Drug Discovery Toxicology

Yvonne Will, PhD, is a Senior Director and the Head of Science and Technology Strategy, Drug Safety Research and Development at Pfizer, Connecticut, USA. She co-edited the book Drug-Induced Mitochondrial Dysfunction, published by Wiley in 2008. J. Eric McDuffie, PhD, is the Director of the Discovery / Investigative Toxicology and Laboratory Animal Medicine groups at Janssen Research & Development, California, USA. Andrew J. Olaharski, PhD, is an Associate Director of Toxicology at Agios Pharmaceuticals, Massachusetts, USA. Brandon D. Jeffy, PhD, is a Senior Principal Scientist in the Exploratory Toxicology division of Nonclinical Development at Celgene Pharmaceuticals, California, USA.

LIST OF CONTRIBUTORS xxi

FOREWORD xxv

PART I INTRODUCTION 1

1 Emerging Technologies and their Role in Regulatory Review 3
Thomas J. Colatsky

1.1 Introduction 3

1.2 safety assessment in Drug Development and Review 4

1.3 The Role of New Technologies in Regulatory Safety Assessment 6

1.4 Conclusions 8

References 8

PART II SAFETY LEAD OPTIMIZATION STRATEGIES 13

2 Small‐Molecule Safety Lead Optimization 15
Donna M. Dambach

2.1 Background and Objectives of Safety Lead Optimization Approaches 15

2.2 Target Safety Assessments: Evaluation of Undesired Pharmacology and Therapeutic Area Considerations 16

2.3 Implementing Lead Optimization Strategies for Small Molecules 16

2.4 Conclusions 23

References 23

3 Safety Assessment Strategies and Predictive Safety of Biopharmaceuticals and Antibody Drug Conjugates 27
Michelle J. Horner, Mary Jane Hinrichs and Nicholas Buss

3.1 Background and Objectives 27

3.2 Target Safety Assessments: Strategies to Understand Target Biology and Associated Liabilities 28

3.3 Strategic Approaches for Biopharmaceuticals and ADCs 29

3.4 Predictive Safety Tools for Large Molecules 33

3.5 Strategies for Species Selection 34

3.6 Strategy for Dose‐Ranging Studies for Safety Evaluation of Biopharmaceuticals 35

3.7 Conclusions 35

References 36

4 Discovery and Development Strategies for Small Interfering Rnas 39
Scott A. Barros and Gregory Hinkle

4.1 Background 39

4.2 Target Assessments 40

4.3 siRNA Design and Screening Strategies 41

4.4 Safety Lead Optimization of siRNA 45

4.5 Integration of Lead Optimization Data for Candidate Selection and Development 48

4.6 Conclusions 49

References 49

PART III BASIS FOR IN VITRO–IN VIVO PK TRANSLATION 53

5 Physicochemistry and the Off‐Target Effects of Drug Molecules 55
Dennis A. Smith

5.1 Lipohilicity, Polar Surface Area, and Lipoidal Permeability 55

5.2 Physicochemistry and Basic ADME Properties for High Lipoidal Permeability Drugs 56

5.3 Relationship between Volume of Distribution (Vd) and Target Access for Passively Distributed Drugs 58

5.4 Basicity, Lipophilicity, and Volume of Distribution as a Predictor of Toxicity (T): Adding The T to ADMET 59

5.5 Basicity and Lipophilicity as a Predictor of Toxicity (T): Separating the D from T in ADMET 60

5.6 Lipophilicity and PSA as a Predictor of Toxicity (T): Adding the T to ADMET 60

5.7 Metabolism and Physicochemical Properties 61

5.8 Concentration of Compounds by Transporters 61

5.9 Inhibition of Excretion Pumps 63

5.10 Conclusions 64

References 65

6 The Need for Human Exposure Projection in the Interpretation of Preclinical In Vitro and In Vivo ADME Tox Data 67
Patrick Poulin

6.1 Introduction 67

6.2 Methodology Used for Human PK Projection in Drug Discovery 67

6.3 Summary of the Take‐Home Messages from the Pharmaceutical Research and Manufacturers of America Cpcdc Initiative on Predictive Models of Human PK from 2011 72

Abbreviations 77

References 77

7 A DME Properties Leading to Toxicity 82
Katya Tsaioun

7.1 Introduction 82

7.2 The Science of ADME 83

7.3 The ADME Optimization Strategy 83

7.4 Conclusions and Future Directions 89

References 90

PART IV Predicting Organ Toxicity 93

8 Liver 95
J. Gerry Kenna, Mikael Persson, Scott Q. Siler, Ke Yu, Chuchu Hu, Minjun Chen, Joshua Xu, Weida Tong, Yvonne Will and Michael D. Aleo

