Metabolite Safety in Drug Development E-Book

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 679

Veröffentlichungsjahr: 2016

Beschreibung

A reference on drug metabolism and metabolite safety in the development phase, this book reviews the analytical techniques and experimental designs critical for metabolite studies. It features case studies of lessons learned and real world examples, along with regulatory perspectives from the US FDA and EMA.

•    Reviews the analytical techniques and experimental designs critical for metabolite studies
•    Covers methods including chirality, species differences, mass spectrometry, radiolabels, and in vitro / in vivo correlation
•    Discusses target pharmacology, in vitro systems aligned to toxicity tests, and drug-drug interactions
•    Includes perspectives from authors with firsthand involvement in industry and the study of drug metabolites, including viewpoints that have influenced regulatory guidelines

Leseprobe

Table of Contents

COVER

TITLE PAGE

PREFACE

LIST OF CONTRIBUTORS

1 INTRODUCTION: HISTORY OF METABOLITE SAFETY IN DRUG DEVELOPMENT

1.1 PEOPLE, EVENTS, AND REACTION

1.2 THE RISE OF INDUSTRIAL DRUG METABOLISM

1.3 THE APPEARANCE OF MIST

1.4 THE JOURNEY TRIGGERED BY THALIDOMIDE: WOULD PRESENT SCIENCE HAVE MADE A DIFFERENCE?

1.5 KEY EVENTS FROM THALIDOMIDE TO MIST

1.6 THE PURPOSE OF THIS BOOK

REFERENCES

2 “MIST” AND OTHER METABOLITE GUIDELINES IN THE CONTEXT OF INDUSTRIAL DRUG METABOLISM

2.1 A HISTORICAL PERSPECTIVE

2.2 THE EMERGENCE OF THE REGULATORY GUIDANCE DOCUMENTS

2.3 IMPACT OF THE GUIDELINES

2.4 FUTURE DIRECTIONS

REFERENCES

3 METABOLITE TECHNOLOGY: QUALITATIVE AND QUANTITATIVE

3.1 INTRODUCTION

3.2 CLINICAL SAMPLES

3.3 PRECLINICAL SAMPLES

3.4 RADIOLABELED TEST COMPOUNDS

3.5 MASS SPECTROMETRY

3.6 NMR SPECTROSCOPY

3.7 ACCELERATOR MASS SPECTROMETRY

REFERENCES

FURTHER READING

4

IN VITRO

METHODS FOR EVALUATION OF DRUG METABOLISM: IDENTIFICATION OF ACTIVE AND INACTIVE METABOLITES AND THE ENZYMES THAT GENERATE THEM

4.1 INTRODUCTION

4.2

IN VITRO

METHODS FOR METABOLITE PROFILING AND IDENTIFICATION

4.3 APPLICATION OF

IN VITRO

METHODS FOR METABOLITE PROFILING IN DRUG DISCOVERY AND DEVELOPMENT

4.4 HOW WELL DO

IN VITRO

METABOLITE PROFILES REPRESENT

IN VIVO

METABOLITE PROFILES?

4.5 PHARMACOLOGICALLY ACTIVE METABOLITES AND THEIR IDENTIFICATION

4.6 CONCLUSION

REFERENCES

5 INTEGRATED REACTIVE METABOLITE STRATEGIES

5.1 INTRODUCTION

5.2 ROLE OF RMs IN TOXICITY

5.3 STRATEGIES FOR PREDICTING, ASSESSING, AND DERISKING RM-MEDIATED TOXICITY

REFERENCES

6 UNDERSTANDING DRUG METABOLISM IN HUMANS:

IN VIVO

6.1 INTRODUCTION

6.2 PRECLINICAL ANIMAL STUDIES

6.3 EARLY HUMAN

IN VIVO

METABOLISM STUDIES

6.4 THE “WHAT IFS…?”

6.5 SOURCES OF VARIABILITY IN

IN VIVO

BIOTRANSFORMATION STUDIES: SPECIES, STRAIN, AGE, AND SEX DIFFERENCES

6.6 EXTRAHEPATIC DRUG METABOLISM (ANIMALS AND MAN)

6.7 NONHUMAN METABOLISM IN HUMANS

6.8 NONHUMAN MODELS OF HUMAN

IN VIVO

METABOLISM

6.9 ALTERNATIVES TO RADIOLABELS

6.10 CONCLUSIONS

REFERENCES

7 TOPICAL ADMINISTRATION AND SAFETY TESTING OF METABOLITES

7.1 INTRODUCTION

7.2 SKIN STRUCTURE AND FUNCTION OF THE EPIDERMAL LAYER

7.3 SKIN MODELS

7.4 METABOLIC CAPACITY OF HUMAN SKIN

7.5 SPECIES DIFFERENCES IN METABOLIC CAPACITY OF THE SKIN

7.6 METABOLIC CAPACITY OF DISEASED SKIN

7.7 SOFT DRUG APPROACH

7.8 EXPOSURE TO METABOLITES AND RISK OF ADVERSE EVENTS

REFERENCES

8

IN SILICO

MODELING OF METABOLITE KINETICS

8.1 INTRODUCTION

8.2 Simcyp APPROACH TO MODELING METABOLITE PBPK

8.3 MODEL VERIFICATIONS

8.4 DISCUSSION

8.5 CONCLUDING REMARKS

REFERENCES

9 INTRODUCTION TO CASE STUDIES

REFERENCES

10 A MASS BALANCE AND METABOLITE PROFILING STUDY OF SONIDEGIB IN HEALTHY MALE SUBJECTS USING MICROTRACE APPROACH

10.1 INTRODUCTION TO THE STUDY

10.2 RADIOACTIVE DOSE LIMITATIONS

10.3 RESULTS

10.4 METABOLITE PROFILING AND IDENTIFICATION

ACKNOWLEDGMENTS

REFERENCES

11 DEALING WITH REALITY: WHEN IS IT NECESSARY TO QUALIFY AND QUANTIFY METABOLITES? SOME CASE STUDIES

11.1 INTRODUCTION

11.2 CASE STUDY 1

11.3 CASE STUDY 2

11.4 CASE STUDY 3

REFERENCES

12 THE VALUE OF METABOLITE IDENTIFICATION AND QUANTIFICATION IN CLINICAL STUDIES. SOME CASE STUDIES ENABLING EARLY ASSESSMENT OF SAFETY IN HUMANS: GLAXOSMITHKLINE

12.1 GW644784: SPECIES-SPECIFIC METABOLITES

12.2 DANIRIXIN: ASSESSMENT OF VICTIM DRUG INTERACTION RISK USING BILE SAMPLING

12.3 SITAMAQUINE: UNIQUE, ACTIVE, AND POSSIBLE GENOTOXIC METABOLITES AND HUMAN RADIOLABEL STUDY NOT FEASIBLE

12.4 SB-773812: CONCERNS OVER LONG HALF-LIFE METABOLITE AND EARLY EMPLOYMENT OF ACCELERATOR MASS SPECTROMETRY

12.5 GW766994: CONSIDERATION OF STEADY-STATE KINETICS AND MULTIPLE ANALYTICAL METHODOLOGIES FOR AN ACCURATE ASSESSMENT OF HUMAN METABOLISM

