Companion Biomarkers in Drug Development

NEW YORK, Aug. 19, 2013 /PRNewswire/ -- Reportlinker.com announces that a new market research report is available in its catalogue:

Companion Biomarkers in Drug Development
http://www.reportlinker.com/p0115524/Companion-Biomarkers-in-Drug-Development.html#utm_source=prnewswire&utm_medium=pr&utm_campaign=Genomics

Companion biomarkers are diagnostic tests that are specifically linked to a therapeutic drug either during its development or in the clinic. This linkage can be an important component of the drug development process; alternatively, the companion biomarker can be useful in ameliorating the regulatory process for the drug, or acting as an aid to therapeutic use in the clinic. Market opportunities for companion biomarkers are focused in drug development targets, drug development efficacy and clinical end points in four main therapeutic areas: oncology, cardiovascular, neurology and autoimmune.

Using companion biomarkers yields safer and more efficacious drug products, reduces clinical trial and development costs, improves post-marketing safety profiles and salvages therapies that otherwise would not be granted approval. This TriMark Publications report focuses on the role of companion diagnostic tests in drug development. It provides an in-depth discussion and analysis of the application of companion biomarkers to drug development and targeted therapeutics, as well as their use in clinical trials and the regulatory forum. The examination emphasizes new and developing technology platforms meant to aid in development of drugs for therapeutic use, and sometimes to be available as companion tests for these drugs in the clinic.

This report also examines companies that are actively developing and marketing companion biomarkers around the world. Detailed tables and charts with sales forecasts and marketshare data are also included.

1. Overview 16

1.1 Statement of Report 16
1.2 About This Report 16
1.3 Scope of the Report 16
1.4 Objectives 16
1.5 Methodology 18
1.6 Executive Summary 19

2. Introduction: Companion Diagnostics in Drug Development 25

2.1 Companion Diagnostics as Biomarkers 26
2.1.1 Potential Benefits of Biomarkers as Companion Diagnostics 28
2.2 Biomarkers in Different Phases of Drug Development 28
2.2.1 Drug Discovery and Development Process 28
2.2.2 Biomarkers in Drug Development 30
2.3 Drug Targets 31
2.3.1 Target Discovery Using Functional Genomics 34
2.3.2 Functional Genomics 35
2.3.3 Target Validation 36
2.3.3.1 Target Discovery 37
2.3.3.2 Lead Identification 37
2.3.4 Target and Biomarker Discovery 37
2.3.4.1 Biomarker Validation 38
2.4 Biomarkers in Drug Discovery, Development and Clinical Diagnostics 38
2.4.1 Role of Biomarkers in Drug Discovery, Preclinical, Clinical Development and Diagnostics 38
2.4.2 The Pipeline Problem 40
2.4.3 Biomarkers in the Drug Discovery Process 41
2.4.4 Segmentation of Biomarker Usage 42
2.4.5 Efficacy of Biomarkers as Surrogate Endpoints 42
2.4.6 Biomarkers Used to Reduce the Cost of Drug Development 43
2.4.7 Biomarkers: Challenges and Opportunities 43
2.4.8 Biomarkers in Early Safety and Toxicity Assessment 44
2.4.9 Biomarkers in Determining Validation Parameters 44
2.4.10 Challenges in Development of Biomarkers 45

2.4.11 Using Biomarkers in Early Clinical Development 45
2.4.12 Translational Biomarkers 45
2.4.13 Use of Biomarkers in "Go"/No-Go" Decisions 46
2.4.14 Diagnostic Tests 46
2.4.15 Biomarkers in Deal Making 46
2.4.16 Payors Use Biomarkers in Decision-Making 47
2.5 World Pharmaceutical Markets 47
2.5.1 World Market Summary 47
2.5.2 Forces Affecting the Structure of the Pharmaceutical Industry 51
2.5.2.1 Threats 52
2.5.2.2 Competitive Forces 52
2.6 Companion Diagnostics Market Opportunity 53
2.6.1 Industry Overview 53

2.6.1.1 Pharmaceutical Industry Drug Pipeline 54
2.6.1.2 Asia-Pacific to Replace U.S. and Europe as Pharmaceutical Industry Center 64
2.6.1.3 The Changing Pharmaceutical Business Model 65
2.6.2 Benefits for Companion Diagnostic Tests in Drug Development 65
2.6.3 Strategies for the Creation of Partnerships—Predicting and Overcoming Challenges in Creating Drug Response Profiling Diagnostics 67
2.6.4 Options and Applications 68
2.6.4.1 Clinical Applications of Genomics: The Use of Evidence Based Frameworks by Decision-Makers 68
2.6.5 Challenges, Drivers and Trends 68
2.6.5.1 Macro Trends in Biomarkers 69
2.6.5.2 Biomarkers: Industry SWOT Analysis 72
2.6.6 Collaboration for Companion Diagnostics 72
2.6.7 Key Stake Holders in Companion Diagnostics 73
2.7 Impact of CDx/PM on Drug Clinical Trials 75
2.8 Evolving business models in Companion Dx and Personalized Medicine. 76
2.9 Current Pharm/Dx Business Model Examples 76
2.10 Future Developments 76