8.1 Introduction 95

8.2 DILI Mechanisms and Susceptibility 96

8.3 Common Mechanisms that Contribute to DILI 98

8.4 Models Systems Used to Study DILI 108

8.5 In Silico Models 114

8.6 Systems Pharmacology and DILI 118

8.7 Summary 119

References 121

9 Cardiac 130
David J. Gallacher, Gary Gintant, Najah Abi‐Gerges, Mark R. Davies, Hua Rong Lu, Kimberley M. Hoagland, Georg Rast, Brian D. Guth, Hugo M. Vargas and Robert L. Hamlin

9.1 General Introduction 130

9.2 Classical In Vitro/Ex Vivo Assessment of Cardiac Electrophysiologic Effects 133

9.3 Cardiac Ion Channels and In Silico Prediction 137

9.4 From Animal Ex Vivo/In Vitro Models to Human Stem Cell‐Derived Cms for Cardiac Safety Testing 140

9.5 In Vivo Telemetry Capabilities and Preclinical Drug Development 141

9.6 Assessment of Myocardial Contractility in Preclinical Models 144

9.7 Assessment of Large Versus Small Molecules in CV SP 147

9.8 Patients do not Necessarily Respond to Drugs and Devices as do Genetically Identical, Young Mature, Healthy Mice! 148

References 152

10 Predictive In Vitro Models for Assessment of Nephrotoxicity and Drug–Drug Interactions In Vitro 160
Lawrence H. Lash

10.1 Introduction 160

10.2 Biological Processes and Toxic Responses of the Kidneys that are Normally Measured in Toxicology Research and Drug Development Studies 163

10.3 Primary Cultures of hPT Cells 164

10.4 Toxicology Studies in hPT Primary Cell Cultures 166

10.5 Critical Studies for Drug Discovery in hpt Primary Cell Cultures 168

10.6 S ummary and Conclusions 168

References 170

11 Predicting Organ Toxicity In Vitro: Bone Marrow 172
Ivan Rich and Andrew J. Olaharski

11.1 Introduction 172

11.2 Biology of the Hematopoietic System 172

11.3 Hemotoxicity 173

11.4 Measuring Hemotoxicity 173

11.5 The Next Generation of Assays 175

11.6 Proliferation or Differentiation? 175

11.7 Measuring and Predicting Hemotoxicity In Vitro 176

11.8 Detecting Stem and Progenitor Cell Downstream Events 177

11.9 Bone Marrow Toxicity Testing During Drug Development 177

11.10 Paradigm for In Vitro Hemotoxicity Testing 178

11.11 Predicting Starting Doses for Animal and Human Clinical Trials 179

11.12 Future Trends 179

11.13 Conclusions 180

References 180

12 Predicting Organ Toxicity In Vitro: Dermal Toxicity 182
Patrick J. Hayden, Michael Bachelor, Mitchell Klausner and Helena Kandárová

12.1 Introduction 182

12.2 Overview of Drug‐Induced Adverse Cutaneous Reactions 182

12.3 Overview of In Vitro Skin Models with Relevance to Preclinical Drug Development 183

12.4 Specific Applications of In Vitro Skin Models and Predictive In Vitro Assays Relevant to Pharmaceutical Development 184

12.5 Mechanism‐Based Cutaneous Adverse Effects 187

12.6 Summary 188

References 189

13 In Vitro Methods in Immunotoxicity Assessment 193
Xu Zhu and Ellen Evans

13.1 Introduction and Perspectives on In Vitro Immunotoxicity Screening 193

13.2 Overview of the Immune System 194

13.3 Examples of In Vitro Approaches 196

13.4 Conclusions 198

References 199

14 Strategies and Assays for Minimizing Risk of Ocular Toxicity during Early Development of Systemically Administered Drugs 201
Chris J. Somps, Paul Butler, Jay H. Fortner, Keri E. Cannon and Wenhu Huang

