Predictive Toxicology: From Vision to Reality

Tailored to the needs of scientists developing drugs, chemicals, cosmetics and other products this one–stop reference for medicinal chemists covers all the latest developments in the field of predictive toxicology and its applications in safety assessment.

With a keen emphasis on novel approaches, the topics have been tackled by selected expert scientists, who are familiar with the theoretical scientific background as well as with the practical application of current methods. Emerging technologies in toxicity assessment are introduced and evaluated in terms of their predictive power, with separate sections on computer predictions and simulation methods, novel in vitro systems including those employing stem cells, toxicogenomics and novel biomarkers. In each case, the most promising methods are discussed and compared to classical in vitro and in vivo toxicology assays. Finally, an outlook section discusses such forward–looking topics as immunotoxicology assessment and novel regulatory requirements.

With its wealth of methodological knowledge and its critical evaluation of modern approaches, this is a valuable guide for toxicologists working in pharmaceutical development, as well as in safety assessment and the regulation of drugs and chemicals.

List of Contributors XV

Preface XXI

A Personal Foreword XXIII

1 Introduction to Predictive Toxicology Tools and Methods1
Laura Suter–Dick and Friedlieb Pfannkuch

1.1 Computational Tools and Bioinformatics 1

1.1.1 In Silico Prediction Tools 1

1.1.2 Bioinformatics 2

1.2 Omics Technologies 2

1.2.1 Toxicogenomics (Transcriptomics) 2

1.2.2 Proteomics 3

1.2.3 Metabolomics 3

1.3 Data Interpretation and Knowledge Management 4

1.4 Biomarker Development 4

1.5 Advanced In Vitro Systems and Stem Cell Research 4

1.5.1 Advanced In Vitro Testing 4

1.5.2 Stem Cell Research 5

1.6 Immunogenicity 6

1.7 Integration and Validation 7

1.7.1 Use of Omics for Toxicology Testing 7

1.7.2 Integration of New Technologies into RiskAssessment 7

1.7.3 Use of Human–Derived Cellular Systems 8

1.7.4 General Acceptance Translation intoGuidelines 8

1.8 Research Initiative/Collaborations 9

1.9 Concluding Remarks 9

References 9

2 In Silico Toxicology Current Approaches and FuturePerspectives to Predict Toxic Effects with Computational Tools11
Thomas Steger–Hartmann

2.1 Introduction 11

2.2 Prediction of Hazard 11

2.2.1 Definition of Hazard and Its Use 11

2.2.2 Prediction of Mutagenicity 12

2.2.3 Prediction of Phospholipidosis 13

2.2.4 Prediction of Carcinogenicity 14

2.2.5 Prediction of Skin Sensitization 14

2.2.6 Prediction of Skin and Eye Irritation 16

2.2.7 Approaches to Systemic Toxicity Prediction 17

2.3 Prediction of Risk 21

2.3.1 Risk Definition and Some Basic Considerations 21

2.3.2 Data Availability 23

2.3.3 Database Structure and Data Curation 24

2.3.4 Approaches to Model and Predict Risk 26

2.4 Thoughts on Validation 27

2.5 Conclusions and Outlook 28

References 28

3 In Silico Approaches: Data Management Bioinformatics 33
Arnd Brandenburg, Hans Gmuender, and Timo Wittenberger

3.1 Introduction 33

3.2 Experimental Setup and Statistical Power 34

3.3 Properties of Different Omics Data 35

3.3.1 Next–Generation Sequencing Data 35

3.3.2 DNA Methylation Data 36

3.3.3 miRNA Data 36

3.3.4 CNV and SNP Data 36

3.3.5 ChIP–seq Data 37

3.3.6 Gene Expression Microarray Data (Affymetrix) 37

3.3.7 Mass Spectrometry Data 38

3.3.8 Missing Values and Zero Values 40

3.3.9 Data Normalization 40

3.4 Statistical Methods 41

3.4.1 Data Overviews 41

3.4.2 Null Hypothesis/Type I and Type II Errors 42

3.4.3 Multiple Testing Methods 42

3.4.4 Statistical Tests 43

3.4.5 Linear Models and Linear Mixed Models 43

3.5 Prediction and Classification 44

3.5.1 Overview 44

3.5.2 Generating a Reference Compendium of Compounds 45

3.5.3 Cross–Validation 46

3.5.4 Selection Bias 47

3.6 Combining Different Omics Data and BiologicalInterpretations 47

3.7 Data Management 48

References 51

4 Role of Modeling and Simulation in Toxicology Prediction53
Antje–Christine Walz, Hans Peter Grimm, Christophe Meille,Antonello Caruso, Neil Parrott, and Thierry Lavé