3. Biomarker Development Tools 78

3.1 New Technologies in Functional Genomics 78
3.1.1 Genomics-Derived Drug Pipeline 78
3.1.2 Future of Genomics Technologies for Drug Target Identification 78
3.2 Overview of Microarrays 79
3.2.1 General Theory of Microarrays 80
3.2.2 GeneChip Probe Array Technology 81
3.2.3 DNA Microarrays 81

3.2.3.1 DNA Microarray Market Size 83
3.2.3.2 DNA Microarrays in SNP Analysis 84
3.2.3.3 DNA Microarrays in Cancer 85
3.2.4 Protein Microarrays 85
3.2.4.1 Reasons Why Researchers Use Protein Microarrays 86
3.2.4.2 Factors for Adoption of Protein Microarrays Technology 87
3.2.4.3 Future Innovations in Protein Microarray Technology 87
3.2.5 New Technologies 87
3.2.5.1 Antibody Microarrays 87
3.2.5.2 Peptide Microarrays 88
3.2.5.3 Peptide MHC Microarrays 88
3.2.5.4 Tissue Microarrays 88
3.2.5.5 Key Points for Developing Microarray Based Applications 89
3.2.5.6 Reasons Why Researchers use DNA Microarrays 89
3.2.5.7 Factors for Difficulties Applying DNA Microarrays Technology 90
3.2.5.8 Emerging Microarray Trends 91
3.2.5.9 Emerging Microarray Applications 91
3.2.5.10 Key Findings on Use of Microarrays 92
3.2.5.11 Advantages and Drivers of Microarrays 92
3.2.5.12 Limitations and Barriers to Use of Microarrays 94
3.2.5.13 qRT-PCR Use in Biomarker Identification and Drug Development 96
3.2.5.14 Microarray Quality Control (MAQC) Project 97

3.3 Theranostics 97
3.3.1 Theranostics in Drug Development 97
3.3.2 Trends in Theranostics 97
3.3.3 Timeline for Impact on Various Segments in Theranostics 98
3.3.4 Challenges for Biomarker Based Therapeutics Development 99
3.4 Pharmaceutical Development and Bioanalytical Services 100
3.4.1 Wyeth (now part of Pfizer) Singulex's Erenna 101
3.5 Metabolomics in Drug Discovery 101
3.6 Bioinformatics 102
3.6.1 Definition and Role of Bioinformatics 103
3.6.2 Bioinformatics Sector Overview 105
3.6.3 Future Status of Bioinformatics 106
3.6.3.1 Future in Drug Discovery 106
3.6.3.2 Mergers and Acquisitions Could Deter Bioinformatics Growth 106
3.6.3.3 Barriers to Bioinformatics Growth 106
3.6.3.4 Types of Data and Bioinformatics Applications 106
3.6.3.5 Validated Core Modeling Technology 108
3.6.3.6 Applicability of Bioinformatics for Biomarker Discovery 108
3.6.3.7 Biomarker Data Management Compliant with Industry Standards 108
3.6.3.8 Data Management for Biomarkers 108
3.6.3.8.1 Data Transformation for Biomarker Development 108
3.6.3.8.2 Biomarker Data Collaboration 108

3.6.3.8.3 Interface for Online Data Sources for Genomic Structures 109
3.6.3.8.4 Target Markets for Informatics Software 109
3.6.3.8.5 Bioinformatics Drivers and Challenges in the Pharmaceutical Industry 110
3.6.3.8.6 Products of Bioinformatics 112
3.6.3.8.7 Informatics Tools and Functionalities 113
3.6.3.8.8 Bioinformatics in Lead Identification and Optimization 114
3.6.3.8.9 Bioinformatics in Drug Development and Formulation 114
3.6.3.8.10 Role of Bioinformatics in the Drug Discovery Value Chain 114
3.6.3.8.11 Bioinformatics Software for Drug Discovery and Biomarker Development 115
3.6.3.8.12 Bioinformatics Services 116
3.7 Biomarkers and Proteomics 117
3.7.1 Scientific Background 118
3.7.2 Applying Proteomics to Biomarker Discovery 118
3.7.2.1 Challenges Facing Biomarker Developers 119
3.7.3 Limitations of Proteomic Approaches to Biomarker Discovery 121
3.7.4 Validation of Biomarkers Using LC-MS/MS Systems 121
3.7.5 Use of Mass Spectrometry in Biomarker Discovery 122
3.7.5.1 Multiple Reaction Monitoring Assays (MRMs) 123
3.7.5.2 Gel-based Approaches 123
3.7.5.3 Non-Gel-based Approaches 123
3.7.5.4 SELDI-TOF MS 123
3.7.5.5 SELDI and Prognosis 124
3.7.5.6 SELDI and Treatment Monitoring 124
3.7.5.7 Limitations of Mass Spectroscopy 125
3.7.6 Partnerships for Developing Proteomic Biomarkers 126
3.7.7 Proteomics in Developing a New Cancer Marker 127
3.7.7.1 Translating Proteomic Oncology Discoveries to the Clinic: Development of Analytical Reference Materials, Reagents, Data, and Technology Assessment and Validation 127

