat limited for bioanalytical applications. One practical matter is that the current autosampler cannot be temperature controlled and, more importantly, only has the capacity to hold one 96-well plate. A larger capacity autosampler is being designed to alleviate this problem. The current sampling rate of 40 s per sample [23] is another area that should be considered in future refinements to the system. In order to allow greater batch size for overnight runs, it will also be necessary to increase the array size of the ESI-ChipTM to avoid the practical matter of chip replacement during the run. Fortunately, this issue is currently being addressed with the introduction of a 20
20 array chip, which has the same dimensions as the current ESIChipTM. This technological advance will also have the added advantage of reducing the price per chip. Finally, it should be pointed out that early attempts at interfacing on-line chromatography to the chip have been reported. In one approach Tan and co-workers successfully bonded a polymeric porous monolithic phase inside a chip to allow on-line SPE desalting prior to infusion. Human urine spiked with imipramine was used as an initial test case of this technology [44]. Another approach under investigation involves the direct interfacing of C18 ZipTipsTM to the ESI-ChipTM to combine sample transfer and desalting using a single pipette tip. This second approach is interesting because it is consistent with the current interface used with the Nanomate 100TM. The usefulness of this technology relative to infusion nanoESI for pharmaceutical bioanalysis remains to be tested.

12.6

Conclusions

The examples presented in this chapter provide recent illustrations involving a novel application of an emerging technology. Admittedly, further investigation will be needed to understand the true potential of infusion nanoESI as a bioanalytical tool, but the feasibility of this technology for quantitative applications has been adequately demonstrated. Greater implementation of this technology awaits technological refinement as well as further investigation into core issues, such as ion suppression, internal standard tracking, robustness and cost. In addition, an important step, which has not yet been undertaken, is an expanded cross-validation of this technology with results obtained by Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:36pm Page: 353/356

Role and Potential of Infusion Nanoelectrospray Ionization

353

LC-MS/MS. While the results presented in this chapter involving Caco-2 and metabolic stability look promising, a much wider investigation is needed, including the use of infusion nanoESI to support GLP–toxicology studies. With appropriate sample preparation and the use of a stable isotope labeled internal standard, this latter application would appear feasible and would benefit greatly from two advantages of this technology: reduced expenditure on method development and the avoidance of system carryover. 12.6.1

In search of parallelization

In closing, a final thought is offered on the importance of this new technology, which represents the first viable interface between ESI and microchip technology. It is our hope, that advances such as this will ultimately help address a fundamental limitation of LC–MS as a screening technology, namely that it is a serial technique. Given the fanfare surrounding LC–MS/MS, it may appear odd to some to know that LC–MS/MS is a relatively low-throughput technology compared to most formats for HTS that employ parallel detection. This limitation explains the extreme emphasis placed in recent years on reducing the chromatographic duty cycle associated with LC–MS/MS. It should be mentioned that some attempts have been made at achieving parallel sample introduction into the mass spectrometer. A notable case is the commercial introduction of an indexed multiple-sprayer electrospray ionization (ESI) source referred to as MUXTM [45], which allows the effluent streams from up to eight independent LC columns to be time shared by a single mass spectrometer. Despite reported applications of this technology for bioanalysis [45, 46], it should be understood that this approach does not represent true parallel MS since the only single detector is employed. The obvious path to parallel MS requires the introduction of parallel schemes for MS detection, such as the current work by Patterson et al. involving cylindrical ion trap arrays [47]. Unfortunately, this quest for is made difficult by the relative complexity, size and cost of mass spectrometers relative to other analytical detectors. Because of these reasons, it is safe to conclude that any successful path to parallel MS will involve miniaturization of both the mass analyzer as well as the means of sample introduction. For this reason alone, we are encouraged by the recent commercial introduction of the first technology interfacing ESI to microchip technology and look forward to future developments.

References 1. Hofgartner, G. and Bourgogne, E., Quantitative high-throughput analysis of drugs in biological matrices by mass spectrometry, Mass Spectrom. Rev., 22(3), 195, 2003. 2. Ackermann, B.L., Berna, M.J., and Murphy, A.T., Recent advances in use of LC–MS/MS for quantitative high-throughput bioanalytical support of drug discovery, Curr. Top. Med. Chem., 2, 56, 2002.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:37pm Page: 354/356