REFERENCES

13 THE IMPORTANCE OF DOSE-AND TIME-DEPENDENT PHARMACOKINETICS DURING EARLY METABOLITE SAFETY ASSESSMENT IN HUMANS

REFERENCES

14 MIST AND THE FUTURE

14.1 INTRODUCTION

14.2 MIST AND PHARMACOLOGY

14.3 REACTIVE METABOLITES, PHARMACOLOGY, AND MIST

14.4 IMPLICATIONS OF DRUG BIOACTIVATION AND COVALENT BINDING FOR MIST

14.5 DRUG BIOACTIVATION AND DRUG HEPATOTOXICITY

14.6 DRUG-CONJUGATE FORMATION AND DRUG HYPERSENSITIVITY

14.7 DRUG BIOACTIVATION, CONJUGATE FORMATION, AND DRUG HYPERSENSITIVITY

14.8 TOWARD A MIST STRATEGY FOR REACTIVE METABOLITES

REFERENCES

INDEX

END USER LICENSE AGREEMENT

List of Tables

Chapter 01

TABLE 1.1 Pharmacokinetic Parameters Calculated from the Data Presented by Chung et al. (2004)

TABLE 1.2 The Metabolism of Halothane and Its Analogs to a Trifluoroacetyl Chloride Metabolite and the Relative Association of Each Anesthetic with Hepatic Failure

Chapter 03

TABLE 3.1 Comparison of Detection Limits Associated with Commonly Used Radiodetectors

Chapter 04

TABLE 4.1 Common Drug-Metabolizing Enzymes and Their Subcellular Location and Cofactors/Cosubstrates Required for Activity

TABLE 4.2 Common Organic Substituents in Drug Molecules, the Drug Metabolism Reactions They Can Undergo, and the Enzymes That Catalyze These Reactions

TABLE 4.3 Examples of Pharmacologically Active Metabolites in Humans

Chapter 05

TABLE 5.1 Examples of Safe Drugs that are Chemically and Pharmacologically Related to Toxic Drugs

TABLE 5.2 Structural Alerts, Types of Reactive Species Formed, and Enzyme System

TABLE 5.3 Downstream Metabolites that Indicate the Generation of a Reactive Intermediate

Chapter 07

TABLE 7.1 Overview of Cell Lines for Studying Xenobiotic-Metabolizing Enzymes

TABLE 7.2 Overview of Commercially Available and Open-Source Reconstructed Human Skin Models

Chapter 11

TABLE 11.1 Percentage of Circulating Radioactivity of Zoniporide and Its Metabolites in Plasma of Healthy Male Volunteers and Toxicology Species after Intravenous Administration of [

14

C]Zoniporide (Dalvie et al. 2010)

TABLE 11.2 Estimation of Exposures of Zoniporide and Metabolites M1 and M3 from Percentages of Circulating Radioactivity in Rat and Human Plasma (Dalvie et al. 2010)

TABLE 11.3 Estimation of Total Body Burden of M1 from Excretion Data in Humans and Rats (Dalvie et al. 2010)

TABLE 11.4 Relative Exposure of M4 in Rat and Dog (Sawant Basak et al. 2014)

Chapter 12

TABLE 12.1 Metabolites of GW644784 in Human Plasma Quantified by NMR and the Exposure Multiples Compared with Rat, Dog, Monkey, and Mouse

TABLE 12.2 Summary of the Metabolites of Danirixin Identified in Human Duodenal Bile at 7 h Postdose as Quantified by

19

F NMR

TABLE 12.3 Major Metabolites of Sitamaquine in Human Plasma and Urine as Detected and Quantified by NMR (2 mg/kg Dosed for 21 days)

TABLE 12.4 Relative Proportions of SB-773812 and Its Metabolites in Human Plasma Taken from Single-Dose Clinical Studies Using LC/MS with Biological Standards Compared to AMS [

14

C]

TABLE 12.5 GW766994 and Its Metabolites in Human Plasma Following Oral Administration for Up to 14 Days Quantified by NMR or LC/MS Methods

Chapter 13

TABLE 13.1 Major Metabolites of Compound X Identified after 7 Days of Dosing, with their UPLC/MS Characteristics and the Corresponding Biotransformation

TABLE 13.2 Metabolite Exposure after Single Dose (1.5 × D and 4.5 × D mg, AUC

0–24 h

(ng-eq.h/ml)—Sampling Times of 0.5, 1, 2, 8, and 24 h for 1.5 × D mg Dose and 0.5, 2, and 24 h for 4.5 × D mg Dose) and 7-Day Multiple Doses (1 × D, 2 × D, and 4.5 × D mg, AUC

0–12 h

(ng-eq.h/ml)—Sampling Times 0, 4, 8, and 12 h at all Doses) of cpd X as estimated by UPLC/UV/MS

TABLE 13.3 AUC

0–120 h

(ng.h/ml) of Parent and Met A and B after Single Dose of cpd X (2 × D mg) with or without Ketoconazole and AUC

0–12 h

(ng.h/ml) of Parent and Met A and B after Multiple Dose of cpd X (2 × D mg b.i.d.) (Calculated Using a Validated Bioanalytical LC/MS/MS Method)

Chapter 14

TABLE 14.1 Examples of Drugs Metabolized to More Pharmacologically Active Metabolites

TABLE 14.2 Changes in Physicochemical Properties Produced by Metabolism

TABLE 14.3 Drugs Withdrawn Postmarketing in the United States Since 1980 due to Toxicity in Which Reactive Metabolites Are Implicated

List of Illustrations

Chapter 01

FIGURE 1.1 Structure of thalidomide.

Chapter 02

FIGURE 2.1 Comparison of workflows for metabolite identification.

FIGURE 2.2 Decision tree from the draft FDA MIST guidance document.

FIGURE 2.3 Decision tree for circulating metabolites.

FIGURE 2.4 Decision tree for excreted metabolites.

FIGURE 2.5 Decision tree from the final FDA MIST guidance document.

FIGURE 2.6 Summary of four strategies typically used to underwrite metabolite safety and understand the impact of metabolism on clearance and efficacy.

Chapter 03

FIGURE 3.1 A plot of increasing publications using the search terms “NMR” or “nuclear magnetic resonance” and “mass spectrometry” and “drug metabolism” in all fields (*compiled using Scopus database, article search).

FIGURE 3.2 Q Exactive connected to fraction collector for simultaneous measurement of mass spectra and collection of radioactive fractions into multiwell plates.

FIGURE 3.3 A comparison of radiodetection methods for metabolite quantification: (a) online (β-RAM) detection, (b) fraction collection/LSC detection, (c) microplate detection, and (d) phosphor plate detection.

FIGURE 3.4 Comparative quantification using radioflow detection, fraction collection/liquid scintillation counting, microplate scintillation counting, and phosphor plate detection.

FIGURE 3.5 Mass defect filtering example 1: (a) accurate mass extracted ion chromatogram, positive ion mode (b) full non-filtered scan for peak at 39 minutes (c) scan using mass defect filter for peak at 39 minutes (d) expanded scale showing presence of chlorine isotope in molecule.

FIGURE 3.6 Mass defect filtering example 2: (a) accurate mass extracted ion chromatogram, negative ion mode (b) full non-filtered scan for peak at 42 minutes (c) scan using mass defect filter for peak at 42 minutes (d) expanded scale showing presence of carbon-14 isotope in molecule.

FIGURE 3.7

1

H NMR neat urine versus isolated urine metabolite.

FIGURE 3.8

1

H NMR metabolite isolated by preparative HPLC versus further purification by LC-NMR.

FIGURE 3.9

19

F NMR spectrum of fluorine-containing metabolites analyzed in neat urine.

Chapter 04

FIGURE 4.1 Target receptor occupancy versus ligand concentration.

Chapter 05

SCHEME 5.1 Mechanism of covalent adduction of acyl glucuronide metabolites to proteins.

SCHEME 5.2 Mechanism of covalent adduction to proteins of

S

-acyl-CoA thioester metabolites (ACS = acyl-CoA synthetase).