3.7.7.2 Challenges of Discovering and Validating Clinical Protein Biomarkers 128
3.7.7.3 Importance of Proteomics in Biomarker Discovery 128
3.8 Toxicogenomics 128
3.8.1 Toxicogenomics Concerns in Drug Safety Data 129
3.8.2 Toxicogenomics and Prioritization of Drug Candidates 129
3.8.3 Genomic Biomarkers for Drug-Induced Nephrotoxicity 130
3.8.4 Use of Biomarkers of Drug-Induced Cardiotoxicity 130
3.8.5 Use of Biomarkers of Drug-induced Hepatotoxicity 130
3.8.6 Transgenic Biomarkers for Adverse Drug-Drug Interactions 130
3.8.7 Challenges to Toxicogenomics 130
3.8.8 The Future Use of Toxicogenomics in Drug Discovery 131

4. Market for Biomarkers in Drug Development 132

4.1 C-KIT (CD117) Expression 136
4.2 CCR5 -Chemokine C-C Motif Receptor 136
4.3 CYP2C19 Variants 136
4.4 CYP2C9 Variants 137
4.5 CYP2D6 Variants 137
4.6 CYP2D6 Variants with Alternate Context 137
4.7 Clinical Biomarkers 138
4.8 Targeting Kidney Toxicity 138
4.8.1 Proximal and Distal Tubular Injury (Alpha-GST and Pi-GST) 139
4.8.2 Collecting Duct and Loop of Henle Injury (RPA-1 and RPA-2) 139
4.8.3 Glomerular Injury (Collagen IV) 139
4.8.4 KIM-1 140
4.9 Targeting Hepatotoxicity 140
4.9.1 Breast Cancer 141
4.9.2 Colorectal Cancer 142
4.9.3 Prostate Cancer 142
4.9.4 Cystic Fibrosis 142

4.10 Biomarker Application in Oncology Clinical Development 142
4.10.1 Specific Example of Companion Biomarkers in Clinical Oncology 148
4.10.2 Integration of a Companion Diagnostic Strategy into Oncology Drug Development 148
4.10.2.1 Lilly to Co-Develop Companion IVDs for Cancer Drugs 148
4.10.2.2 Galena Biopharma and Leica Biosystems Announced a Partnership to Develop a Companion Diagnostic for HER2 Screening in Women with Breast Cancer 149
4.10.2.3 bioMérieux and Ipsen Sign Theragnostics Agreement to Develop Companion Test for New Breast Cancer Treatment 149
4.10.2.4 Life Technologies to Partner with Bristol-Myers Squibb for Companion Diagnostics Development 149
4.10.2.5 Ventana Medical Systems and the Critical Path Institute 149
4.10.2.6 Siemens Forms New Companion Diagnostics Partnerships with ViiV Healthcare and Tocagen 149
4.10.2.7 Biomarkers in Development 150
4.10.2.8 Epigenomics' Methylation Biomarker Septin 150
4.10.2.9 Quest Diagnostics and Lab Corp Develop IL 28-B Test for Hepatitis C 150
4.10.2.10 NSLC Patients with EGFR Mutation 150
4.10.2.11 A Personalized Medicine Program for Chronic Myeloid Leukemia 151
4.10.2 12 Clarient adopts Qiagen KRAS 151
4.11 Targeting Diabetes Related Heart Disease 151
4.12 Key Challenges and Opportunities in Developing Targeted Therapeutics 152

5. Imaging Biomarkers in Drug Discovery 153

5.1 Introduction 153
5.1.1 Validation of Imaging Biomarkers 153
5.1.2 Types of Imaging Used in Drug Development 153
5.1.3 Development of Imaging Technologies 154
5.2 Molecular Imaging 154
5.2.1 Use in Drug Discovery 154
5.2.2 Use in Clinical Applications 154
5.2.3 Use in Clinical Trials 154
5.2.4 Cell-based Screening Technologies in Drug Development 154
5.2.5 Optical Biomarkers 155
5.3 Magnetic Resonance Imaging 155
5.4 Positron Emission Tomography 155
5.5 FDG-PET Patient Phase I Studies 156
5.6 Imaging Biomarkers as Study Endpoints 157
5.6.1 Oncology 157
5.6.2 Parkinson's Disease 157
5.6.3 Cardiac Disease 157
5.7 IT Solutions for Imaging Biomarkers in Biopharmaceutical Research and Development 159

6. Clinical Biomarkers Improving Trial Design 160

6.1 Strategies to Improve the Measurement of Biomarkers for Drug Trials 160
6.2 Key Opportunities in Biomarker Discovery, Development and Commercialization 160
6.2.1 Contract Research Companies 160
6.3 What Strategies Help Translate Biomarkers from Preclinical to Clinical Development? 162
6.4 How Should Biomarker Data Be Compared to "Traditional" Safety and Efficacy Data? 162

7. Biomarkers as Surrogate Endpoints 164

7.1 What is a Surrogate Endpoint? 164
7.2 Benefits and Drawbacks of Surrogate Endpoints 164
7.2.1 Benefits 164
7.2.2 Drawbacks 164
7.3 Improving the Efficacy of Clinical Surrogate End Points Using Biomarkers 164
7.4 Surrogate Endpoint Validation 165
7.5 Effective Use of Surrogates 165
7.5.1 FDG-PET as a Surrogate Endpoint in Oncology Studies 165
7.6 Conclusions 165