354

Using Mass Spectrometry for Drug Metabolism Studies

3. Plumb, R.S. et al. Quantitative analysis of pharmaceuticals in biological fluids using high-performance liquid chromatography coupled to mass spectrometry: a review, Xenobiotica, 31, 599, 2001. 4. Jemal, M., High-throughput quantitative bioanalysis by LC–MS/MS, Biomed. Chromatogr., 14, 422, 2000. 5. Janiszewski, J.S. et al. A high-capacity LC–MS system for the bioanalysis of samples generated from plate-based metabolic screening, Anal. Chem., 73, 1495, 2001. 6. Kerns, E.H. and Di, L., Pharmaceutical profiling in drug discovery, Drug Discov. Today, 8, 316, 2003. 7. Korfmacher, W.A. et al. Cassette-accelerated rapid rat screen: a systematic procedure for the dosing and liquid chromatography/atmospheric pressure ionization tandem mass spectrometric analysis of new chemical entities as part of new drug discovery, Rapid Commun. Mass Spectrom., 15, 335, 2001. 8. Olah, T.V., McLoughlin, D.A., and Gilbert, J.D., The simultaneous determination of mixtures of drug candidates by liquid chromatography/atmospheric pressure chemical ionization mass spectrometry as an in vivo drug screening procedure, Rapid Commun. Mass Spectrom., 11, 17, 1997. 9. Chen, S. and Carvey, R., Validation of liquid–liquid extraction followed by flowinjection negative ion electrospray mass spectrometry assay to topiramate in human plasma, Rapid Commun. Mass Spectrom., 15, 159, 2001. 10. Hopfgartner, G., Bean, K., Henion, J. and Henry, R., Ion spray mass spectrometric detection for liquid chromatography: a concentration—or a mass-flow-sensitive device? J. Chromatogr., 647, 51, 1993. 11. Zheng, J.J., Lynch, E.D., and Unger, S.E., Comparison of SPE and fast LC to eliminate mass spectrometric matrix effects from microsomal incubation products, J. Pharm. Biomed. Anal., 28, 279, 2002. 12. Kadkhodayan, M. et al. High-throughput 36 second LC–MS/MS analysis of plasma samples using the new SPExpress system, In Proceedings of the 51st Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, June 8–12, 2003. 13. Olech, R.M. et al. A novel SPE system for high-throughput quantification by ESI– LC–MS/MS utilizing 96 discrete zones in a disposable card format, In Proceedings of the 49th Conference on Mass Spectrometry and Allied Topics, Chicago, IL, May 27–31, 2001. 14. Duggan, J.X., Gutierrez, V.S., Worboys, P., and Ellefson, P.J., The evaluation of a 96-well SPE Card extraction technique for pharmaceutical bioanalysis, In Proceedings of the 51st Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, June 8–12, 2003. 15. Cole, M.J. et al. Characterization of MALDI on a triple quadrupole mass spectrometer for analysis and quantitation of small molecules, In Proceedings of the 51st Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, June 8–12, 2003. 16. Thomas, J.J. et al. Desorption/ionization on silicon (DIOS): a diverse mass spectrometry platform for protein characterization a diverse mass spectrometry platform for protein characterization, Proc. Natl. Acad. Sci. USA, 98, 4932, 2001. 17. Schultz, G.A., Corso, T.N., Prosser, S.J., and Zhang, S., A fully integrated monolithic microchip electrospray device for mass spectrometry, Anal. Chem., 72, 4058, 2000.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:37pm Page: 355/356

Role and Potential of Infusion Nanoelectrospray Ionization

355

18. Van Pelt, C., Zhang, S., and Henion, J., Characterization of a fully automated nanoelectrospray system with mass spectrometric detection for proteomic analyses, J. Biomolecular Techniques, 6, 3, 2002. 19. Zhang, S., Van Pelt, C.K., and Wilson, D.B., Quantitative determination of noncovalent binding interactions using automated nanoelectrospray mass spectrometry, Anal. Chem., 75, 3010, 2003. 20. Dethy, J.M. et al. Demonstration of direct bioanalysis of drugs in plasma using nanoESI infusion from a silicon chip coupled with tandem mass spectrometry, Anal. Chem., 75, 805, 2003. 21. Van Pelt, C.K. et al. Chip-based automated nanoelectrospray mass spectrometry, Am. Lab., 35, 14, 2003. 22. Van Pelt, C.K. et al. A fully automated nanoESI tandem mass spectrometric method for analysis of Caco-2 samples, Rapid Commun. Mass Spectrom., 17, 1573, 2003. 23. Kapron, J.T., Pace, E., Van Pelt, C.K., and Henion, J., Quantitation of midazolam in human plasma by automated chip-based infusion nanoESI tandem mass spectrometry, Rapid Commun. Mass Spectrom., 17, 2019, 2003. 24. Leuthold, L.A. et al. The use of alternative SRM and full scan MS/MS with chipbased infusion MS for high throughput analysis in biological fluids with improved assay selectivity, In Proceedings of the 51st Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, June 8–12, 2003. 25. Rule, G., Corso, T., Prosser, S., and Schultz, G., Small molecule determination by nanoelectrospray mass spectrometry from a silicon chip, In Proceedings of the 49th Conference on Mass Spectrometry and Allied Topics, Chicago, IL, May 27–31, 2001. 26. Leaver, N. et al. A novel method for the quantitative analysis of immunosuppressive drugs in whole blood using chromatography-free chip-based infusion ion trap mass spectrometry, In Proceedings of the 51st Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, June 8–12, 2003. 27. Dethy, J.M. et al. Investigation of infusion nano-ESI using a silicon chip for high throughput determination of hepatic metabolic stability, In Proceedings of the 51st Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, June 8–12, 2003. 28. Lastelle, M. et al. Utilization of an automated blood sampling device for rat pharmacokinetic studies with direct bioanalysis by nano-ESI-MS/MS from a silicon chip, In Proceedings of the 51st Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, June 8–12, 2003. 29. Shah, V.P. et al. Bioanalytical method validation—a revisit with a decade of progress. Pharm. Res., 17, 1551, 2000. 30. Hidalgo, I.J., Raub, T.J., and Borchardt, R.T., Characterization of the human colon carcinoma cell line (Caco-2) as a model system for intestinal epithelial permeability, Gastroenterology, 96, 736, 1989. 31. Whalen, K.M., Rogers, K.J., Cole, M.J., and Janiszewski, J.S., AutoScan: an automated workstation for rapid determination of mass and tandem mass spectrometry conditions for quantitative bioanalytical mass spectrometry, Rapid Commun. Mass Spectrom., 14, 2074, 2000. 32. Ackermann, B.L., Ruterbories, K.J., Hanssen, B.R., and Lindstrom, T.D., increasing the throughput of microsomal stability screening using fast gradient elution LC-MS, In Proceedings of the 46th ASMS Conference on Mass Spectrometry and Allied Topics, Orlando, FL, May 31–June 5, 1998.