FIGURE 5.1 Role of RMs in toxicity.

FIGURE 5.2 Potential causes of toxicity resulting from glucuronidation or acyl-CoA conjugation.

SCHEME 5.3 CYP2C9-mediated metabolic bioactivation of tienilic acid.

SCHEME 5.4 Metabolism of duloxetine.

FIGURE 5.3 Structures of ibufenac and ibuprofen.

FIGURE 5.4 Formed metabolites after incubation in HLM in the presence of (a) NADPH, (b) UDPGA, and (c) CoA. CVB after incubation in HLM in the presence of (d) NADPH, (e) UDPGA, and (f) CoA.

FIGURE 5.5 Zone plots. (a) Aggregated

in vitro

panel score versus CVB burden. (b) Exposure-adjusted aggregated

in vitro

panel score versus CVB burden for the series of endothelin receptor antagonists.

Chapter 06

FIGURE 6.1 A whole-body autoradiography section of a rat administered a radiolabeled drug showing the distribution of the radiolabel in the major organs.

FIGURE 6.2 Data generated by radioanalysis and bioanalysis of samples from a human ADME study. Upper panel: excretion profile providing data on rates and routes of excretion and recovery in excreta and the total DRM. Lower panel: plasma concentration–time curves for parent drug, individual metabolites, and the total DRM giving elimination rates from the circulation.

FIGURE 6.3 Data generated by radioanalysis and bioanalysis of samples from a human ADME study. Upper panel: HPLC-based metabolite profiles (radiochromatograms) of urine, feces, and plasma providing a number of metabolites in each sample type and quantities of metabolites as percentage of dose. Lower panel: metabolite pathways following LC/MS/MS analysis and structural characterization provided by interpretation of parent ion fragmentation (Darnell et al. 2012).

FIGURE 6.4 Workflow to generate the full understanding of human metabolism as outlined in the text.

FIGURE 6.5 Example of metabolism in the gut. The ether (M7) and acyl (M2) glucuronides are excreted via the bile. Enzymatic activity in the gut cleaves the glucuronides to regenerate the parent drug, following which the sulfide is oxidized to the diastereomeric pair of sulfoxides (M1a and M1b). Metabolite profiling with radioflow detection (

14

C) and metabolite identification by LC/MS/MS (L. Weidolf, AstraZeneca R&D, Mölndal, Sweden).

FIGURE 6.6 Expanded region (10–40 min) of the HPLC-ICPMS profile (TIC) using selective Br detection of 0–12 h urine resulting from a sample obtained from a male rat dosed i.p. with 50 mg/kg of 4-bromoaniline.

Chapter 07

FIGURE 7.1 Structure of the skin.

FIGURE 7.2 Histology (×400 magnification) of normal human skin (NHS) and skin models (EpiSkin™, RHE™, and EpiSkin™ FTM). D, dermis; E, epidermis; S, support; and SC, stratum corneum.

FIGURE 7.3 Potential routes of xenobiotic metabolism in the skin and liver. The size of each arrow is proportional to the expression of xenobiotic enzymes that may contribute to catalyze each biotransformation indicated.

FIGURE 7.4 A boron-containing PDE4 inhibitor was used as a starting point of a soft drug approach for the discovery of a more potent carboxylic ester compound (2) which was rapidly hydrolyzed to the corresponding inactive acid (7).

FIGURE 7.5 Ester 2 and acid 7 plasma concentrations after oral dose of ester 2 in mice (CD-1,

n

 = 3) at 100 mg/kg single dosage (1% CMC).

FIGURE 7.6 Development of the soft drug, LEO 29102, was based on Piclamilast, a PDE4 inhibitor developed for asthma, but with a low solubility making it unsuitable as a dermatological product.

Chapter 08

FIGURE 8.1 The structures of minimal PBPK model (left) and full PBPK model (right). The minimal PBPK model describes the human body using four compartments (Rowland Yeo et al. 2010). The full PBPK model has more detailed description of each tissue/organ and can involve permeability-limited compartments for the gut, liver, kidney, lung, and brain (Jamei et al. 2013a).

FIGURE 8.2 Link between parent full PBPK (left) and metabolite full PBPK (right) models. The two PBPK models are linked via the formation (solid single arrows) and DDIs (dash double arrows). Note that there is no administration route (IV or PO dosing) in the metabolite full PBPK model.

FIGURE 8.3 Example of simulation results of gemfibrozil (left) and its metabolite gemfibrozil 1-

O

-β glucuronide (right). The solid line is the mean concentration–time profile of 100 virtual subjects generated by the Simcyp Simulator using the healthy volunteer population. The gray lines are 5th and 95th percentiles. Dots are mean clinical observations (Backman et al. 2009; Honkalammi et al. 2011a, b, 2012).

FIGURE 8.4 Simulation results of what-if case (a) where the metabolite formation rate is faster than its elimination rate and case (b) where the metabolite elimination rate is faster than its formation rate.

FIGURE 8.5 Simulation results of what-if case (c) when the metabolite x is assumed to be a strong inhibitor. Case (a): metabolite formation is faster than its elimination. Case (b): metabolite formation is slower than its elimination.

FIGURE 8.6 Simulation results of what-if case (d) when the metabolite x is assumed to be a strong inducer. Case (a): metabolite formation is faster than its elimination. Case (b): metabolite formation is slower than its elimination.

FIGURE 8.7 Simulation results of what-if case (e) where simulated subjects are all CYP2C19 EMs.

FIGURE 8.8 Simulation results of what-if case (f) where simulated subjects are all CYP2C19 PMs.

FIGURE 8.9 DDIs within Simcyp Simulator. PK profiles of eight moieties including four metabolites can be modeled and simulated simultaneously in the simulator. The DDIs include autoinhibition, competitive inhibition, mechanism-based inhibition, induction, and suppression.

Chapter 10

FIGURE 10.1 Cumulative fecal excretion of radioactivity after a single oral dose of 800 mg [

14

C]sonidegib in healthy volunteers.

FIGURE 10.2 Cumulative urinary excretion of radioactivity after a single oral dose of 800 mg [

14

C]sonidegib in healthy volunteers.

FIGURE 10.3 Total cumulative excretion of radioactivity in urine and feces after a single oral dose of 800 mg [

14

C]sonidegib in healthy volunteers.

FIGURE 10.4 MS/MS product ion spectrum of protonated metabolite M16 (LNC119); [M + H]

+

formed by electrospray ionization, fragments generated by collisional activation with argon using a collision offset of 50 V.

FIGURE 10.5 MS/MS product ion spectrum of deprotonated metabolite M47e (CMN964); [M − H]

−

formed by electrospray ionization, fragments generated by collisional activation with argon using a collision offset of 27 V.

FIGURE 10.6 MS/MS product ion spectrum of deprotonated metabolite M48 (LGE899); [M − H]

−

formed by electrospray ionization, fragments generated by collisional activation with argon using a collision offset of 27 V.

FIGURE 10.7 MS/MS product ion spectrum of protonated sonidegib; [M + H]

+

formed by electrospray ionization, fragments generated by collisional activation with argon using a collision offset of 45 V.

FIGURE 10.8 Metabolite profiles (radiochromatograms) in plasma after a single oral dose of 800 mg [

14

C]sonidegib. (a) Plasma 4 h, pool across all six subjects, (b) plasma 16 h, pool across all six subjects;

y

-axis zoomed threefold, and (c) plasma 504 h, pool across all six subjects.

FIGURE 10.9 Concentration–time profiles of total radiolabeled components (radioactivity), sonidegib, and LGE899 in plasma after a single oral dose of 800 mg [

14

C]sonidegib in healthy volunteers; arithmetic means.