8. Market Size, Collaborations and Future Directions for Companion Diagnostics in Drug Development 166

8.1 Strategies to Improve the Measurement of Biomarkers for Drug Trials 166
8.1.1 Key Opportunities in Biomarker Discovery, Development and Commercialization 166
8.1.2 The Rationale Behind Biomarker Strategy 166
8.1.3 New Development Strategies and their Implications for Deal Making 167
8.1.4 How Biomarkers are Being Used to Reduce Attrition in Development 168
8.1.5 Combined Therapeutics and Diagnostics Biomarker Business Makes Sense 168
8.1.6 Use of Biomarkers In House or Partner with a Diagnostics Company 168
8.2 What is the Best Balance of Resources to Have the Most Efficient Pathway to Develop Biomarkers? 168
8.3 Current and Future Trends in Drug Development 169
8.4 Future Role of Biomarkers in Healthcare 169
8.5 What are the Current Organizational Obstacles in Biomarker Implementation? 170

9. Regulatory Issues for Biomarkers in Drug Development 171

9.1 Introduction 171
9.1.1 Role of Regulatory Agencies in Development of Biomarkers 172
9.2 FDA Perspective of Biomarkers in Clinical Trials 173
9.2.1 FDA as a Gatekeeper of Companion Biomarkers 173
9.2.2 FDA Criteria for a Valid Biomarker 173
9.2.3 FDA Product Submission and Review Process 174
9.2.4 FDA Pipeline for Biomarker Tests 175
9.2.5 Adaptive Clinical Trial Design 175
9.2.6 Orphan Drug Act and Biomarkers: Options and Opportunities 175
9.3 Role of StaRT-PCR™ in Increasing Value of Pharmacogenomic Data 176
9.4 Supporting IND, NDA, and BLA Submissions 177
9.5 Performance Characteristics of Biomarker Tools 179
9.6 Biomarker Initiative and VGDs 181
9.7 Biomarker Qualification Pilot Process at the FDA 181
9.7.1 Introduction 181
9.7.2 Biomarker is Validity 182
9.7.3 Biomarker Qualification Process Map 182
9.7.4 Biomarker Qualification Pilot Process 183
9.7.5 The Pipeline Problem 184
9.7.6 FDA Critical Path 185
9.7.6.1 Challenge and Opportunity on the Critical Path to New Medical Products 186
9.7.6.2 The NIH Roadmap 187
9.7.6.3 Predictive Safety Testing Consortium 187
9.7.6.4 FDA Risk-based Approach 187
9.7.6.5 Examples of drugs being held up due to lack of compliance with FDA directives 187
9.7.7 Negotiating the Critical Path 187
9.7.8 Technical Dimensions along the Critical Path 188
9.7.9 Product Development Toolkit 189
9.7.10 Tools for Assessing Safety 190
9.7.11 Tools for Demonstrating Medical Utility 192
9.7.12 Tools for Manufacturing 195
9.7.13 Orphan Products Grant Program 196
9.7.14 Slowdown in New Medical Products 196
9.7.15 Factors Contributing to the Decline in New Product Applications 199
9.7.16 Factors that Cause Unnecessary Delays in New Product Approvals 201
9.7.17 Reducing Avoidable Delays in Time to Approval 202
9.7.18 Reducing Delays in Medical Device Reviews 203
9.7.19 Reducing Delays in Animal Drug Reviews 204
9.7.20 Quality Systems Approach to Medical Product Review 204
9.7.20.1 Instituting Quality Systems in Review of New Drugs and Biologics 205
9.7.20.2 Implementing of the Common Technical Document (CTD) and the electronic CTD 205
9.7.20.3 Implementing Medical Device Quality Initiatives 206
9.7.21 Case Study: Nephrotoxicity Biomarkers 206
9.7.22 Role of the FDA 2069.7.6 FDA Critical Path 185

9.7.6.1 Challenge and Opportunity on the Critical Path to New Medical Products 186
9.7.6.2 The NIH Roadmap 187
9.7.6.3 Predictive Safety Testing Consortium 187
9.7.6.4 FDA Risk-based Approach 187
9.7.6.5 Examples of drugs being held up due to lack of compliance with FDA directives 187
9.7.7 Negotiating the Critical Path 187
9.7.8 Technical Dimensions along the Critical Path 188
9.7.9 Product Development Toolkit 189
9.7.10 Tools for Assessing Safety 190
9.7.11 Tools for Demonstrating Medical Utility 192
9.7.12 Tools for Manufacturing 195
9.7.13 Orphan Products Grant Program 196
9.7.14 Slowdown in New Medical Products 196
9.7.15 Factors Contributing to the Decline in New Product Applications 199
9.7.16 Factors that Cause Unnecessary Delays in New Product Approvals 201
9.7.17 Reducing Avoidable Delays in Time to Approval 202
9.7.18 Reducing Delays in Medical Device Reviews 203
9.7.19 Reducing Delays in Animal Drug Reviews 204
9.7.20 Quality Systems Approach to Medical Product Review 204
9.7.20.1 Instituting Quality Systems in Review of New Drugs and Biologics 205
9.7.20.2 Implementing of the Common Technical Document (CTD) and the electronic CTD 205
9.7.20.3 Implementing Medical Device Quality Initiatives 206
9.7.21 Case Study: Nephrotoxicity Biomarkers 206
9.7.22 Role of the FDA 206
9.8 CMS Regulatory Responsibilities 207