Copyright © 2005 CRC Press, LLC

File: {Books}4354-Korfmacher/Revises-II/4354-Chapter-12.3d Creator: iruchan/cipl-un1-3b2-1.unit1.cepha.net Date/Time: 25.10.2004/7:37pm Page: 356/356

356

Using Mass Spectrometry for Drug Metabolism Studies

33. Carrillo, J.A. et al. Analysis of midazolam and metabolites in plasma by highperformance liquid chromatography: probe of CYP3A. Ther. Drug Monit., 20, 319, 1998. 34. Shiran, M.R. et al. Determination of midazolam and 10 -hydroxymidazolam by liquid chromatography–mass spectrometry in plasma of patients undergoing methadone maintenance treatment. J. Chromatogr. B, Analyt. Technol. Biomed. Life Sci., 783, 303, 2003. 35. Buhrman, D.L., Price, P.I., and Rudewicz, P.J., Quantitation of SR 27417 in human plasma using electrospray liquid chromatography–tandem mass spectrometry: a study of ion suppression, J. Am. Soc. Mass Spectrom., 7, 1099, 1996. 36. Matuszewski, B.K., Constanzer, M.L., and Chavez-Eng, C.M., Matrix effect in quantitative LC–MS/MS analyses of biological fluids: a method for determination of finasteride in human plasma at picogram per milliliter concentrations, Anal. Chem., 70, 882, 1998. 37. King, R. et al. Mechanistic investigation of ionization suppression in electrospray ionization, J. Am. Soc. Mass Spectrom., 11, 942, 2000. 38. Mei, H. et al. Investigation of matrix effects in bioanalytical high-performance liquid chromatography/tandem mass spectrometric assays: application to drug discovery, Rapid Commun. Mass Spectrom., 17, 97, 2003. 39. Tong, X.S. et al. Effect of signal interference from dosing excipients on pharmacokinetic screening of drug candidates by liquid chromatography/mass spectrometry, Anal. Chem., 74, 6305, 2002. 40. Shou, W.Z. and Naidong, W., Post-column infusion study of the ‘dosing vehicle effect’ in the liquid chromatography/tandem mass spectrometric analysis of discovery pharmacokinetic samples, Rapid Commun. Mass Spectrom., 17, 589, 2003. 41. Schmidt, A., Karas, M., and Dulcks, T., Effect of different solution flow rates on analyte ion signals in nano-ESI MS, or: when does ESI turn into nano-ESI?, J. Am. Soc. Mass Spectrom., 14, 492, 2003. 42. Shi, G., Application of co-eluting structural analog internal standards for expanded linear dynamic range in liquid chromatography/electrospray mass spectrometry, Rapid Commun. Mass Spectrom., 17, 202, 2003. 43. Jemal, M., Ouyang, Z., and Powell, M.L., A strategy for a post-method-validation use of incurred biological samples for establishing the acceptability of a liquid chromatography/tandem mass-spectrometric method for quantitation of drugs in biological samples. Rapid Commun. Mass Spectrom., 16, 1538, 2002. 44. Tan, A., Benetton, S., and Henion, J.D., Chip-based solid-phase extraction pretreatment for direct electrospray mass spectrometry analysis using an array of monolithic columns in a polymeric substrate, In Proceedings of the 51st Conference on Mass Spectrometry and Allied Topics, Montreal, Canada, June 8–12, 2003. 45. Yang, L. et al. Evaluation of a four-channel multiplexed electrospray triple quadrupole mass spectrometer for the simultaneous validation of LC-MS/MS methods in four different preclinical matrices, Anal. Chem., 73, 1740, 2001. 46. Deng, Y., Zeng, H., Unger, S.E., and Wu, J.T., Multiple-sprayer tandem mass spectrometry with parallel high flow extraction and parallel separation for highthroughput quantitation in biological fluids. Rapid Commun. Mass Spectrom., 15, 1634, 2001. 47. Patterson, G.E. et al. Miniature cylindrical ion trap mass spectrometer, Anal. Chem., 74, 6145, 2002.

Copyright © 2005 CRC Press, LLC