Table of Contents for Commercial Opps from Biomarkers: Transforming drug discovery, clinical dev. & molecular diag.
Executive Summary 12
Biomarkers in drug discovery, development and clinical diagnostics 12
Regulatory acceptance of biomarkers now and in the future 13
Fishing for new drug targets with biomarkers 14
Biomarkers aiding go/no go decisions 15
Imaging biomarkers directing clinical dosing studies 16
Clinical biomarkers improving trial design 17
Biomarkers as surrogate endpoints 18
Market size, collaborations and future directions 19
Chapter 1 Biomarkers in drug discovery,
development and clinical
diagnostics 22
Summary 22
Introduction 23
The role of biomarkers in drug discovery, preclinical, clinical
development and diagnostics 24
Biomarkers in the drug discovery process 26
Safety/toxicology biomarkers 27
Efficacy or outcome biomarkers and surrogate endpoints 27
Biomarkers: challenges and opportunities 28
Chapter 2 Regulatory acceptance of
biomarkers now and in the future 32
Summary 32
Introduction 33
The critical path initiative and FDA guidance 33
Regulatory guidance from the other major markets 36
Europe - the European Medicines Agency (EMEA) 36
Japan – the Ministry of Health and Welfare (MHLW) 37
Regulatory agencies working together 37
Other biomarker initiatives 38
Regulatory acceptance of a valid biomarker 39
Regulatory acceptance of
in vitro diagnostic biomarkers 43Costs and incentives for biomarker development and validation 44
Conclusions 46
Chapter 3 Fishing for new drug targets with
biomarkers 48
Summary 48
Introduction 49
Target discovery via functional genomics 50
What is functional genomics? 50
Target discovery 51
New technologies in functional genomics 52
DNA and protein microarrays 53
New technologies 54
The genomics-derived drug pipeline 55
Case study – target discovery by CuraGen Corporation 56
The future of genomics technologies for drug target identification 57
Biomarker discovery via proteomics 57
What is proteomics? 57
Proteomics in biomarker development: the HUPO Project 60
Case studies - Biomarker development using proteomic technologies 62
Caprion Pharmaceuticals Inc. case study 62
Millennium Pharmaceuticals case study 64
Limitations of proteomics for biomarker discovery 65
Integrating ‘omics in biomarker discovery: metabonomics 65
What is metabonomics? 65
Metabonomics-based biomarker discovery – case studies 68
Metabolon Inc case study 68
Phenomenone Discoveries case study 69
Limitations of metabonomics 71
Conclusions 71
Chapter 4 Biomarkers aiding go/no go
decisions 74
Summary 74
Introduction 75
Technologies for safety biomarker discovery 75
Toxicogenomics 75
Genomic biomarkers for drug-induced nephrotoxicity, genotoxicity
and neutropenia 77
Proteomic biomarkers of drug-induced hepatotoxicity and
cardiotoxicity 81
Metabonomic biomarkers for vasculitis and hepatotoxicity 82
Databases for predictive toxicogenomics 84
Privately held databases 85
Publicly held databases 88
Challenges and opportunities 89
Challenges 89
Opportunities 90
Collaboration in biomarker discovery 91
Conclusions 91
Chapter 5 Imaging biomarkers directing
clinical dosing studies 94
Summary 94
Introduction 95
Imaging biomarkers 95
X-ray and computed tomography 97
Magnetic resonance imaging 97
Novel MRI imaging agents 97
Positron emission tomography 99
Molecular imaging 101
The role of imaging biomarkers in preclinical studies 101
Bioluminescence 103
Matrix metalloproteinase inhibition 104
The role of imaging biomarkers in clinical studies 106
Phase 1: the role of imaging biomarkers in pharmacokinetic and dosing
studies 106
Receptor occupancy studies 106
PET and MRI dosing strategies for anticancer agents 107
Phase 2 and 3: imaging biomarkers as study endpoints 108
Oncology 108
Multiple sclerosis 109
Rheumatoid arthritis 110
Alzheimer’s disease 110
Go/no-go decision making 111
Case study – VirtualScopics 112
Regulatory aspects of imaging technologies 113
Development of molecular imaging agents 113