4.1 Introduction 53

4.2 The Need to Bring PK and PD in Predictive Models Together54

4.2.1 Physiologically Based Pharmacokinetic Modeling 54

4.2.2 Mathematical (PBPK, PK/PD) Modeling 55

4.2.3 Predictive Tools 55

4.3 Methodological Aspects and Concepts 56

4.3.1 Cascading Drug Effects 56

4.3.2 Linking Exposure and Effect 57

4.3.3 Receptor Occupancy/Enzyme Inhibition 57

4.3.4 Transduction into In Vivo Response 57

4.3.5 Disease Modeling 59

4.4 Application During Lead Optimization 60

4.4.1 Example 1: PK/PD Modeling for Identifying the TherapeuticWindow between an Efficacy and a Safety Response 60

4.5 Application During Clinical Candidate Selection 62

4.5.1 Example 2: Translational PK/PD Modeling to Support Go/NoGo Decisions 63

4.6 Entry–into–Human Preparation and Translational PK/PDModeling 65

4.6.1 Selection of Safe and Pharmacologically Active Dose forAnticancer Drugs 65

4.6.2 PK/PD for Toxicology Study Design and Evaluation 67

4.7 Justification of Starting Dose, Calculation of SafetyMargins, and Support of Phase I Clinical Trial Design 69

4.8 Outlook and Conclusions 70

References 71

5 Genomic Applications for Assessing Toxicities of Liver andKidney Injury 73
Philip Hewitt and Esther Johann

5.1 Introduction 73

5.1.1 Toxicogenomics in Drug Development 73

5.2 Toxicogenomic Approaches 75

5.2.1 High–Throughput Expression Profiles and DNA Microarrays75

5.2.2 Data Analysis 76

5.3 Specific Applications of Toxicogenomics 77

5.3.1 Mechanistic Toxicogenomics and Risk Assessment 77

5.3.2 Toxicogenomic Profiling of Hepatotoxicity 78

5.3.3 Functional and Structural Properties of the Liver 78

5.3.4 Liver Morphology 79

5.3.5 Cell Types 80

5.3.6 Functional Gradients 80

5.4 Toxicogenomic Applications for the Better Understanding ofHepatotoxicity 80

5.4.1 Mechanistic Toxicology 80

5.4.2 Class Identification 82

5.4.3 Predictive Toxicology 83

5.4.4 In Vitro Classifiers of Hepatotoxicity 84

5.4.5 Biomarker Identification 84

5.5 Toxicogenomic Profiling of Nephrotoxicity 86

5.5.1 Toxicogenomic Approaches in Nephrotoxicity 86

5.5.2 Finding Genes that Matter in AKI 87

5.5.3 Searching for New Biomarkers of Kidney Injury 88

5.6 Limitations of Toxicogenomics 90

5.6.1 Idiosyncrasies 90

5.6.2 Epigenetics 91

5.7 Conclusions 91

References 92

6 Use of Toxicogenomics for Mechanistic Characterization ofHepatocarcinogens in Shorter Term Studies 97
Heidrun Ellinger–Ziegelbauer

6.1 Introduction 97

6.1.1 Rodent Carcinogenicity Testing 97

6.1.2 Classes of Carcinogens 99

6.2 Toxicogenomics 99

6.2.1 Mechanistic Toxicogenomic Analysis after Short–TermTreatment with Rodent Hepatocarcinogens 99

6.2.2 Approaches for Prediction of Potential HepatocarcinogensBased on Gene Expression Profiling 104

6.2.3 Recent Developments: Transcriptional Benchmark DoseModeling Based on Functional Analyses 119

6.2.4 Recent Opportunities: Publicly Available Data 120

6.3 Conclusions and Outlook 123

References 123

7 Discovery and Application of Novel Biomarkers 129
Timothy W. Gant, Emma L. Marczylo, and Martin O. Leonard

7.1 Introduction 129

7.1.1 New Technologies Give Rise to Novel Opportunities forBiomarker Discovery 130

7.2 Novel RNA Biomarkers 131

7.2.1 The Complex RNA Biomarker in Cancer 131

7.2.2 The Complex RNA Biomarker in Toxicology 133

7.2.3 Connectivity Mapping with the Complex RNA Biomarker forHazard Identification 134

7.2.4 miRNA Biomarkers 135

7.3 DNA as a Biomarker 138

7.3.1 DNA Polymorphisms as Future Biomarkers of Disease andXenobiotic Susceptibility 138

7.3.2 DNA and Protein Adduct Biomarkers 140

7.3.3 Epigenetic Biomarkers 140

7.4 Novel Biomarkers: Beyond Nucleotide–Based Discovery 143

7.5 Summary and Outlook 145

References 146

8 Predictive Toxicology: Genetics, Genomics, Epigenetics, andNext–Generation Sequencing in Toxicology 151
Tobias Heckel and Laura Suter–Dick