FIGURE 10.10 Metabolite profiles (radiochromatograms) in urine after a single oral dose of 800 mg [

14

C]sonidegib.

FIGURE 10.11 Metabolite profiles (radiochromatograms) in feces after a single oral dose of 800 mg [

14

C]sonidegib.

FIGURE 10.12 Overview of identified metabolic pathways.

Chapter 11

FIGURE 11.1 Circulating metabolites of zoniporide observed in man following intravenous infusion of 80 mg of [

14

C]zoniporide for 1 h (Dalvie et al. 2010).

FIGURE 11.2 Circulating metabolites of lersivirine in man (Vourvahis et al. 2010).

FIGURE 11.3 Metabolic profile of TBPT following its incubation with hepatocytes and in human plasma following its oral administration at a 40 mg dose (Sawant Basak et al. 2014).

Chapter 13

FIGURE 13.1 Representative UPLC/UV chromatogram of plasma from healthy volunteers (pool of six subjects) administered compound X orally at 2 × D mg b.i.d. (D = dose/black, predose sample; light grey, 4 h sample, Day 7). Metabolite letter codes are indicated (UD = unchanged drug).

FIGURE 13.2 Metabolite exposure after (a) single dose (1.5 × D and 4.5 × D mg, AUC

0–24 h

(ng-eq.h/ml)—sampling times of 0.5, 1, 2, 8, and 24 h for 1.5 × D mg dose and 0.5, 2, and 24 h for 4.5 × D mg dose) and (b) 7-day multiple doses (1 × D, 2 × D, and 4.5 × D mg, AUC

0–12 h

(ng-eq.h/ml)—sampling times 0, 4, 8, and 12 h at all doses) of cpd X as estimated by UPLC/UV/MS. *Exposure of Met B after single dose is significantly underestimated as

T

max

was not reached at 24 h. **Met E and F: data only available after repeated dosing; no interpretable exposure data available after single dose due to insufficient sampling times.

FIGURE 13.3 Metabolite exposure after (a) single dose (doses of 1.5 × D and 4.5 × D mg, AUC

0–24 h

(ng-eq.h/ml)) and (b) 7-day multiple doses (doses of 1 × D, 2 × D, and 4.5 × D mg, AUC

0–12 h

(ng-eq.h/ml)) of cpd X expressed as percentage of total drug-related material (TDRM, sum of AUC

0–12 h

(ng-eq.h/ml) of each individual metabolite) as estimated by UPLC/UV/MS. The horizontal line represents 7.5% of TDRM (arbitrary threshold to qualify MIST relevant metabolites based on the analytical uncertainty linked to the methodology used). *Exposure of Met B after single dose is significantly underestimated as

T

max

was not reached at 24 h. **Met E and F: data only available after repeated dosing; no interpretable exposure data available after single dose due to insufficient sampling times.

FIGURE 13.4 Exposure of parent (cpd X), Met A, and Met B after (a) single dose (2 × D mg) of cpd X (Day 1 to Day 5) and (b) after single dose (2 × D mg) of cpd X (Day 10 to Day 15) following administration of ketoconazole (200 mg b.i.d.—Day 6 to Day 11).

Chapter 14

FIGURE 14.1 Structure of BMS-204352.

FIGURE 14.2 Relationship between drug disposition, protein modification, protein conjugation, and drug toxicity.

FIGURE 14.3 Relationship between drug disposition and drug-induced liver injury caused by acetaminophen.

FIGURE 14.4 Current hypotheses of drug hypersensitivity.

Guide

Cover

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METABOLITE SAFETY IN DRUG DEVELOPMENT

Edited by

SUZANNE L. IVERSONDENNIS A. SMITH

Copyright © 2016 by John Wiley & Sons, Inc. All rights reserved

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Library of Congress Cataloging-in-Publication Data

Names: Iverson, Suzanne L., 1971– author. | Smith, Dennis A., author.Title: Metabolite safety in drug development / Suzanne L. Iverson, Dennis A. Smith.Description: Hoboken, NJ : John Wiley & Sons Inc., [2016] | Includes bibliographical references and index.Identifiers: LCCN 2016009167| ISBN 9781118949658 (hardback) | ISBN 9781118949665 (adobe pdf) | ISBN 9781118949672 (epub)Subjects: LCSH: Drugs–Metabolism. | Drugs–Safety measures. | Pharmacology. | BISAC: SCIENCE / Chemistry / Analytic. | MEDICAL / Pharmacology.Classification: LCC RM301.55 .I94 2016 | DDC 615.1–dc23LC record available at https://lccn.loc.gov/2016009167

PREFACE

This book traces the history of the study of drug metabolites and their implication in the safety assessment of drug candidates produced by the pharmaceutical industry and other institutions. It traces the history but importantly brings the reader to present-day thinking and approaches that are easily translated to other industries where the biological fate of human-made molecules is studied, for example, agrochemicals, chemicals in the environment, and cosmetics. The subject of the safety assessment of metabolites is often collectively grouped under the acronym MIST (metabolites in safety testing), but the topic is actually far wider than that covered by the ICH and FDA1 regulatory guidelines that MIST brings to mind. While the published regulatory guidelines covering drug metabolites provide scientists with a welcome framework, the area cannot be tightly legislated, or confined, due to the complexity of risk assessment. Addressing the issues of MIST requires a knowledge of pharmacology, toxicology, physicochemistry, chemistry, drug metabolism, and pharmacokinetics. Identifying metabolites, particularly in human, requires highly specialized technology and analytical skills. The book introduces all these areas and addresses the questions of diversity and flexibility with a series of case examples that exemplify the science in actual practice. Thus, the reader gains the knowledge and philosophy to address this highly important diverse area of drug discovery and development with confidence.

Note

1

FDA—United States of America Food and Drug Administration; ICH—International Conference of Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use.

LIST OF CONTRIBUTORS

Claire Beaumont, Platform Technology & Science, David Jack Centre for R&D, GlaxoSmithKline, Hertfordshire, UK

Jackie Bloomer, Platform Technology & Science, David Jack Centre for R&D, GlaxoSmithKline, Hertfordshire, UK

Marc Bockx, Pharmacokinetics, Dynamics & Metabolism, Janssen R&D, Beerse, Belgium

Hilde Bohets, Preclinical Development Team, Janssen R&D, Beerse, Belgium

Howard Burt, Simcyp Limited (a Certara Company), Blades Enterprise Centre, Sheffield, UK

Deepak K. Dalvie, PDM-Oncology Research Unit, Pfizer Inc., La Jolla, CA, USA

Gordon J. Dear, Platform Technology & Science, David Jack Centre for R&D, GlaxoSmithKline, Hertfordshire, UK

Lu Gaohua, Simcyp Limited (a Certara Company), Blades Enterprise Centre, Sheffield, UK

Helen Humphries, Simcyp Limited (a Certara Company), Blades Enterprise Centre, Sheffield, UK

Suzanne L. Iverson, Honorary Chairman, Drug Metabolism Discussion Group (DMDG), Leicester, UK; and Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden

Masoud Jamei, Simcyp Limited (a Certara Company), Blades Enterprise Centre, Sheffield, UK

Amit S. Kalgutkar, PDM-Cardiovascular and Metabolic Disease Research Unit, Pfizer Inc., Cambridge, MA, USA

J. Gerry Kenna, Drug Safety Consultant, Macclesfield, Cheshire, UK

Laurent Leclercq, Pharmacokinetics, Dynamics & Metabolism, Janssen R&D, Beerse, Belgium