Imaging biomarkers and surrogate endpoints 113
Conclusions 114
Chapter 6 Clinical biomarkers improving
trial design 116
Summary 116
Introduction 117
Patient enrichment in clinical trials 117
Patient enrichment – advantages 119
Patient enrichment – potential problems 119
Targeted cancer treatments – case studies 120
Herceptin case study 121
Gleevec case study 123
Iressa case study 124
Patient enrichment via pharmacogenomics in therapeutic areas other
than cancer 127
Vilazodone – case study 129
Pharmacogenomic testing in the pharmaceutical industry – an update 130
Conclusions 131
Chapter 7 Biomarkers as surrogate
endpoints 134
Summary 134
Introduction 135
What is a surrogate endpoint? 136
Benefits and drawbacks of surrogate endpoints 137
Benefits 137
Drawbacks 138
Surrogate endpoint validation 139
Effective use of surrogates and examples 141
Case study – FDG-PET as a surrogate endpoint in oncology studies 143
CA-125 as a surrogate endpoint in trials of ovarian cancer 144
Costs of surrogate endpoint development 146
Regulatory perspective on surrogate endpoints 146
Conclusions 147
Chapter 8 Market size, collaborations and
future directions 150
Summary 150
Introduction 151
The biomarker market 151
Potential cost savings in drug discovery and development 151
Market size 153
Genomics and proteomics 154
Metabonomics 155
Bioinformatics 155
Imaging 156
Molecular diagnostics 156
Companies and their alliances in the biomarker field 157
Outline of key companies 157
Key alliances 161
Alliances with pharmaceutical companies 161
Biomarker-diagnostic company alliances 165
Alliances with academia 166
Pharma strategies for biomarkers 167
Current and future trends for the evaluation of disease biomarkers 169
Conclusions 171
Chapter 9 Appendix 174
Biomarker discovery collaborations 174
Bibliography 181
Glossary 192
Index 196
Footnotes 198
List of Figures
Figure 1.1: Types of biomarker and examples 24
Figure 1.2: Low success rate of developmental drugs 25
Figure 1.3: The many roles of biomarkers in drug development 26
Figure 2.4: Voluntary genomic data submissions: process and outcomes 35
Figure 2.5: The EMEA and FDA working together 37
Figure 2.6: Valid DNA based biomarkers of enzyme activity 40
Figure 2.7: Exploratory DNA based biomarkers of enzyme or transporter activity 41
Figure 2.8: Fit-for-purpose qualification of biomarkers 42
Figure 2.9: Proposed biomarker validation in preclinical drug safety assessment 43
Figure 3.10: Genomics, proteomics and metabonomics: what is measured? 49
Figure 3.11: Technologies and methods used in biomarker discovery 50
Figure 3.12: A timeline for the introduction of various genomics technologies 53
Figure 3.13: The branches of proteomics for biomarker discovery 58
Figure 3.14: Scientific initiatives in the Human Proteome Organisation 60
Figure 3.15: CellCarta®: uses for proteomic analysis 63
Figure 3.16: An NMR metabonomic profile of urine 67
Figure 3.17: Metabonomic analysis of data from patients with ALS and controls 68
Figure 3.18: Biomarker discovery through metabolomics 70
Figure 4.19: Toxicogenomics and traditional toxicology working together to provide a framework for systems toxicology 76
Figure 4.20: Principal component analysis of gene expression changes following treatment with cisplatin, gentamicin and puromycin 78
Figure 4.21: Principal component analysis of urine from rats treated with a vasculitis causing compound 82
Figure 4.22: Database enabled predictive toxicology 84
Figure 4.23: Example of rank ordering candidate leads using the ToxExpress® Program 87
Figure 5.24: Imaging techniques and their uses 96
Figure 5.25: Targeted MRI imaging agents from Kereos Inc. 98
Figure 5.26: A PET/CT image indicating the uptake of 18F-fluoro-2-deoxy-D-glucose in a primary cancer lesion and a lymph node (orange areas) 99
Figure 5.27: Whole body microPET images through a rat showing 18F-FDG distribution 102
Figure 5.28: The VivoVision technology from Xenogen Inc. 104