14.1 Introduction 201

14.2 In Silico and In Vitro Tools and Strategies 201

14.3 Higher‐Throughput In Vivo Tools and Strategies 202

14.4 S trategies, Gaps, and Emerging Technologies 208

14.5 Summary 210

References 210

15 Predicting Organ Toxicity In Vivo—Central Nervous System 214
Greet Teuns and Alison Easter

15.1 Introduction 214

15.2 Models for Assessment of CNS ADRs 214

15.3 S eizure Liability Testing 216

15.4 Drug Abuse Liability Testing 218

15.5 General Conclusions 222

15.5.1 In Vitro 222

15.5.2 In Vivo 223

Abbreviations 223

References 224

16 Biomarkers, Cell Models, and In Vitro Assays for Gastrointestinal Toxicology 227
Allison Vitsky and Gina M. Yanochko

16.1 Introduction 227

16.2 A natomic and Physiologic Considerations 228

16.3 GI Biomarkers 229

16.4 Cell Models of the GI Tract 231

16.5 Cell‐Based In Vitro Assays for Screening and Mechanistic Investigations to Gi Toxicity 235

16.6 Summary/Conclusions/Challenges 236

References 236

17 Preclinical Safety Assessment of Drug Candidate‐Induced Pancreatic Toxicity: From an Applied Perspective 242
Karrie A. Brenneman, Shashi K. Ramaiah and Lauren M. Gauthier

17.1 Drug‐Induced Pancreatic Toxicity 242

17.2 Preclinical Evaluation of Pancreatic Toxicity 245

17.3 Preclinical Pancreatic Toxicity Assessment: In Vivo 247

17.4 Pancreatic Biomarkers 249

17.5 Preclinical Pancreatic Toxicity Assessment: In Vitro 253

17.6 Summary and Conclusions 257

Acknowledgments 258

References 258

PART V A DDRESSING THE FALSE NEGATIVE SPACE—INCREASING

PREDICTIVITY 261

18 Animal Models of Disease for Future Toxicity Predictions 263
Sherry J. Morgan and Chandikumar S. Elangbam

18.1 Introduction 263

18.2 Hepatic Disease Models 264

18.3 Cardiovascular Disease Models 268

18.4 Nervous System Disease Models 270

18.5 Gastrointestinal Injury Models 273

18.6 Renal Injury Models 279

18.7 Respiratory Disease Models 282

18.8 Conclusion 285

References 287

19 The Use of Genetically Modified Animals in Discovery Toxicology 298
Dolores Diaz and Jonathan M. Maher

19.1 Introduction 298

19.2 Large‐Scale Gene Targeting and Phenotyping Efforts 299

19.3 Use of Genetically Modified Animal Models in Discovery Toxicology 300

19.4 The Use of Genetically Modified Animals in Pharmacokinetic and Metabolism Studies 303

19.5 Conclusions 309

References 309

20 Mouse Population-Based Toxicology for Personalized Medicine and Improved Safety Prediction 314
Alison H. Harrill

20.1 Introduction 314

20.2 Pharmacogenetics and Population Variability 314

20.3 Rodent Populations Enable a Population‐Based Approaches to Toxicology 316

20.4 Applications for Pharmaceutical Safety Science 320

20.5 Study Design Considerations for Genomic Mapping 322

20.6 Summary 326

References 326

PART VI STEM CELLS IN TOXICOLOGY 331

21 Application of Pluripotent Stem Cells in Drug‐Induced Liver Injury Safety Assessment 333
Christopher S. Pridgeon, Fang Zhang, James A. Heslop, Charlotte M.L. Nugues, Neil R. Kitteringham, B. Kevin Park and Christopher E.P. Goldring

21.1 The Liver, Hepatocytes, and Drug‐Induced Liver Injury 333

21.2 Current Models of Dili 334

21.3 Uses of iPSC HLCs 338

21.4 Challenges of Using ipscs and New Directions for Improvement 339

21.5 Alternate Uses of HLCs in Toxicity Assessment 341

References 342

22 Human Pluripotent Stem Cell‐Derived Cardiomyocytes: A New Paradigm in Predictive Pharmacology and Toxicology 346
Praveen Shukla, Priyanka Garg and Joseph C. Wu

22.1 Introduction 346

22.2 A dvent of hPSCs: Reprogramming and Cardiac Differentiation 347

22.3 iPSC‐Based Disease Modeling and Drug Testing 349

22.4 Traditional Target‐Centric Drug Discovery Paradigm 354

22.5 iPSC‐Based Drug Discovery Paradigm 354

22.6 Limitations and Challenges 358

22.7 Conclusions and Future Perspective 359

Acknowledgments 360

References 360

23 Stem Cell‐Derived Renal Cells and Predictive Renal In Vitro Models 365
Jacqueline Kai Chin Chuah, Yue Ning Lam, Peng Huang and Daniele Zink