Frederic Lozac’h, Novartis Pharma AG; and Department of Drug Metabolism and Pharmacokinetics, Novartis Institutes for BioMedical Research, Basel, Switzerland

Andrew McEwen, Reviresco Solutions Ltd., Peterborough, UK

Angus N. R. Nedderman, Metabolism and Discovery Services, Unilabs York Bioanalytical Solutions, Kent, UK

Stephanie North, Platform Technology & Science, David Jack Centre for R&D, GlaxoSmithKline, Hertfordshire, UK

R. Scott Obach, PDM-Biotransformation, Pfizer Inc., Groton, CT, USA

B. Kevin Park, Institute of Translational Medicine, University of Liverpool, Liverpool, UK

Amin Rostami-Hodjegan, Simcyp Limited (a Certara Company), Blades Enterprise Centre, Sheffield; and Manchester Pharmacy School, University of Manchester, Manchester, UK

Ellen Scheers, Pharmacokinetics, Dynamics & Metabolism, Janssen R&D, Beerse, Belgium

Vikash Sinah, Clinical Pharmacology, Janssen R&D, Spring House, NJ, USA

Dennis A. Smith, The Maltings, Kent, UK

Hans Stieltjes, Pharmacokinetics, Dynamics & Metabolism, Janssen R&D, Beerse, Belgium

Vibeke Hougaard Sunesen, Preclinical Development, LEO Pharma A/S, Ballerup, Denmark

Piet Swart, Novartis Pharma AG; and Department of Drug Metabolism and Pharmacokinetics, Novartis Institutes for BioMedical Research, Basel, Switzerland

Richard A. Thompson, Respiratory, Inflammation & Autoimmune Diseases, Innovative Medicines and Early Development Biotech Unit, AstraZeneca, Mölndal, Sweden

Lars Weidolf, Cardiovascular and Metabolic Diseases, Innovative Medicines and Early Development Biotech Unit, AstraZeneca, Mölndal, Sweden

Ian D. Wilson, Department of Surgery and Cancer, Imperial College, London, UK

Graeme Young, Platform Technology & Science, David Jack Centre for R&D, GlaxoSmithKline, Hertfordshire, UK

Markus Zollinger, Novartis Pharma AG; and Department of Drug Metabolism and Pharmacokinetics, Novartis Institutes for BioMedical Research, Basel, Switzerland

1INTRODUCTION: HISTORY OF METABOLITE SAFETY IN DRUG DEVELOPMENT

Dennis A. Smith1 and Suzanne L. Iverson2,3

1The Maltings, Kent, UK

2Drug Metabolism Discussion Group (DMDG), Leicester, UK

3Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden

1.1 PEOPLE, EVENTS, AND REACTION

Change, whether social or technological, often is catalyzed by a convergent set of events and influences. Drug testing using animals became important in the twentieth century. In 1937 a preparation of sulfanilamide, using diethylene glycol (DEG) as a solvent and called the preparation “elixir sulfanilamide,” was marketed. DEG is highly toxic and the preparation led to the deaths of more than a hundred people. No animal testing had been conducted, a step that would have highlighted the risks. The public outcry caused by this incident led to the passing of the 1938 Federal Food, Drug, and Cosmetic Act requiring safety testing of drugs on animals before they could be marketed. This event would have remained perhaps as a footnote, with drug metabolism remaining an academic pastime of minor note, but further events and people would catalyze dramatic change.

Richard Tecwyn Williams was one of the founding scientists in the systematic study of the metabolism of chemicals including drugs. He detailed this in a major book Detoxication Mechanisms which was published in 1947. His work led to the widely adopted phase 1 (oxidation, hydrolysis, etc.) and phase 2 (conjugation) divisions of drug metabolism. Following his appointment in 1949 to Chair of Biochemistry at St Mary’s Hospital Medical School in London, a growing group of researchers studied in the field. The group focused on many aspects of drug metabolism, but species differences in metabolism became a key topic, building on observations described in the aforementioned book. For instance, in 1956 together with Parke, he published a paper describing “species differences in the ortho-hydroxylation and para-hydroxylation of aniline.” As part of his later research activities (Schumacher et al. 1965), he examined the metabolism of thalidomide (a key component in the changes; see as follows) showing hydrolysis products and hydroxylated metabolites in various species, but a constant theme was species differences. Typical findings of Williams’ group are exemplified by studies with sulphamethomidine (Bridges et al. 1969). In the rat, rabbit, and monkey, the main metabolite was the N4-acetyl derivative. In man, the major metabolite was the sulphamethomidine N1-glucuronide, which was also excreted by the monkey but not by the rat or rabbit. Many other drugs were examined, all leading to descriptions of species differences of a major or minor form such as amphetamine, methamphetamine, etc. (Caldwell et al. 1972). In many of these publications, the use of 14C labeled drugs was used to obtain detailed results. The studies created an awareness that the products of metabolism excreted by animals could differ markedly from those excreted by man. Again this course of research could have remained an academic pursuit, but events dictated otherwise.

The drug thalidomide was first marketed in 1957 in West Germany under the trade name Contergan as a sedative. Generally very well tolerated it was prescribed for a number of CNS indications, but crucially it became commonly administered to counteract nausea and alleviate morning sickness in pregnant women. The drug was licensed out to other distributors and was widely used. A terrible consequence of its wide acceptance was the realization that thalidomide was a human teratogen. Throughout the world, about 10 000 cases were reported of infants with phocomelia (a malformation in which the limbs were absent or present as stumps), with a high morbidity (50% survival). Deformities were also observed in the eyes, hearts, and alimentary and urinary tracts. At this time there was no legal requirement for animal studies to evaluate risk in pregnancy, although they were already established, albeit without rigorous guidelines or protocols on species selection, duration, and size of dosing.

This drug tragedy led to a complete change in the way drugs could be marketed. For instance, in the United Kingdom in 1963, Sir Derrick Dunlop set up a committee to investigate the control and introduction of new medicines which resulted in the Committee on Safety of Drugs being established. This evolved into the Committee on Safety of Medicines. These moves paralleled the Kefauver Harris Amendment in the United States and Directive 65/65/EEC1 in the EU. The principal change was the enforcement that applicants needed to prove efficacy and to disclose all side effects encountered in testing prior to marketing approval.

1.2 THE RISE OF INDUSTRIAL DRUG METABOLISM

The metabolic fate of drugs in animals and man, in these times, was not a major focus or priority research topic for the innovator company. Illustrative of this period is propranolol, the first full antagonist of β-adrenoceptors which was discovered in 1962, first marketed in 1964. Analytical methods for propranolol were first published in 1965 with techniques relying on the optical (fluorescence) properties of the drug, while it was not until 1967 (Bond 1967) that preliminary reports on its metabolic fate first appeared.

Williams’ book title implied that metabolism was primarily a detoxification step, a concept that is still mainly correct. However growing evidence indicated that metabolism could also lead to toxicity. These observations concerned metabolites which were intrinsically reactive. Pioneering work on the carcinogenicity of polycyclic aromatic hydrocarbons and other planar heterocyclic aromatic compounds (Boyland 1969; Ames et al. 1972) had shown that the reactive metabolites were the ultimate toxin. This finding was broadened by early studies of liver necrosis in rodents. Many studies demonstrated that enhanced toxicity was associated with induction of liver enzymes by agents such as phenobarbital and attenuated toxicity with the inhibition of drug-metabolizing enzymes by agents such as SKF525A. Radiolabeled studies showed that this toxicity was accompanied by the irreversible covalent binding of drug-related material. By the 1970s Gillette et al. (1974) was able to establish that cellular necrosis, hypersensitivity, and blood dyscrasias could result from the formation of reactive metabolites.

