Companion Biomarkers in Drug Development

Content

• 1. Overview
  • 1.1 Statement of Report
  • 1.2 about This Report
  • 1.3 Scope of the Report
  • 1.4 Objectives
  • 1.5 Methodology
  • 1.6 Executive Summary
• 2. Introduction: Companion Diagnostics in Drug Development
  • 2.1 Companion Diagnostics as Biomarkers
    • 2.1.1 Potential Benefits of Biomarkers as Companion Diagnostics
  • 2.2 Biomarkers in Different Phases of Drug Development
    • 2.2.1 Drug Discovery and Development Process
    • 2.2.2 Biomarkers in Drug Development
  • 2.3 Drug Targets
    • 2.3.1 Target Discovery Using Functional Genomics
    • 2.3.2 Functional Genomics
    • 2.3.3 Target Validation
      • 2.3.3.1 Target Discovery
      • 2.3.3.2 Lead Identification
    • 2.3.4 Target and Biomarker Discovery
      • 2.3.4.1 Biomarker Validation
  • 2.4 Biomarkers in Drug Discovery, Development and Clinical Diagnostics
    • 2.4.1 Role of Biomarkers in Drug Discovery, Preclinical, Clinical Development and Diagnostics
    • 2.4.2 The Pipeline Problem
    • 2.4.3 Biomarkers in the Drug Discovery Process
    • 2.4.4 Segmentation of Biomarker Usage
    • 2.4.5 Efficacy of Biomarkers as Surrogate Endpoints
    • 2.4.6 Biomarkers Used tReduce the Cost of Drug Development
    • 2.4.7 Biomarkers: Challenges and Opportunities
    • 2.4.8 Biomarkers in Early Safety and Toxicity Assessment
    • 2.4.9 Biomarkers in Determining Validation Parameters
    • 2.4.10 Challenges in Development of Biomarkers
    • 2.4.11 Using Biomarkers in Early Clinical Development
    • 2.4.12 Translational Biomarkers
    • 2.4.13 Use of Biomarkers in ""Go""/No-Go"" Decisions
    • 2.4.14 Diagnostic Tests
    • 2.4.15 Biomarkers in Deal Making
    • 2.4.16 Payors Use Biomarkers in Decision-Making
  • 2.5 World Pharmaceutical Markets
    • 2.5.1 World Market Summary
    • 2.5.2 Company Performance in this Segment
    • 2.5.3 Forces Affecting the Structure of the Pharmaceutical Industry
      • 2.5.3.1 Threats
      • 2.5.3.2 Competitive Forces
    • 2.6.1 Industry Overview
      • 2.6.1.1 Pharmaceutical Industry Drug Pipeline
      • 2.6.1.2 Asia-Pacific tReplace United States and Europe as Pharmaceutical Industry Center
      • 2.6.1.3 The Changing Pharmaceutical Business Model
    • 2.6.2 Benefits for Companion Diagnostic Tests in Drug Development
    • 2.6.3 Strategies for the Creation of Partnerships - Predicting and Overcoming Challenges in Creating Drug Response Profiling Diagnostics
    • 2.6.4 Options and Applications
      • 2.6.4.1 Clinical Applications of Genomics: The Use of Evidence Based Frameworks by Decision-Makers
    • 2.6.5 Challenges, Drivers and Trends
      • 2.6.5.1 MacrTrends in Biomarkers
      • 2.6.5.2 Biomarkers: Industry SWOT Analysis
    • 2.6.6 Breakaway Technologies
    • 2.6.7 Collaboration for Companion Diagnostics
    • 2.6.8 Key Stake Holders in Companion Diagnostics
  • 2.9 Future Developments
• 3. Biomarker Development Tools
  • 3.1 New Technologies in Functional Genomics
    • 3.1.1 Genomics-Derived Drug Pipeline
    • 3.1.2 Future of Genomics Technologies for Drug Target Identification
  • 3.2 Overview of Microarrays
    • 3.2.1 General Theory of Microarrays
    • 3.2.2 GeneChip Probe Array Technology
    • 3.2.3 DNA Microarrays
      • 3.2.3.1 DNA Microarray Market Size
      • 3.2.3.2 DNA Microarrays in SNP Analysis
      • 3.2.3.3 DNA Microarrays in Cancer
    • 3.2.4 Protein Microarrays
      • 3.2.4.1 Reasons Why Researchers Use Protein Microarrays
      • 3.2.4.2 Factors for Adoption of Protein Microarrays Technology
      • 3.2.4.3 Future Innovations in Protein Microarray Technology
    • 3.2.5 New Technologies
      • 3.2.5.1 Antibody Microarrays
      • 3.2.5.2 Peptide Microarrays
      • 3.2.5.3 Peptide MHC Microarrays
      • 3.2.5.4 Tissue Microarrays
      • 3.2.5.5 Key Points for Developing Microarray Based Applications
      • 3.2.5.6 Reasons Why Researchers use DNA Microarrays
      • 3.2.5.7 Factors for Difficulties Applying DNA Microarrays Technology
      • 3.2.5.8 Emerging Microarray Trends
      • 3.2.5.9 Emerging Microarray Applications
      • 3.2.5.10 Key Findings on Use of Microarrays
      • 3.2.5.11 Advantages and Drivers of Microarrays