9.9 Role of National Institute of Standards and Technology in Validation of Biomarkers 208
9.10 Biomarkers and FDA's Voluntary Genomic Data Submission 208
9.11 Federal Health Oncology Biomarker Qualification Initiative 210
9.12 Orphan Drug Act and Pharmacogenomics: Options and Opportunities 211
9.13 Post-market Covigilance Programs 212
9.14 Technology Options, Potential Diagnostic Partners and Regulatory Hurdles 212
9.15 What Regulatory Guidance Is Needed for Companion Biomarkers? 213
9.16 U.S. Patent and Trademark Office (USPTO) 215
9.17 IRB Approval in Clinical Trials 215
9.18 Reimbursement and Value Creation 215
9.19 FDA Guidance document on co-development 215
9.20 What is the future role of PBM's in laboratory services 215
9.21 FDA Guidance document on co-development 216

10. Business Decisions Using Companion Biomarkers in Drug Development 217

10.1 Advantages of a Pharmacogenomic Assessment of Biomarkers to Determine Clinical Dose 217
10.2 Key Opportunities in Biomarker Discovery, Development and Commercialization 217
10.3 What Are the Current Obstacles in Biomarker Implementation in Clinical Medicine? 218
10.4 How Do Business Strategies, Such as Those Relating to Acquisition, Drive Biomarker Strategies? 219
10.5 What is the Right Balance Between Using External Partnerships and Developing Internal Infrastructure? 219
10.6 How Might Novel Biomarker Development Lead to Acquisition Strategies and Their Implications For Deal Making? 219
10.7 Which Types of Biomarkers Should Be Developed at Various Stages in the Drug Pipeline? 219
10.8 What Strategies Help Translate Biomarkers From Preclinical to Clinical Development? 219
10.9 In What Class of Drugs Is the Value of Using Biomarkers in Decision Making the Highest? 220
10.10 Increased Clinical Trial Costs in Targeted Phase I Trials 221
10.11 How Can Big Pharma Co-develop Biomarkers in a Cost-sharing Model for Regulatory Acceptance? 221
10.12 How are Biomarkers Being Used to Reduce the Attrition Rate in Drug Development? 221
10.13 How is ROI Measured Using Biomarkers in Drug Development? 221
10.14 How might Organizational Structures Limit the Use of Biomarkers in Drug Development and How Should R&D Organizations Address this Problem? 221
10.15 How to Maximize Business Development through Biomarker Strategies 222
10.16 What Is the Best Type of Business Model for Developing Biomarkers? 222
10.17 What Are Organizational Impediments Limiting the Use of Biomarkers in Drug Development? 222
10.18 What Are Internal Capabilities for Novel Biomarker Development and Application? 222
10.19 How Can Key Biomarker Technical Expertise Be Applied Across a Complex and Highly-Stratified R&D Value Chain? 223
10.20 At What Stage of Drug Development Have Biomarkers Provided the Most Benefit? 223
10.21 What Companies Are the Most Innovative in Development of Biomarkers? 223
10.22 Best Values for Biomarkers in Drug Development and in Diagnostics 223
10.23 Companion Biomarkers Can Increase Value in an Associated Drug 224
10.24 What is the role of governmental agencies in driving the adoption of CDx? 224
10.25 What is the role of the insurance industry in driving the adoption? 224
10.26 What is the role of the pharma industry in driving the adoption of PGx? 224
10.27 What is the role of the diagnostic industry in driving the adoption of PGx? 225

11. Company Profiles 226

11.1 Abbott Laboratories 226
11.2 Accelrys 229
11.3 Affymetrix 230
11.4 Agilent Technologies 233
11.5 Almac Diagnostics 236
11.6 Amgen 236
11.7 Ananomouse 238
11.8 Applied Maths 238
11.9 Ariadne Genomics 239
11.10 ArrayIt (Integrated Media Holdings) 239
11.11 AstraZeneca 239
11.12 AutoGenomics 241
11.13 Axontologic 241
11.14 Beckman Coulter (now part of Danaher) 241
11.15 Becton, Dickinson and Company (BD) 244
11.16 Bender MedSystems (Affymetrix) 245
11.17 Bioalma 246
11.18 BioAnalytics Group 246
11.19 Biocartis 246
11.20 Biocept Laboratories 247
11.21 BioChain 248
11.22 BioData 248
11.23 BioDiscovery 248
11.24 Biodesix 248
11.25 BioForce Nanosciences 249
11.26 BioGenex 250
11.27 Bioinformatics Solutions 250
11.28 Biomax Informatics 250
11.29 BioMérieux 250