The increased focus on drug safety, the realization that species differences could occur, and the concept that drugs could be metabolized to reactive metabolites and bind to organs, combined to lead to the decision that part of drug safety should have a drug metabolism component. Thus toxicology species and eventually human would be examined for overall excretion of the drug and its products, evidence that the drug had not been sequestered in the body (of animals) and a view as to what metabolites were produced. Metabolite profiling, where urine and feces extracts were compared quantitatively between species and eventually human, by techniques such as thin-layer chromatography became common practice. These experiments were conducted after the synthesis of a 14C- or 3H-labeled version of the candidate drug of interest. These early studies lacked sophistication as methodology was not advanced. Identifying metabolites required considerable workup of fairly large quantities. In vitro reagents such as human microsomes and hepatocytes were not available to allow early species comparisons. The principal focus was on excreted metabolites as evidenced with work on propranolol. The determination that 4-hydroxypropranolol, a major circulating metabolite of propranolol, had pharmacological activity equivalent to the parent was not made until 1971 (Fitzgerald and O’Donnell, 1971), 7 years after its launch.

Studies tended to report the identity of excreted metabolites. Circulating drug-related material was often reported as the proportion of parent present in the total radioactivity measured in plasma. Regardless of dose, results were quoted as percentage and not absolute amounts. Typical of this is isoxepac (6,11-dihydro-11-oxodibenz[be]oxepin-2-acetic acid) which Illing and Fromson reported in 1978. The disposition was studied in rat, rabbit, dog, rhesus monkey, and human. Fecal excretion of radioactivity occurred in the rat (26–37%) and dog (33–49%), whereas in the other species elimination was mainly urinary (<83%). Biliary excretion accounted for 18–52% of the dose in the rat and dog. Enterohepatic circulation was demonstrated in both species. Plasma of all species was found to contain mainly unchanged isoxepac. The compound was rapidly eliminated from plasma of dog, rhesus monkey, and man but was more slowly eliminated in rat and rabbit. In the rabbit and dog the principal metabolites were the glycine and taurine conjugates of isoxepac, respectively, whereas in the rhesus monkey and man, isoxepac was excreted unchanged or as the glucuronide. This species difference was highlighted even though the metabolites were conjugates. It is arguable that emphasis was put on species differences to justify publication. The emphasis from excreted metabolites to both circulating metabolites and excreted metabolites was a gradual process over the next decade, and authors began to state more implications for their findings. For instance, the disposition of amlodipine, R,S,2-[(2-aminoethoxy)methyl]-4-(2-chlorophenyl)-3-ethoxycarbonyl-5-methoxycarbonyl-6-methyl-1,4-dihydropyridine, was reported in 1998 by Beresford et al. and showed renal elimination was the major route of excretion. Only pyridine metabolites of amlodipine were excreted in urine (apart from a small amount of parent). The major excreted metabolite was 2-([4-(2-chlorophenyl)-3-ethoxycarbonyl-5-methoxycarbonyl-6-methyl-2-pyridyl] methoxy) acetic acid representing 33% of urinary radioactivity. The data indicated that oxidation of amlodipine to its pyridine analog is the principal route of metabolism with subsequent metabolism by oxidative deamination, de-esterification, and aliphatic hydroxylation. In the circulation amlodipine concentrations in plasma declined with a mean half-life of 33 h, while slower elimination of total drug-related material from plasma was observed. Importantly only amlodipine and pyridine metabolites were found in the circulation. As these pyridine derivatives have minimal calcium antagonist activity, the authors were able to conclude that the efficacy of amlodipine in man was due solely to the parent drug.

1.3 THE APPEARANCE OF MIST

Debate continued as to which was the more important matrix to study for metabolism, a debate often confused by the scientific objectives versus the technological challenges. The ad hoc approach to metabolism studies and comparison with animals continued until a unifying force appeared. In 2002 a report (Baillie et al. 2002) was published under the title Drug Metabolites in Safety Testing summarizing the deliberations of a multidisciplinary committee, sponsored by the Pharmaceutical Research and Manufacturers of America, on current “best practices” within the US pharmaceutical industry in assessing the role of drug metabolites as potential mediators of the toxicity of new drug products. A workshop was held in 2000 and the collective advice of members of the pharmaceutical industry, academic investigators, and representatives of regulatory was assembled. The paper set out to define practical and scientifically based approaches to the use of metabolite data that responded to issues in the safety evaluation of drug candidates. The report stated that consensus was lacking on how best to deal with several aspects and still case by case analysis was vital. Importantly the document did propose situations in which metabolites should be further studied to help define risk assessment for the parent drug. The primary trigger suggested was if the metabolite is present in humans at 25% or more of the total drug-related material in the circulation, it would require further investigation as a potential contributor to safety findings. This figure was based on the need for a defined limit and on pragmatic considerations of the technical feasibility of radiometric methods of quantitation, the results of which were almost always presented as percentage rather than absolute amounts. The title of the paper led to this branch of pharmaceutical sciences being branded metabolites in safety testing or more usually MIST.

In responding to this paper, the FDA produced a draft guidance, while a number of authors produced independent manuscripts. The FDA’s initial draft focused on 10% of the amount of drug. This was based on the toxicity of drugs such as halothane and paracetamol where the toxic metabolite was around 10% of the dose. Dialog on this and other aspects were presented by Smith and Obach in 2005 who proposed that absolute abundance criteria be used rather than relative abundance. The absolute abundance of a metabolite in circulation or excreta in humans should be combined with other information regarding the chemical structure of the metabolite (e.g., similarity to the parent drug, presence of chemically reactive substituents, or downstream products of reactivity) and potential mechanisms of toxicity (e.g., suprapharmacological effects or secondary pharmacological effects). Various redrafts that were discussed with the International Conference on Harmonization: Guideline on Nonclinical Safety Studies for the Conduct of Human Clinical Trials and Marketing Authorization for Pharmaceuticals (ICH M3[R2]) describe the threshold as 10% of total drug-related exposure. Metabolites above this threshold need to be qualified in preclinical toxicity testing by demonstrating similar exposure based on absolute amount (Robison and Jacobs, 2009). The case by case analysis now includes consideration of the metabolite type (e.g., N-glucuronides which are known to be preferentially formed in human but have no association with toxicity), protein binding, and actual concentrations observed in the clinic and safety testing rather than pure reliance on percentage.

1.4 THE JOURNEY TRIGGERED BY THALIDOMIDE: WOULD PRESENT SCIENCE HAVE MADE A DIFFERENCE?

At the outset of this chapter, we discussed the impact of thalidomide (Figure 1.1) on drug regulation and the trail to MIST. The question can be asked as to how well placed we are now to avoid another thalidomide and how present thinking would have impacted its development.

FIGURE 1.1 Structure of thalidomide.

Source: http://chemwiki.ucdavis.edu/Organic_Chemistry/Organic_Chemistry_With_a_Biological_Emphasis/Chapter_03%3A_Conformations_and_Stereochemistry/Section_3.3%3A_Stereoisomerism_%E2%80%93_chirality,_stereocenters,_enantiomers. http://creativecommons.org/licenses/by-nc-sa/3.0/us/.