8.1 Introduction 151

8.2 Technological Advances 152

8.3 Applications in Toxicology 154

8.3.1 Genome Sequencing and Sequence Level Comparisons 154

8.3.2 Genotype and Metabolism 157

8.3.3 Mechanistic Toxicology and Toxicogenomics 160

8.3.4 Epigenetic Changes and miRNAs 162

8.4 Summary and Outlook 164

References 165

9 Biomarkers as Tools for Predictive Safety Assessment: NovelMarkers of Drug–Induced Kidney Injury 171
Angela Mally

9.1 Need and Search for Novel Biomarkers of Kidney Injury171

9.2 Urinary Biomarkers of Drug–Induced Kidney Injury 172

9.2.1 Structure and Function of Novel Urinary Biomarkers 172

9.2.2 Experimental and Clinical Support for the Use of NovelUrinary Biomarkers for the Detection and Prediction of Acute KidneyInjury 177

9.3 Genomic Biomarkers 179

9.3.1 Individual Genes 179

9.3.2 Biomarker Panels and Gene Signatures 180

9.3.3 MicroRNAs 181

9.4 Qualification and Use of Novel Kidney Injury Biomarkers inPreclinical Safety Assessment 182

9.4.1 Biomarker Qualification and Regulatory Acceptance 182

9.4.2 Application of Novel Renal Safety Markers to PreclinicalDecision Making 183

9.4.3 Technological Aspects 184

9.5 Summary and Perspectives 185

References 186

10 The Use of Renal Cell Culture for NephrotoxicityInvestigations 195
Anja Wilmes and Paul Jennings

10.1 Introduction 195

10.2 In Vitro Renal Models 196

10.2.1 Characterization 197

10.2.2 Immortalization of Primary Cells 199

10.2.3 Available Podocyte and Proximal Tubule Cell Lines 201

10.3 Stem Cells 202

10.4 Optimal Cell Culture Conditions 206

10.5 In Vitro Nephrotoxicity Assessment 208

10.6 Outlook 209

References 210

11 The Zebrafish Model in Toxicology 217
Natalie Mesens

11.1 The Need for a Physiologically Relevant Organ Model in DrugToxicity Testing 217

11.2 Extensive Knowledge about Genetics, Development, andPhysiology of D. rerio 219

11.3 Studies of Specific Organ Toxicities in Zebrafish Embryosand Larvae 220

11.3.1 Cardiotoxicity 220

11.3.2 Neurotoxicity 221

11.3.3 Hepatotoxicity 222

11.3.4 Teratogenicity 226

11.3.5 Future Directions: ADME Studies and Future ExplorativeResearch 231

References 234

12 Predictive Method Development: Challenges for Cosmeticsand Genotoxicity as a Case Study 241
Gladys Ouédraogo, Fabrice Nesslany, Sophie Simar, SmailTalahari, Doris Lagache, Eric Vercauteren, Lauren Nakab, AstridMayoux, Brigitte Faquet, and Nicole Flamand

12.1 Introduction 241

12.2 The Toolbox of Predictive Methods 243

12.2.1 In Silico Tools 243

12.2.2 Biochemical (In Chemico) Assays 244

12.2.3 In Vitro 2D Assays 245

12.2.4 Organotypic Models 246

12.3 Genotoxicity as a Case Study 246

12.3.1 Materials and Methods 248

12.3.2 Chemicals 250

12.3.3 Treatment Schedules 250

12.3.4 Results 257

12.4 The Way Forward: Combining In Silico and In Vitro Tools268

Abbreviations 269

References 270

13 Using Pluripotent Stem Cells and Their Progeny as an InVitro Model to Assess (Developmental) Neurotoxicity 279
Lisa Hoelting, Marcel Leist, and Luc Stoppini

13.1 Introduction 279

13.2 Neurodevelopment In Vivo 281

13.3 Main Principle of In Vitro Test Systems to Model DNT283

13.4 Requirements of an In Vitro Test System for DNT/NT 284

13.5 Modeling of Disease and Toxicant–Induced Damage 291

13.6 Using Stem Cells to Assess (Developmental) Neurotoxicity296

13.6.1 Proliferation and Cell Death 296

13.6.2 Differentiation 297

13.6.3 Migration 298

13.6.4 Neuritogenesis 299

13.6.5 Synaptogenesis and Neuronal Excitability 300

13.6.6 Myelination 302

13.6.7 Neuroinflammation 302

13.7 Limitations 303

References 304

14 Stem Cell–Based Methods for Identifying DevelopmentalToxicity Potential 321
Jessica A. Palmer, Robert E. Burrier, Laura A. Egnash, andElizabeth L.R. Donley