11.30 Biomind 251
11.31 Bio-Rad Laboratories 251
11.32 BioSystems International (BSI) 252
11.33 Biotrin (DiaSorin) 252
11.34 BioWisdom (Instem Scientific Limited) 253
11.35 Bristol-Myers Squibb Company 253
11.36 Caliper Life Sciences (A PerkinElmer Company) 255
11.37 Caprion Proteomics 258
11.38 Carestream Health 259
11.39 Celera 259
11.40 Cepheid 262
11.41 Chang Bioscience 264
11.42 Clontech Laboratories 264
11.43 CombiMatrix Diagnositcs 264
11.44 Compugen 266
11.45 Correlogic Systems, Inc. (Vermillion, Inc.) 268
11.46 Covance 268
11.47 Cybrdi 268
11.48 Cytogen Corporation (now EUSA Pharma) 268
11.49 Dako A/S (Agilent Technologies) 269
11.50 Decodon 270
11.51 Definiens 270
11.52 DiagnoSwiss 271
11.53 Discerna 271
11.54 DNAStar 271
11.55 DNATools 272
11.56 Eidogen-Sertanty 272
11.57 Electric Genetics 272
11.58 Eli Lilly and Company 272
11.59 Entelos 273
11.60 ePitope Informatics 274
11.61 Eurogentec 274
11.62 Exiqon A/S 274
11.63 Forensic Bioinformatics 275
11.64 Fujitsu 275
11.65 Future Diagnostics 275
11.66 Gene Codes 276
11.67 Genedata 276
11.68 GeneGo 276
11.69 Gene Network Sciences 276
11.70 Geneva Bioinformatics 277
11.71 Genomatica 277
11.72 Genomic Solutions 277
11.73 Genomining 277
11.74 GE Healthcare 278
11.75 GeneStudio 278
11.76 Genomatix Software 278
11.77 GenomeQuest 279
11.78 Genus BioSystems 279
11.79 Genzyme (Sanofi-Aventis) 279
11.80 Geospiza 279
11.81 GlaxoSmithKline 279
11.82 Golden Helix 280
11.83 Grace Bio-Labs 280
11.84 Gyros AB 281
11.85 HealthCare IT 281
11.86 Hologic Gen-Probe 281
11.87 High Throughput Genomics 286
11.88 Human Genome Sciences (GSK) 286
11.89 Illumina, Inc. 287
11.90 Imgenex Corp. 288
11.91 Imaxia 288
11.92 INCOGEN, Inc. 288
11.93 Incyte 289
11.94 InforSense 289

11.95 Ingenuity Systems 289
11.96 InPharmix 290
11.97 Insightful Corporation 290
11.98 Integromics, S.L 290
11.99 IBM 290
11.100 IO Informatics 292
11.101 Ipsen 292
11.102 Jerini AG 292
11.103 Johnson & Johnson 292
11.104 Koada Technology 293
11.105 KOOPrime 293
11.106 Life Technologies Corporation 293
11.107 LINCO Research 296
11.108 Luminex 296
11.109 Marligen Biosciences 297
11.110 Matrix Science 298
11.111 MDS, Inc. (Nordion, Inc.) 298
11.112 Merck & Co., Inc. 298
11.113 Merck KGaA 299
11.114 Meso Scale Discovery 300
11.115 Metabolon 300
11.116 Microbionix 300
11.117 MicroDiscovery 301
11.118 Millennium Pharmaceuticals 301
11.119 Millipore 301
11.120 MiraiBio 303
11.121 Molecular Connections 303
11.122 MolMine AS 303
11.123 Molsoft 304
11.124 Monogram Biosciences (Labcorp) 304
11.125 MTR Scientific 305
11.126 Multimetrix 305
11.127 Nanogen, Inc. 306
11.128 Nanosphere 306
11.129 NetGenics 307
11.130 NextGen Sciences 307
11.131 NimbleGen Systems 307
11.132 Nonlinear Dynamics 307
11.133 Novartis 308
11.134 Nuvera Biosciences 309
11.135 Ocimum Biosolutions 309
11.136 OmniViz 309
11.137 One Lambda (Thermo Fisher's Specialty Diagnostics Segment) 309
11.138 Oracle 310
11.139 OriGene Technologies 311
11.140 Ore Pharmaceuticals, Inc. (Ore Holdings, Inc.) 312
11.141 Orla Protein Technologies 313
11.142 Osmetech Plc (Genmark Diagnostics) 313
11.143 Oxonica 313
11.144 PamGene BV 314

11.145 Panomics 314
11.146 Partek Incorporated 314
11.147 Pepscan Therapeutics 315
11.148 Perbio Science 315
11.149 Perlegen Sciences 315
11.150 Pfizer 315
11.151 PharmaSeq, Inc. 316
11.152 Pierce Biotechnology 316
11.153 Platypus Technologies, LLC 316
11.154 Predictive Patterns Software 317
11.155 Proceryon Biosciences 317
11.156 Protagen AG 317
11.157 ProteinOne 318
11.158 Proteome Sciences 318
11.159 Pub Gene 318
11.160 Qiagen 319
11.161 Radix BioSolutions 323
11.162 Randox Laboratories 323
11.163 RayBiotech 323
11.164 Redasoft 324
11.165 RedStorm Scientific 324
11.166 Reel Two (Surechem, Inc.) 324
11.167 Rescentris 324
11.168 Roche 324
11.169 Rosetta Biosoftware 326
11.170 Rules-Based Medicine (Myriad Genetics, Inc.) 326
11.171 SAS 327
11.172 Schleicher & Schuell BioScience 327
11.173 SciTegic 327
11.174 Semantx Life Sciences 327
11.175 Sequenom 327
11.176 Siemens Heathcare Diagnostics 328
11.177 Sigma-Aldrich 330
11.178 Silicon Genetics 331
11.179 Singulex 331
11.180 Softberry, Inc. 331
11.181 SoftGenetics 331
11.182 SomaLogic 331
11.183 Spotfire 332
11.184 SPSS 332
11.185 Strand Life Sciences 333
11.186 Stratagene 333
11.187 SuperBioChips Laboratories 333