23.1 Introduction 365

23.2 Protocols for the Differentiation of Pluripotent Stem Cells into Cells of the Renal Lineage 367

23.3 Renal In Vitro Models for Drug Safety Screening 376

23.4 Achievements and Future Directions 378

Acknowledgments 379

Notes 379

References 379

PART VII CURRENT STATUS OF PRECLINICAL IN VIVO TOXICITY BIOMARKERS 385

24 Predictive Cardiac Hypertrophy Biomarkers in Nonclinical Studies 387
Steven K. Engle

24.1 Introduction to Biomarkers 387

24.2 Cardiovascular Toxicity 387

24.3 Cardiac Hypertrophy 388

24.4 Diagnosis of Cardiac Hypertrophy 389

24.5 Biomarkers of Cardiac Hypertrophy 389

24.6 Case Studies 392

24.7 Conclusion 392

References 393

25 Vascular Injury Biomarkers 397
Tanja S. Zabka and Kaïdre Bendjama

25.1 Historical Context of Drug‐Induced Vascular Injury and Drug Development 397

25.2 Current State of Divi Biomarkers 398

25.3 Current Status and Future of In Vitro Systems to Investigate Divi 402

25.4 Incorporation of In Vitro and In Vivo Tools in Preclinical Drug Development 403

25.5 Divi Case Study 403

References 403

26 Novel Translational Biomarkers of Skeletal Muscle Injury 407
Peter M. Burch and Warren E. Glaab

26.1 Introduction 407

26.2 Overview of Drug‐Induced Skeletal Muscle Injury 407

26.3 Novel Biomarkers of Drug‐Induced Skeletal Muscle Injury 409

26.4 Regulatory Endorsement 411

26.5 Gaps and Future Directions 411

26.6 Conclusions 412

References 412

27 Translational Mechanistic Biomarkers and Models for Predicting Drug‐Induced Liver Injury : Clinical to In Vitro Perspectives 416
Daniel J. Antoine

27.1 Introduction 416

27.2 Drug‐Induced Toxicity and the Liver 417

27.3 Current Status of Biomarkers for the Assessment of DILI 418

27.4 Novel Investigational Biomarkers for DILI 419

27.5 In Vitro Models and the Prediction of Human Dili 422

27.6 Conclusions and Future Perspectives 423

References 424

PART VIII Kidney Injury Biomarkers 429

28 Assessing and Predicting Drug‐Induced Kidney Injury, Functional Change, and Safety in Preclinical Studies in Rats 431
Yafei Chen

28.1 Introduction 431

28.2 Kidney Functional Biomarkers (Glomerular Filtration and Tubular Reabsorption) 433

28.3 Novel Kidney Tissue Injury Biomarkers 435

28.4 Novel Biomarkers of Kidney Tissue Stress Response 436

28.5 Application of an Integrated Rat Platform (Automated Blood Sampling and Telemetry, Abst) for Kidney Function and Injury Assessment 437

References 439

29 Canine Kidney Safety Protein Biomarkers 443
Manisha Sonee

29.1 Introduction 443

29.2 Novel Canine Renal Protein Biomarkers 443

29.3 Evaluations of Novel Canine Renal Protein Biomarker Performance 444

29.4 Conclusion 444

References 445

30 Traditional Kidney Safety Protein Biomarkers and Next‐Generation Drug‐Induced Kidney Injury Biomarkers in Nonhuman Primates 446
Jean‐Charles Gautier and Xiaobing Zhou

30.1 Introduction 446

30.2 Evaluations of Novel Nhp Renal Protein Biomarker Performance 447

30.3 New Horizons: Urinary MicroRNAs and Nephrotoxicity in Nhps 447

References 447

31 Rat Kidney MicroRNA Atlas 448
Aaron T. Smith

31.1 Introduction 448

31.2 Key Findings 448

References 449

32 MicroRNAs as Next‐Generation Kidney Tubular Injury Biomarkers in Rats 450
Heidrun Ellinger‐Ziegelbauer and Rounak Nassirpour

32.1 Introduction 450

32.2 Rat Tubular miRNAs 450

32.3 Conclusions 451

References 451

33 MicroRNAs as Novel Glomerular Injury Biomarkers in Rats 452
Rachel Church

33.1 Introduction 452

33.2 Rat Glomerular miRNAs 452

References 453

34 Integrating Novel Imaging Technologies to Investigate Drug‐Induced Kidney Toxicity 454
Bettina Wilm and Neal C. Burton