14.1 Introduction 321

14.2 Developmental Toxicity Screening: Past and Present 321

14.2.1 Definition and Scope of the Problem 321

14.2.2 Historical Strategies and the Need for New Human–BasedModels 323

14.3 Pluripotent Stem Cells 324

14.3.1 Definition 324

14.3.2 Ethical Considerations 325

14.4 Metabolomics 326

14.4.1 Definition 326

14.4.2 Methods 326

14.4.3 Untargeted versus Targeted Metabolomic Approaches 328

14.4.4 Metabolomics in Toxicology 329

14.5 Stem Cell–Based In Vitro Screens for Developmental ToxicityTesting 331

14.5.1 Mouse Embryonic Stem Cell Test 331

14.5.2 Human Embryonic Stem Cell–Based Developmental ToxicityTests 332

14.5.3 Combining Human Embryonic Stem Cells and Metabolomics: APowerful Tool for Developmental Toxicity Testing 333

14.5.4 Drawbacks of In Vitro Models 337

14.6 Summary 338

References 339

15 Immunogenicity of Protein Therapeutics: Risk Assessmentand Risk Mitigation 347
Harald Kropshofer

15.1 Introduction 347

15.2 The Central Role of CD4+ T Cells 349

15.3 Generation of T–Cell Epitopes 350

15.3.1 HLA Restriction 350

15.3.2 T–Cell Epitopes Controlling Immunogenicity 352

15.4 Tolerance to Therapeutic Drugs 352

15.5 Tool Set for Immunogenicity Risk Assessment 353

15.5.1 Epitope Determination 353

15.5.2 HLA Binding Assays 354

15.5.3 T–Cell Activation Assays 355

15.5.4 Mouse Models 357

15.5.5 Case Studies 358

15.6 Immunogenicity Risk Mitigation 359

15.6.1 Deimmunization 360

15.6.2 Tolerization 360

15.6.3 Clinical Control of Immunogenicity Risk Factors 361

15.7 The Integrated Strategy of Risk Minimization 361

15.8 Summary 363

References 364

16 Regulatory Aspects 369
Beatriz Silva Lima

16.1 The History of Medicines Regulations in Brief 369

16.1.1 United States of America 369

16.1.2 Europe 370

16.1.3 The International Conference on Harmonisation 371

16.2 Impact on Drug Success of the Current ICH NonclinicalTesting Paradigm 373

16.3 Actions Taken for Increasing the Drug Development Success374

16.4 Innovative Drugs: Impact on Nonclinical DevelopmentStrategies 376

16.4.1 Biopharmaceuticals 376

16.4.2 Advanced Therapy Medicinal Products 377

16.4.3 Nanopharmaceuticals 379

16.4.4 Biosimilar Medicinal Products 380

16.4.5 Innovative Small Chemical Entities 380

16.5 Envisaging a Paradigm Change 381

16.5.1 The Present 381

16.5.2 The Basis for a Paradigm Change 382

16.5.3 Vision of a Renewed Paradigm 385

16.6 Regulatory Actions Needed to Shift the Animal–BasedParadigm 386

References 388

Index 391

Friedlieb Pfannkuch graduated as a physician from the Free University of Berlin, Germany and is Professor at the University of Basel, Switzerland. He has more than 27 years of experience in non–clinical safety assessment for all phases of drug development. During his career he was head of experimental toxicology at Ciba–Geigy in Basel, head of the non–clinical safety section at Yamanouchi Europe in the Netherlands, responsible for non–clinical nutrition safety at Roche Vitamins, and from 2003 until his retirement in 2011 he was a senior scientist in the global non–clinical drug safety department of F. Hoffmann–La Roche in Basel. He has contributed to international pharmaceutical consortia, such as toxicity testing of alternatives to CFCs propellants – IPACT, the ILSI task force on Food Safety in Europe and to working groups of the International Conference on Harmonization – ICH. IN the period from 2004–2009 he as the responsible manager of the European Commission′s Research Framework Program 6 Project InnoMed: "Predictive Toxicology – PredTox".

Laura Suter–Dick graduated as a biologist from the University of Buenos Aires (Argentina) and subsequently received her PhD from the Free University of Berlin (Germany). She has nearly 20 years of experience within the pharmaceutical industry, mainly in the field of toxicology. During her career in the pharmaceutical industry she worked as a scientist in the reproductive toxicology at Sandoz in Basel. She specialized in molecular toxicology (toxicogenomics) and in vitro assays at F. Hoffmann– La Roche Ltd., where she led the mechanistic toxicology. She has recently been appointed Professor for Molecular Toxicology at the Life Sciences School of the University of Applied Sciences and Arts Northwestern Switzerland. She acts as an external expert in several scientific panels and is also a Board Member of ESTIV (European Society of Toxicology in vitro).

This book is a sensible investment and recommended as a "must read" for toxicologists and pharmacologists to get a thorough understanding of the major challenges currently faced in realizing the objective of protecting human health using predictive toxicology.   (BTS Newsletter, 1 March 2015)