Main description:

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.

Contents:

List of Contributors XV Preface XXI A Personal Foreword XXIII 1 Introduction to Predictive Toxicology Tools and Methods 1 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 Risk Assessment 7 1.7.3 Use of Human-Derived Cellular Systems 8 1.7.4 General Acceptance Translation into Guidelines 8 1.8 Research Initiative/Collaborations 9 1.9 Concluding Remarks 9 References 9 2 In Silico Toxicology Current Approaches and Future Perspectives to Predict Toxic Effects with Computational Tools 11 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 Biological Interpretations 47 3.7 Data Management 48 References 51 4 Role of Modeling and Simulation in Toxicology Prediction 53 Antje-Christine Walz, Hans Peter Grimm, Christophe Meille, Antonello Caruso, Neil Parrott, and Thierry Lave 4.1 Introduction 53 4.2 The Need to Bring PK and PD in Predictive Models Together 54 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 Therapeutic Window 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/No Go Decisions 63 4.6 Entry-into-Human Preparation and Translational PK/PD Modeling 65 4.6.1 Selection of Safe and Pharmacologically Active Dose for Anticancer Drugs 65 4.6.2 PK/PD for Toxicology Study Design and Evaluation 67 4.7 Justification of Starting Dose, Calculation of Safety Margins, 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 and Kidney 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 Microarrays 75 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 of Hepatotoxicity 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 of Hepatocarcinogens 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-Term Treatment with Rodent Hepatocarcinogens 99 6.2.2 Approaches for Prediction of Potential Hepatocarcinogens Based on Gene Expression Profiling 104 6.2.3 Recent Developments: Transcriptional Benchmark Dose Modeling 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 for Biomarker 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 for Hazard 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 and Xenobiotic 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, and Next-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: Novel Markers of Drug-Induced Kidney Injury 171 Angela Mally 9.1 Need and Search for Novel Biomarkers of Kidney Injury 171 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 Novel Urinary Biomarkers for the Detection and Prediction of Acute Kidney Injury 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 in Preclinical Safety Assessment 182 9.4.1 Biomarker Qualification and Regulatory Acceptance 182 9.4.2 Application of Novel Renal Safety Markers to Preclinical Decision Making 183 9.4.3 Technological Aspects 184 9.5 Summary and Perspectives 185 References 186 10 The Use of Renal Cell Culture for Nephrotoxicity Investigations 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 Drug Toxicity Testing 217 11.2 Extensive Knowledge about Genetics, Development, and Physiology of D. rerio 219 11.3 Studies of Specific Organ Toxicities in Zebrafish Embryos and 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 Explorative Research 231 References 234 12 Predictive Method Development: Challenges for Cosmetics and Genotoxicity as a Case Study 241 Gladys Ouedraogo, Fabrice Nesslany, Sophie Simar, Smail Talahari, Doris Lagache, Eric Vercauteren, Lauren Nakab, Astrid Mayoux, 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 Tools 268 Abbreviations 269 References 270 13 Using Pluripotent Stem Cells and Their Progeny as an In Vitro 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 DNT 283 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) Neurotoxicity 296 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 Developmental Toxicity Potential 321 Jessica A. Palmer, Robert E. Burrier, Laura A. Egnash, and Elizabeth 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-Based Models 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 Toxicity Testing 331 14.5.1 Mouse Embryonic Stem Cell Test 331 14.5.2 Human Embryonic Stem Cell-Based Developmental Toxicity Tests 332 14.5.3 Combining Human Embryonic Stem Cells and Metabolomics: A Powerful 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 Assessment and 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 Nonclinical Testing Paradigm 373 16.3 Actions Taken for Increasing the Drug Development Success 374 16.4 Innovative Drugs: Impact on Nonclinical Development Strategies 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-Based Paradigm 386 References 388 Index 391