11.188 SurroMed 333
11.189 Sun Microsystems 333
11.190 Sygnis Pharma AG 33411.187 SuperBioChips Laboratories 333
11.188 SurroMed 333
11.189 Sun Microsystems 333
11.190 Sygnis Pharma AG 334
11.191 Techne Corporation 334
11.192 Tepnel Life Sciences (Hologic Gen-Probe) 335
11.193 Teranode 335
11.194 Textco BioSoftware 336
11.195 TG Services, Inc. 336
11.196 Thermo Fisher Scientific 336
11.197 Third Wave Technologies 337
11.198 Thomson Reuters 337
11.199 TIBCO Software 338
11.200 TimeLogic 338
11.201 TriStar Technology Group 338
11.202 Tyrian Diagnostics (formerly Proteome Systems) 338
11.203 VBC-Genomics Bioscience Research GmbH (Phadia Multiplexing Diagnostics GmbH) 339
11.204 Ventana Medical Systems 339
11.205 ViaLogy 339
11.206 Wyeth 339
11.207 Zeptosens 340
11.208 Zeus Scientific 340
11.209 Zyagen 340
Appendix 1: FDA Guidance for Industry: Pharmacogenomic Data Submission 341
Appendix 1.1: Introduction 341
Appendix 1.2: Background 341
Appendix 1.3: Submission Policy 342
Appendix 1.3.1: General Principles 342
Appendix 1.3.2: Specific Uses of Pharmacogenomic Data in Drug Development and Labeling 343
Appendix 1.3.3: Benefits of Voluntary Submissions to Sponsors and FDA 344
Appendix 1.4: Submission of Pharmacogenomic Data 345
Appendix 1.4.1: Submission of Pharmacogenomic Data during the IND Phase 345
Appendix 1.4.2: Submission of Pharmacogenomic Data to a New NDA, BLA, or Supplement 346
Appendix 1.4.3: Submission to a Previously Approved NDA or BLA 347
Appendix 1.4.4: Compliance with 21 CFR Part 58 347
Appendix 1.4.5: Submission of Voluntary Genomic Data from Application-Independent Research 348

Appendix 1.5: Format and Content of a VGDS 348
Appendix 1.6: Process for Submitting Pharmacogenomic Data 349
Appendix 1.7: Agency Review of VGDSs 349
Glossary 351
Appendix 2: Guidance for Industry and Food and Drug Administration Staff—In Vitro Companion Diagnostic Devices 352
Appendix 2.1: Introduction 352
Appendix 2.2: Background 352
Appendix 2.3: Definition and Use of an IVD Companion Diagnostic Device 353
Appendix 2.4: Review and Approval of IVD Companion Diagnostic Devices and Therapeutic Products 354
Appendix 2.4.1: Novel Therapeutic Products 354
Appendix 2.4.2: Approval of a Therapeutic Product without an Approved IVD Companion Diagnostic Device 354
Appendix 2.4.3: General Policies 355
Appendix 2.5: Labelling 355
Appendix 2.5.1: Therapeutic Product Labelling 355
Appendix 2.5.2: IVD Companion Diagnostic Device Labeling 356
Appendix 2.6: Investigational Use 357

INDEX OF FIGURES

Figure 2.1: Drug Discovery and Development Paradigm 30
Figure 2.2: Paradigm of Drug Discovery and Development Illustrating the Central and Essential Role of Biomarkers in Screening 34
Figure 2.3: Functional Genomic Process for Drug Development 35
Figure 2.4: Reimbursement for Diagnostics in Healthcare Decision Making: Percentage Influence on Healthcare Decision Making 39
Figure 2.5: Reimbursement for Diagnostics in Healthcare Decision Making: Percentage of Healthcare Spending 39
Figure 2.6: Market Growth and Evolution of Companion Biomarkers 40
Figure 2.7: Medical Product Development Models 41
Figure 2.8: Segmentation of the Biomarker Development Market 42
Figure 2.9: Global Pharmaceutical Drug Sales, 2004-2018 47
Figure 2.10: Worldwide Generic Pharmaceutical Drug Market, 2003-2018 49
Figure 2.11: Worldwide OTC Pharmaceutical Drug Market, 2003-2018 50
Figure 2.12: Worldwide Biopharmaceutical Drug Market, 2003-2018 51
Figure 2.13: Number of Compounds by Clinical Trial Phase, 2012 55
Figure 2.14: Biomarkers Market Drivers 69
Figure 2.15: Challenges in the Biomarkers Space 70
Figure 2.16: FDA Co-Developed Products 75
Figure 3.1: Worldwide Microarray Market Size, 2004-2018 84
Figure 3.2: Informatics Applications Along the Drug Discovery Value Chain 103
Figure 3.3: Bioinformatics Software Flow Chart 104
Figure 3.4: Growth of GenBank, 1982-2012 104
Figure 3.5: Role of Bioinformatics in the Drug Discovery Value Chain 115
Figure 3.6: Challenges in the Study or Utilization of Proteomic Biomarkers 119
Figure 3.7: Challenges in the Study or Utilization of Companion Diagnostic Biomarkers 120
Figure 3.8: Top Unmet Needs in Products in the Biomarkers Space 121
Figure 4.1: Companion Biomarker Market Size, 2008-2018 133