34.1 Introduction 454

34.2 Overviews 455

34.3 Summary 456

References 456

35 In Vitro to In Vivo Relationships with Respect to Kidney Safety Biomarkers 458
Paul Jennings

35.1 Renal Cell Lines as Tools for Toxicological Investigations 458

35.2 Mechanistic Approaches and In Vitro to In Vivo Translation 459

35.3 Closing Remarks 460

References 460

36 Case Study: Fully Automated Image Analysis of Podocyte Injury Biomarker Expression in Rats 462
Jing Ying Ma

36.1 Introduction 462

36.2 Material and Methods 462

36.3 Results 463

36.4 Conclusions 465

References 465

37 Case Study: Novel Renal Biomarkers Translation to Humans 466
Deborah A. Burt

37.1 Introduction 466

37.2 Implementation of Translational Renal Biomarkers in Drug Development 466

37.3 Conclusion 467

References 467

38 Case Study: Microrn as as Novel Kidney Injury Biomarkers in Canines 468
Craig Fisher, Erik Koenig and Patrick Kirby

38.1 Introduction 468

38.2 Material and Methods 468

38.3 Results 468

38.4 Conclusions 470

References 470

39 Novel Testicular Injury Biomarkers 471
Hank Lin

39.1 Introduction 471

39.2 The Testis 471

39.3 Potential Biomarkers for Testicular Toxicity 472

39.4 Conclusions 473

References 473

PART IX Best Practices in Biomarker Evaluations 475

40 Best Practices in Preclinical Biomarker Sample Collections 477
Jaqueline Tarrant

40.1 Considerations for Reducing Preanalytical Variability in Biomarker Testing 477

40.2 Biological Sample Matrix Variables 477

40.3 Collection Variables 480

40.4 Sample Processing and Storage Variables 480

References 480

41 Best Practices in Novel Biomarker Assay Fit‐for‐Purpose Testing 481
Karen M. Lynch

41.1 Introduction 481

41.2 Why Use a Fit‐for‐Purpose Assay? 481

41.3 Overview of Fit‐for‐Purpose Assay Method Validations 482

41.4 Assay Method Suitability in Preclinical Studies 482

41.5 Best Practices for Analytical Methods Validation 482

41.6 Species‐ and Gender‐Specific Reference Ranges 486

41.7 Analyte Stability 487

41.8 Additional Method Performance Evaluations 487

References 487

42 Best Practices in Evaluating Novel Biomarker Fit for Purpose and Translatability 489
Amanda F. Baker

42.1 Introduction 489

42.2 Protocol Development 489

42.3 Assembling an Operations Team 489

42.4 Translatable Biomarker Use 490

42.5 Assay Selection 490

42.6 Biological Matrix Selection 490

42.7 Documentation of Patient Factors 491

42.8 Human Sample Collection Procedures 491

42.9 Choice of Collection Device 491

42.10 Schedule of Collections 492

42.11 Human Sample Quality Assurance 492

42.12 Logistics Plan 493

42.13 Database Considerations 493

42.14 Conclusive Remarks 493

References 493

43 Best Practices in Translational Biomarker Data Analysis 495
Robin Mogg and Daniel Holder

43.1 Introduction 495

43.2 Statistical Considerations for Preclinical Studies of Safety Biomarkers 496

43.3 Statistical Considerations for Exploratory Clinical Studies of Translational Safety Biomarkers 497

43.4 Statistical Considerations for Confirmatory Clinical Studies of Translational Safety Biomarkers 498

43.5 Summary 498

References 498

44 Translatable Biomarkers in Drug Development: Regulatory Acceptance and Qualification 500
John‐Michael Sauer, Elizabeth G. Walker and Amy C. Porter

44.1 Safety Biomarkers 500

44.2 Qualification of Safety Biomarkers 501

44.3 Letter of Support for Safety Biomarkers 502

44.4 Critical Path Institute’s Predictive Safety Testing Consortium 502

44.5 Predictive Safety Testing Consortium and its Key Collaborations 504

44.6 Advancing the Qualification Process and Defining Evidentiary Standards 505

References 506

PART X Conclusions 509

45 Toxicogenomics in Drug Discovery Toxicology: History, Methods, Case Studies, and Future Directions 511
Brandon D. Jeffy, Joseph Milano and Richard J. Brennan

45.1 A Brief History of Toxicogenomics 511

45.2 Tools and Strategies for Analyzing Toxicogenomics Data 513

45.3 Drug Discovery Toxicology Case Studies 519

References 525

46 Issue Investigation and Practices in Discovery Toxicology 530
Dolores Diaz, Dylan P. Hartley and Raymond Kemper

46.1 Introduction 530

46.2 Overview of Issue Investigation in the Discovery Space 530

46.3 Strategies to Address Toxicities in the Discovery Space 532

46.4 Cross‐Functional Collaborative Model 533

46.5 Case‐Studies of Issue Resolution in The Discovery Space 536

46.6 Data Inclusion in Regulatory Filings 538

References 538

ABBREVIATIONS 540

CONCLUDING REMARKS 542

INDEX 543