Early Stage Drug Safety Strategies and Risk
Management: Maximizing opportunities towards achieving clinical success. Executive Summary 10

Introduction 10

Modeling and simulation in drug discovery 11
Novel in vitro technologies for predictive safety testing 12
Novel in vivo methods in for non-clinical safety assessment 12
Current initiatives in preclinical drug safety 13
Strategies to improve safety evaluation in early clinical development 14
Challenges and cost saving opportunities 16


Chapter 1 Introduction 18

Summary 18
State of the industry 19
Drug attrition 20
Innovation in drug safety 21
Report outline 28


Chapter 2 Modeling and simulation in drug discovery 32

Summary 32
Introduction 33
Molecular modeling 34
Structure-toxicity relationships 35
Epix Pharmaceuticals’ in silico discovery platform 37
Chemoinformatic methods 38
Collaborative projects 41
Biosimulation 42
Virtual models of whole organs 43
Conclusions 45


Chapter 3 Novel in vitro technologies for predictive safety testing 48

Summary 48
Introduction 49
Toxicogenomics and systems biology 50
Commercial platforms 53
Cell-based assays 56
Stem cells 61
Conclusions 65


Chapter 4 Novel in vivo methods in for nonclinical safety assessment 68

Summary 68
Introduction 69
Zebrafish 70
Whole animal imaging and microscopy 73
Humanized rodent models 79
Conclusions 80


Chapter 5 Current initiatives in preclinical drug safety 84

Summary 84
Introduction 85
The Predictive Safety Testing Consortium 86
The International Life Sciences – Health and Environmental Sciences
Institute 88
The InnoMed PredTox project 89
The Innovative Medicines Initiative 92
Additional consortia 93
The Chemical Effects in Biological Systems Database 93
The Japanese Toxicogenomics Project 93
Liver Toxicity Biomarker Study 94
Consortium for Metabonomic Toxicology 94
Other European funded initiatives 95
ACuteTox 95
Reprotec 96
Predictomics 96
CarcinoGenomics 97
Conclusions 97


Chapter 6 Strategies to improve safety evaluation in early clinical development 100

Summary 100
Introduction 101
Exploratory clinical trials 102
Other applications of AMS 106
Industry uptake 108
Regulatory status 108
The future for AMS-based studies 109
Technologies 109
Linking pharmacology data to microdose studies 109
Improving safety evaluation in Phase 1 110
Biomarkers in Phase 1 clinical trials 110
Pharmacogenomics and rare, idiosyncratic adverse events 115
Pharmacometrics – modeling and simulation to improve Phase 1 safety 116
Optimizing early clinical trial design 119
QT in Phase 1 121
The Thorough QT Study 121
Timing of the TQT study 124
Intensive QT studies in early Phase 1 124
Costs and decision making 125
Conclusions 125


Chapter 7 Challenges and cost saving opportunities 128

Summary 128
Introduction 129
Implementation of new technologies 129
New technologies, new risks 132
Qualifying biomarkers 133
Translational medicine 135
‘Fail early, fail often’ 136
Conclusions 141


Chapter 8 Appendix 142


Primary research methodology 142
Acknowledgments 143
Index 144
Glossary 145
Glossary 145
Bibliography 148
Endnotes 153


List of Figures

Figure 1.1: Pharma industry productivity decline (1995-2007) 19
Figure 1.2: Reasons for drug attrition 24
Figure 1.3: The place of innovative safety evaluation strategies in drug discovery and development 25
Figure 1.4: Serious adverse events: research priorities 26
Figure 2.5: In silico methods contribute to the earliest stages of drug discovery 33
Figure 2.6: The Safety Intelligence Program from BioWisdom 39
Figure 2.7: Examples of assertions in the Safety Intelligence Program from BioWisdom 40
Figure 3.8: Novel in vitro methods and their use in drug discovery and development 50
Figure 3.9: A typical toxicogenomics workflow in the pharma industry 52
Figure 4.10: Novel in vivo methods and their use in drug discovery and development 70
Figure 4.11: Whole body microPET images through a rat showing 18F-FDG distribution 75
Figure 5.12: Study design and investigations used in the InnoMed PredTox project 90
Figure 6.13: The ‘learn and confirm’ model of drug development 101
Figure 6.14: The place of innovative technologies in early clinical safety assessment 102
Figure 6.15: Comparison of midazolam pharmacokinetics at microdose and therapeutic dose levels in the CREAM study 105
Figure 6.16: Proposed decision tree for integration of pharmacogenetic studies in early drug development 115
Figure 6.17: Information utilized in model-based drug development 118
Figure 6.18: Key attributes of a thorough QT study 123
Figure 7.19: Success rate improvements from increasing investment in technologies for early safety prediction 139


List of Tables

Table 1.1: Failure rates at each stage of clinical drug development 20
Table 1.2: Drugs withdrawn from the market in the US between 1998 and April 2008 21
Table 3.3: Examples of companies providing platforms for toxicogenomics 53
Table 3.4: Examples of companies offering integrated software suites for the analysis of toxicogenomic data 55
Table 3.5: Examples of contract laboratories offering HCA cytotoxicity screening 59
Table 3.6: Examples of companies offering stem cells for toxicity testing 63
Table 4.7: Advantages and disadvantages of zebrafish for toxicity screening 71
Table 4.8: Companies offering zebrafish toxicity screening products and services 72
Table 4.9: Advantages of molecular imaging of whole animals for preclinical studies 76
Table 4.10: Manufacturers of molecular imaging equipment and probes 77
Table 4.11: Companies developing transgenic models for ADMET testing 79
Table 5.12: Biomarker candidates identified by the InnoMed PredTox project 91
Table 6.13: Companies offering AMS services 103
Table 6.14: Advantages and disadvantages of AMS-based microdosing studies 104
Table 6.15: Advantages and disadvantages of using AMS for mass balance and absolute bioavailability studies 107
Table 6.16: Core list of validated genomic biomarkers involved in ADME 112
Table 6.17: Examples of valid genomic biomarkers in drug labels 113
Table 6.18: Pharmacometric consultancies 119
Table 7.19: Definitions and examples of safety biomarkers with different levels of qualification134
Table 7.20: Success rate improvements from increasing investment in technologies for early safety prediction 137
Table 7.21: Success rate improvements from increasing investment in technologies for early safety prediction 140