Figure 4.2: Growth and Evolution of the Biomarker Space 134
Figure 4.3: Revenue Forecast Projections for Global Biomarker Markets by Segments, 2005-2012 135
Figure 4.4: Biomarker Discovery by Therapeutic Area 135
Figure 4.5: Kidney Biomarker Paradigm 139
Figure 4.6: Hepatic Biomarker Paradigm 141
Figure 9.1: IPRG Biomarker Qualification Process 183
Figure 9.2: Critical Path for Drug Development 197
Figure 9.3: Path for R&D Product Development 197
Figure 9.4: Dimensions of the Critical Path 198
Figure 9.5: FDA Interactions During Drug Development 198
Figure 9.6: Problem Resolution During the FDA Review Process 199
Figure 9.7: VGDS Process Flow 209
Figure 10.1: Discovery, Validation and Use of Biomarkers 220

INDEX OF TABLES

Table 2.1: Utility of Biomarkers as Companion Diagnostics to Drug Development 26
Table 2.2: Biomarker End Points in Drug Development 28
Table 2.3: Value of Biomarkers in Phase II Clinical Trials 30
Table 2.4: Representative Companion Diagnostic Deals 31
Table 2.5: Selected examples of Companion Diagnostics used in cancer therapies 33
Table 2.6: Comparative Genome Sizes of Humans and Other Organisms 36
Table 2.7: Global Pharmaceutical Drug Sales, 2004-2018 47
Table 2.8: Worldwide Generic Pharmaceutical Drug Market, 2003-2018 48
Table 2.9: Worldwide OTC Pharmaceutical Drug Market, 2003-2018 49
Table 2.10: Worldwide Biopharmaceutical Drug Market, 2003-2018 50
Table 2.11: Threats to Pharmaceutical Industry Productivity 52
Table 2.12: Competitive Forces Governing the Pharmaceutical Industry 52
Table 2.13: Time Line for Development of Companion Diagnostics 53
Table 2.14: Leading Therapy Classes for R&D, 2012 54
Table 2.15: Global Total Pharmaceutical Industry R&D Spending, 2004-2018 56
Table 2.16: Pharmaceutical R&D Spend: Top 20 Companies and Total Market, 2011 and 2018 57
Table 2.17: Global Pharmaceutical Top Markets, 2011 57
Table 2.18: World's Top-Selling Drugs, 2011 and 2012 58
Table 2.19: Top Pharmaceutical Companies by Pharmaceutical Sales, 2011 and 2012 59
Table 2.20: Leading Therapy Classes by Global Pharmaceutical Sales, 2012 59
Table 2.21: New Molecular Entity Approvals for 2012 61
Table 2.22: Pharmaceuticals Industry Challenges 65
Table 2.23: Reasons for Developing Phase I Biomarkers 66
Table 2.24: Percentage of Non-Responders in Various Drug Classes 66
Table 2.25: High Profile Drug Withdrawals from the Marketplace 67
Table 2.26: Market Opportunities in Biomarkers 70
Table 2.27: Challenges for Market Adoption of the Various Biomarkers Tests 71
Table 2.28: Biomarkers Industry SWOT 72
Table 2.29: Stakeholders and their Expectations of Companion Diagnostics 73
Table 3.1: Worldwide Microarray Market Size, 2004-2018 84
Table 3.2: List of DNA Array Manufacturers 90
Table 3.3: U.S. qRT-PCR Market, 2007-2018 96
Table 3.4: Theranostics Technology Platforms—Timeline of Impact 98
Table 3.5: Impact of Personalized Medicine on Various Therapeutic Areas 99
Table 3.6: Hurdles in Biomarkers Development in Therapeutic Areas 100
Table 3.7: Data Source and Bioinformatic Investigations 107
Table 3.8: Drivers and Challenges of the Bioinformatics Industry 110
Table 3.9: Bioinformatics Activities, Sub-Activities and Key Players 117
Table 3.10: Concentration of Some Abundant Proteins, New Cancer Biomarkers Identified by SELDI-TOF, and Classical Cancer Biomarkers in Serum 126
Table 3.11: Device Submission Elements for the FDA 126
Table 3.12: Toxicogenomic Standards and Their Organizations 130
Table 3.13: Genomic and Proteomic Technologies 131
Table 4.1: Companion Biomarker Market Size, 2008-2018 133
Table 4.2: Kidney Biomarkers 140
Table 4.3: Herceptin Worldwide Sales, 2000-2017 143
Table 4.4: Characteristics of Different Cancer Biomarker Types and Associated Market Opportunities 143
Table 4.5: Segmentation of the Cancer Biomarker Market by Type of Cancer Biomarkers and Market Size 144
Table 4.6: Cancer Biomarker Market Estimates by Tissue of Origin 145
Table 4.7: Companies Developing New Proteomic Cancer Biomarker Technology Platforms 146
Table 4.8: Cancer Biomarkers Used to Maximize Likelihood of Response 147
Table 4.9: Biomarkers for Monitoring Therapeutic Effectiveness and Resistance 148
Table 6.1: Contract Research Companies 161
Table 8.1: Stakeholders in Biomarker Development 170
Table 9.1: Structure of the Critical Path 188
Table 9.2: Device Submission El

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Genomics Industry: Companion Biomarkers in Drug Development

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