Figure 5.29: NIRF data from rats treated with prinomastat 105
Figure 5.30: PET images of the serotonin 5-HT1A¬ receptors in the brain of a healthy volunteer before and after administration of pindolol 107
Figure 5.31: An MRI from a multiple sclerosis patient showing a T2 lesion 109
Figure 5.32: VirtualScopics’ method for tumor growth measurement 112
Figure 6.33: Targeted study designs 118
Figure 6.34: Imatinib mechanism of action in chronic myeloid leukaemia 123
Figure 6.35: Mechanism of action of gefinitib 125
Figure 6.36: Frequency of mutations by exon (EGFR tyrosine kinase domain) 126
Figure 6.37: The association between patients’ alleles for the serotonin transporter long/short polymorphism and response to SSRIs 129
Figure 7.38: Examples of biomarkers that have failed to serve as surrogate endpoints in clinical trials 138
Figure 7.39: Reasons for surrogate endpoint ‘failure’ 140
Figure 7.40: Use of surrogate endpoints in antiretroviral approvals 142
Figure 8.41: Potential cost savings from the use of genomic biomarkers in drug discovery and development 153
Figure 8.42: Alliances between major pharmaceutical and biomarker discovery companies 162
Figure 8.43: Therapeutic areas represented by the major alliances of biomarker and pharmaceutical companies 165
Figure 8.44: Therapeutic areas represented by biomarker patents 169
Figure 8.45: Cancers represented by biomarker patents 170
Figure 8.46: Estimated time to the widespread use of biomarkers in different therapeutic areas 171
List of Tables
Table 3.1: Investments by pharmaceutical companies in genomics companies 52
Table 3.2: Highlights of drug discovery and development based on genomics technologies 55
Table 3.3: Companies predominantly using genomic and proteomic technologies for drug development 62
Table 4.4: Types of toxicogenomic biomarker 77
Table 4.5: Drugs extensively metabolized by CYP2C19 and CYP2D6 80
Table 5.6: Glucose-based imaging biomarkers for a variety of diseases 100
Table 5.7: Advantages of molecular imaging of whole animals for preclinical studies 103
Table 6.8: Comparison of targeted and untargeted study designs 118
Table 6.9: List of targeted cancer treatments 120
Table 6.10: Phase 3 trial outcome for Herceptin with and without HER2 diagnosis 122
Table 6.11: Examples of pharmacogenomic developments in therapeutic areas other than cancer 127
Table 6.12: Approval success rates for different therapeutic drug classes 128
Table 6.13: Currently marketed drugs that might benefit from pharmacogenomics 128
Table 7.14: Examples of surrogate endpoints and related clinical outcomes 136
Table 7.15: Sample size for Alzheimer’s disease clinical trials using volumetric MRI measures as a surrogate endpoint 137
Table 7.16: Uses of CA-125 in routine clinical care 144
Table 8.17: Biomarker market size and forecast ($bn), 2005-2012 154
Table 8.18: Molecular diagnostics market size and forecast ($bn), 2005-2012 157
Table 8.19: Genomics-based biomarker discovery companies 158
Table 8.20: Proteomics-based biomarker discovery companies 159
Table 8.21: Metabonomics-based biomarker discovery companies 160
Table 8.22: Bioinformatics companies in biomarker discovery 160
Table 8.23: Summary of major pharmaceutical company biomarker alliances 164
Table 8.24: Key diagnostic-biomarker company alliances 166
Table 8.25: Number of patents filed by various pharma and biomarker discovery companies 168
Table 9.26: Biomarker discovery collaborations with major pharma 174
Table 9.27: Biomarker discovery collaborations with major pharma (cont.) 175
Table 9.28: Biomarker discovery collaborations with major pharma (cont.) 176
Table 9.29: Biomarker discovery collaborations with smaller pharma or biotechnology companies 177
Table 9.30: Biomarker discovery collaborations with smaller pharma or biotechnology companies (cont.) 178
Table 9.31: Biomarker discovery alliances with academia 179
Table 9.32: Biomarker discovery alliances with academia (cont.) 180
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