Thalidomide shows species-specific effects on the developing embryo. Rodents rarely show birth defects even at high oral doses. Rabbits show teratogenic effects and their sensitivity to thalidomide is a major reason for their adoption as a pivotal species in reproductive studies. Clinically the drug was used as a hypnotic and sedative at dose from 25 to 200 mg (0.3–3 mg/kg). Even a single administration was thought to be sufficient to elicit malformations. To illustrate the range of effects in animals, the most sensitive species (Fratta et al. 1965), New Zealand White rabbits, showed dose-dependent fetal anomalies after administration orally of 50, 150, and 300 mg/kg (dosed from 4 to 16 days of gestation). In contrast CF1, ICR, SJL, CBA, and C57 mice did not produce malformed fetuses after oral dosing of 200 mg/kg. Rats (Long–Evans and Dunning–Fischer) and hamsters show no effects on fetuses at 150 mg/kg. At the same dose arachnodactyly was noted in 8% of the Dunning–Fischer inbred rats. Species differences such as this may suggest metabolism differences.

The hypothesis that thalidomide causes birth defects by being metabolized to a toxic electrophilic intermediate was advanced by Gordon et al. (1981). Supporting data that showed hepatic microsomes from pregnant rabbits mediated the production of a metabolite that was toxic to lymphocytes. Toxicity was enhanced by inhibitors of epoxide hydrolase and abolished by adding the purified enzyme to the incubation medium. The toxic metabolite of thalidomide was not produced by rat liver microsomes but was produced by hepatic preparations from monkey and human fetuses.

A more specific mechanism emerged a decade later. A study in 1994 (D’Amato et al. 1994) showed that orally administered thalidomide was an inhibitor of angiogenesis in a model using a rabbit cornea micropocket assay. The finding that this effect was only produced after oral administration indicated to the authors that an active metabolite was the causal agent. If confirmed the possibility of an unqualified human metabolite or one disproportionate to amounts formed in rodents would be a possibility. This route specificity and metabolite formation are not borne out by studies comparing the teratogenic potency of thalidomide has in rabbits and rats (Schumacher et al. 1968) after intravenous administration. After oral administration thalidomide was markedly teratogenic in rabbits but not rats. After intravenous injection of the drug, teratogenic effects were observed both in rabbits receiving daily doses as low as 2.5 mg/kg and in rats receiving doses of 10 mg/kg.

The evolution of technology allowed detailed metabolism studies to be performed. Metabolism studies (Chung et al. 2004) performed in vivo indicate that hydrolysis products are observed in humans and these are present in rabbit and mice. These hydrolysis products are formed spontaneously as well as enzymatically. Rabbits and mice also form hydroxylated metabolites which can also form glucuronides in mice. Mice appear more capable of oxidation than rabbits (Chung et al. 2004). This in vivo finding is also confirmed in in vitro studies (Lu et al. 2004) in which 5-hydroxy thalidomide was readily formed by mice and rabbit microsomes but only formed in trace quantities by human microsomes. The low rate of oxidation of thalidomide had been shown previously by Eriksson et al. (1998) who showed after incubation of thalidomide, with human liver S9, slow formation of the 5-hydroxy and 5′-hydroxy metabolites. In human volunteers who had received thalidomide, only the 5′-hydroxy metabolite was found in plasma samples. These detailed studies strongly indicate that metabolic differences do not account for species sensitivity toward thalidomide, and with the abundance of the unchanged drug in human, thalidomide itself is the causal agent.

In 2010 Ito and colleagues demonstrated that thalidomide itself initiated its detrimental effects on the embryo by binding to a protein (cereblon) and inhibiting the associated ubiquitin ligase activity. Cereblon forms an E3 ubiquitin ligase complex which ubiquitinates a number of other proteins resulting in reduced levels of fibroblast growth factor 8 (FGF8). FGF8 regulates a number of developmental processes, such as limb and auditory vesicle formation. Thus thalidomide binding to cereblon results in deleterious effects on limb outgrowth in embryos.

This important finding did not deter continued focus on reactive toxic metabolites, even using very sophisticated animal models (Yamazaki et al. 2011). For instance, in experiments with chimeric NOD–scid IL2Rgnull mice with humanized livers, after oral administration of racemic thalidomide, plasma concentrations of 5-hydroxythalidomide were significantly higher in humanized mice than in control mice. A glutathione conjugate was detected in the plasma. The results were interpreted as thalidomide activation occurring and of significance to its toxicity. It is likely that continued experiments will be published like this, even though cereblon binding of the drug itself seems to be a compelling mechanism.

Assuming that it is the parent drug which is the toxic species and the various reactive metabolite findings are not part of the mechanism, three possible scenarios could explain the species sensitivity. The species differences in teratogenicity could be explained by species differences in cereblon expression or structure leading to different affinities for thalidomide, species differences in the pharmacokinetics of thalidomide, or the downstream consequences of cereblon expression on the growing fetus.

Much more is now known about the receptor for thalidomide cereblon (Lopez-Girona et al. 2012; Fischer et al. 2014; Hartmann et al. 2014). This has been stimulated by its efficacy in diseases such as cancer. There is very strong conservation of the cereblon sequence between species. The actual ligand-binding domain, an aromatic cage of three tryptophan residues, has a high degree of conservation in both bacteria and eukaryotes. Thalidomide mimics and competes for the binding of uridine. It has binding affinity (Kd) of 250 nM. This suggests that the expression or structural differences in cereblon do not explain the species differences. The various pharmacokinetic properties for mouse, rabbits, and humans are compared in Table 1.1. Plasma protein binding of the drug is moderate with around 60% bound. While human could be rationalized as the most sensitive species with a single dose (200 mg) potentially inhibiting cereblon for 24 h, the data does not discriminate between teratogenic doses in rabbit (50 mg/kg) and nonteratogenic doses in mouse (200 mg/kg).

TABLE 1.1Pharmacokinetic Parameters Calculated from the Data Presented by Chung et al. (2004)

Dose (mg/kg)

T

1

/2 (h)

C

max

(μM)

C

av

(0–24 h) (μM)

Time above

K

d

(h)

Man

3

5

5

3.3

>24

Mouse

200

1

120

18

12

Rabbit

50

1.5

45

8

11

At this stage it suggests that there are differences between rodents, rabbits, and primates in the importance of cereblon and/or protein substrates modified by cereblon activity during embryonic development at different stages. The previous text indicates the difficulty in interpreting animal safety data. A detailed discussion of thalidomide and the value and limitations of animal testing, in particular reproductive studies, has been authored by Greek et al. (2011) and suggests the thalidomide disaster has not been repeated because of extreme caution in administering drugs to pregnant women rather than extensive animal testing. The review highlights the need to put into context the data from complex systems with different evolutionary systems. The authors suggest revision of the Federal Food, Drug, and Cosmetic Act including the Kefauver Harris Amendment based on current scientific knowledge. What exact revision is required is not stated, but it raises the question that if animal safety studies have high degrees of uncertainty in human prediction, does making them more complex add or diminish the uncertainty? Clearly thalidomide would have been detected in New Zealand rabbits under present protocols, but for another mechanism it is possible that similar species differences in response, but with different species, could give negative findings in reproductive testing, and the sole barrier is the aforementioned extreme caution in administering drugs to pregnant women. The focus on metabolism has continued for over 20 years and probably will continue even though a mechanism implicating the parent drug is established. Most drugs will form reactive metabolites, and with the sensitive systems employed today, they will be detected under the right conditions. In an analysis of the top 200 US prescribed drugs, approximately half contained one or more alerts in their chemical architecture to the possibility of generating reactive metabolites and in subsequent in vitro studies were found to form them (Stepan et al. 2011). Clearly drug metabolism can contribute to drug safety assessment, but it has to ensure that its results are not misleading or distracting from true mechanisms and species sensitivity. These are highlighted by comparison of pharmacokinetic parameters such as unbound drug concentrations across species as shown in Table 1.1.

1.5 KEY EVENTS FROM THALIDOMIDE TO MIST

A rapid advancement of understanding oxidative metabolism and in particular cytochrome P450 (CYP) allowed the variability in pharmacokinetics of drugs and their pharmacodynamics to be rationalized. The pivotal catalyst was the discovery (Mahgoub et al. 1977) of poor metabolizers (PMs) and extensive metabolizers (EMs) of debrisoquine, which was linked to the presence or absence of its hydroxylated metabolite in urine. Because not all drugs were affected in this way in the individuals, the concept of multiple human CYPs was developed. Concerted efforts to purify the enzyme(s) were initiated. The emerging clinical data and the purified enzymes revealed isoforms with broad substrate selectivity. Genetic sequences led to the multiple forms of CYP450 being classified into families (Nebert and Gonzalez 1987). Family 1 (CYP1) enzymes catalyzed the metabolism of many carcinogens and drugs. CYP2 and CYP3 catalyzed the metabolism of drugs; CYP4 lipids and other forms were involved in steroidogenesis.

The metabolism of debrisoquine was shown by an isoform now termed CYP2D6 which also metabolized the hydroxylation of beta-adrenoceptor blockers, class 1 antiarrythmics, tricyclic antidepressants, etc. These drugs all were ionized cations at physiological pH, and the position of hydroxylation was positionally similar in all the molecules. PM status was conferred by several “loss of function” alleles of the CYP CYP2D6 gene. “Ultrarapid” metabolizers were also identified, caused by duplication or amplification of the active CYP2D6 gene. Therapeutic failure changes, or toxicity to metabolites (see later), of CYP2D6 substrates could be associated with the ultrarapid status. Study of CYP2C9 revealed substrates such as losartan, phenytoin, tolbutamide, and torsemide. Again polymorphisms in the coding region of the CYP2C9 gene produced protein variants. Individuals with one of the variants (Leu359) have markedly diminished metabolic capacities for most CYP2C9 substrates and again can explain side effects but, equally important, diminished pharmacological response to drugs which are converted to active metabolites such as losartan (Miners and Birket 1998). CYP3A4 was identified as the most abundant and the isoform metabolizing the most marketed drugs and although highly variable in expression did not show the same polymorphisms.

Such advances helped to predict and understand drug variability per se and that caused by conmeds. The characterization of the isoforms allowed a rationalization of many drug–drug interactions. Warfarin often had raised concentrations and enhanced pharmacodynamics when administered with some nonsteroidal anti-inflammatory drugs (NSAIDs). The conventional belief was this was due to protein binding displacement. Enzymological studies conclusively proved it was inhibition of CYP2C9 (a major clearance enzyme for warfarin and NSAIDs) that caused the interaction.

A turning point in the science of drug interactions was created by terfenadine which was marketed as a nonsedating antihistamine. Until the problems with this drug were resolved, defining route of clearance and enzymology, if clearance was by metabolism, were not major priorities. In addition the impact of conmeds was not studied in a concise and detailed manner. Terfenadine would have been sedating (a lipophilic amine), but the pharmacologically active species was its zwitterionic metabolite fexofenadine, which had high selectivity for the H1 receptor and poor brain penetration. Terfenadine was very rapidly converted to this metabolite, and concentrations of the parent drug in the circulation were very low. Like many lipophilic amines terfenadine exhibited polypharmacology, and in addition to activity at the H1 receptor, the drug was a potent inhibitor of the IKr channel. Conversion to fexofenadine was by CYP3A4 (Yun et al. 1993), and coadministration with potent inhibitors of CYP3A4 such as ketoconazole or erythromycin (Honig et al. 1993) leads to elevated concentrations of terfenadine, which led to prolongation of QT in some individuals and in a small proportion of these fatal cardiac arrhythmias.

The biological response to a drug can be viewed in terms of on-target in which the drug or its metabolites interact with the desired target and off-target in which the drug or its metabolites interact with undesired receptors or enzymes. This concept of receptors includes reversible interactions with proteins and lipid bilayers and irreversible interactions where a protein is adducted, which may in itself be critical or be part of an immune response or a region of DNA critical to a cellular process. In this definition drug interactions triggered by enzyme or transporter inhibition are part of the off-target pharmacology of a drug. Both on- and off-target interactions can elicit toxicities. On-target side effects (suprapharmacological effects) arise as receptor occupancy or enzyme inhibition becomes too great or occupancy or inhibition occurs for too extended a period of time or affecting a receptor in a tissue that is not the tissue targeted for therapy. Factors that can cause this are poor dose selection and individual variability including drug metabolism enzyme or transporter polymorphism.

The example of tramadol illustrates how inter-individual variability can lead to on-target side effects (Gleason et al. 1997). The drug is a centrally acting analgesic which inhibits monoamine transporters and also acts as an agonist of μ-opioid receptors. The parent molecule has both activities, but the μ-opioid receptor agonist activity principally resides in its O-demethylated metabolite formed by CYP2D6. Structural comparison with morphine shows that the demethylated hydroxyl group is spatially identical to the essential 3-hydroxy group of opiate agonists such as morphine. Normally the drug is well tolerated; however, a patient, following a 100 mg dose of tramadol, rapidly developed ataxia, dilation of the pupils, limb numbness, tremulousness, and dysphoria. The patient was phenotyped for CYP2D6 activity and was found to be an extensive (super)metabolizer, with very high CYP2D6 activity.

Off-target toxicity is elicited by drugs or metabolites that do not have sufficient selectivity over the target receptor at therapeutic concentrations. An example of this is binding to the IKr channel and resultant QT interval prolongation and possible cardiac arrhythmias as evidenced by the aforementioned terfenadine. A further example is provided by the appetite suppressants fenfluramine and dexfenfluramine (single enantiomer of fenfluramine). These drugs caused pulmonary hypertension and valvular heart disease in patients, leading to their withdrawal from the market. Fenfluramine and dexfenfluramine are not the active principle. The major circulating metabolite norfenfluramine (nordexfenfluramine) is responsible for the pharmacological activity. The metabolites of the drug bind and activate 5-HT2C receptors, thereby reducing appetite. Norfenfluramine (nordexfenfluramine) is equally potent activating 5-HT2B receptors. Activation of 5-HT2B receptors on heart valves and pulmonary artery interstitial cells leads to the formation of proliferative fibromyxoid plaques that cause the toxicity (Fitzgerald et al. 2000; Rothman et al. 2000). This finding is shared by other drugs which activate at 5-HT2B receptors such as ergotamine and methysergide. Both these drugs are implicated in valvular heart disease.

The period saw increasing findings about the role of reactive metabolites in toxicity. Despite the large amount of work conducted, results were sometimes conflicting. In almost all cases the results were circumstantial without a full link to the toxic event. For example, work was conducted on paracetamol which showed species differences in hepatic effects. Different studies produced conflicting results. The drug and its putative toxic reactive metabolite, NAPQI, were investigated in hepatocytes from different species (Tee et al. 1987). Results from these studies showed acetaminophen triggered cell blebbing and loss of viability in the cells from mouse and hamster, whereas human and rat hepatocytes were much more resistant to these effects. When NAPQI, itself, was tested, there were no significant differences in the sensitivity of the cells, from any species. The conclusion reached in these studies was that species differences in sensitivity to the hepatotoxicity of acetaminophen were due to differences in the rate of formation of NAPQI and not to any intrinsic differences in sensitivity or in any difference in the fate of NAPQI once formed. In contrast monitoring downstream NAPQI metabolites (activation) including glutathione, cysteinylglycine, cysteine, and mercapturate conjugates and detoxification pathways such as paracetamol glucuronide and sulfate conjugates indicated species sensitivity being determined by the balance between toxification and detoxication metabolic pathways (Gregus et al. 1988).