      • 3.2.5.12 Limitations and Barriers tUse of Microarrays
      • 3.2.5.13 qRT-PCR Use in Biomarker Identification and Drug Development
      • 3.2.5.14 Microarray Quality Control (MAQC) Project
  • 3.3 Theranostics
    • 3.3.1 Theranostics in Drug Development
    • 3.3.2 Trends in Theranostics
    • 3.3.3 Timeline for Impact on Various Segments in Theranostics
    • 3.3.4 Challenges for Biomarker Based Therapeutics Development
  • 3.4 Pharmaceutical Development and Bioanalytical Services
    • 3.4.1 Wyeth Singulex's Erenna
  • 3.5 Metabolomics in Drug Discovery
  • 3.6 Bioinformatics
    • 3.6.1 Definition and Role of Bioinformatics
    • 3.6.2 Bioinformatics Sector Overview
    • 3.6.3 Future Status of Bioinformatics
      • 3.6.3.1 Future in Drug Discovery
      • 3.6.3.2 Mergers and Acquisitions Could Deter Bioinformatics Growth
      • 3.6.3.3 Barriers tBioinformatics Growth
      • 3.6.3.4 Types of Data and Bioinformatics Applications
      • 3.6.3.5 Validated Core Modeling Technology
      • 3.6.3.6 Applicability of Bioinformatics for Biomarker Discovery
      • 3.6.3.7 Biomarker Data Management Compliant with Industry Standards
      • 3.6.3.8 Data Management for Biomarkers
      • 3.6.3.8.1 Data Transformation for Biomarker Development
      • 3.6.3.8.2 Biomarker Data Collaboration
      • 3.6.3.8.3 Interface for Online Data Sources for Genomic Structures
      • 3.6.3.8.4 Target Markets for Informatics Software
      • 3.6.3.8.5 Bioinformatics Drivers and Challenges in the Pharmaceutical Industry
      • 3.6.3.8.6 Products of Bioinformatics
      • 3.6.3.8.7 Informatics Tools and Functionalities
      • 3.6.3.8.8 Bioinformatics in Lead Identification and Optimization
      • 3.6.3.8.9 Bioinformatics in Drug Development and Formulation
      • 3.6.3.8.10 Role of Bioinformatics in the Drug Discovery Value Chain
      • 3.6.3.8.11 Bioinformatics Software for Drug Discovery and Biomarker Development
      • 3.6.3.8.12 Bioinformatics Services
  • 3.7 Biomarkers and Proteomics
    • 3.7.1 Scientific Background
    • 3.7.2 Applying Proteomics tBiomarker Discovery
      • 3.7.2.1 Challenges Facing Biomarker Developers
    • 3.7.3 Limitations of Proteomic Approaches tBiomarker Discovery
    • 3.7.4 Validation of Biomarkers Using LC-MS/MS Systems
    • 3.7.5 Use of Mass Spectrometry in Biomarker Discovery
      • 3.7.5.1 Multiple Reaction Monitoring Assays (MRMs)
      • 3.7.5.2 Gel-based Approaches
      • 3.7.5.3 Non-Gel-based Approaches
      • 3.7.5.4 SELDI-TOF MS
      • 3.7.5.5 SELDI and Prognosis
      • 3.7.5.6 SELDI and Treatment Monitoring
      • 3.7.5.7 Limitations of Mass Spectroscopy
    • 3.7.6 Partnerships for Developing Proteomic Biomarkers
    • 3.7.7 Proteomics in Developing a New Cancer Marker
      • 3.7.7.1 Translating Proteomic Oncology Discoveries tthe Clinic: Development of
        • Analytical Reference Materials, Reagents, Data, and Technology Assessment and
        • Validation
      • 3.7.7.2 Challenges of Discovering and Validating Clinical Protein Biomarkers
      • 3.7.7.3 Importance of Proteomics in Biomarker Discovery
  • 3.8 Toxicogenomics
    • 3.8.1 Toxicogenomics Concerns in Drug Safety Data
    • 3.8.2 Toxicogenomics and Prioritization of Drug Candidates
    • 3.8.3 Genomic Biomarkers for Drug-Induced Nephrotoxicity
    • 3.8.4 Use of Biomarkers of Drug-Induced Cardiotoxicity
    • 3.8.5 Use of Biomarkers of Drug-induced Hepatotoxicity
    • 3.8.6 Transgenic Biomarkers for Adverse Drug-Drug Interactions
    • 3.8.7 Challenges tToxicogenomics
    • 3.8.8 The Future Use of Toxicogenomics in Drug Discovery
• 4. Market for Biomarkers in Drug Development
  • 4.1 C-KIT (CD117) Expression
  • 4.2 CCR5 -Chemokine C-C Motif Receptor
  • 4.3 CYP2C19 Variants
  • 4.4 CYP2C9 Variants
  • 4.5 CYP2D6 Variants
  • 4.6 CYP2D6 Variants with Alternate Context
  • 4.7 Clinical Biomarkers
  • 4.8 Targeting Kidney Toxicity
    • 4.8.1 Proximal and Distal Tubular Injury (alpha-GST & Pi-GST)
    • 4.8.2 Collecting Duct and Loop of Henle Injury (RPA-1 and RPA-2)
    • 4.8.3 Glomerular Injury (Collagen IV)
    • 4.8.4 KIM-1
  • 4.9 Targeting Hepatotoxicity
    • 4.9.1 Breast Cancer
    • 4.9.2 Colorectal Cancer
    • 4.9.3 Prostate Cancer
    • 4.9.4 Cystic Fibrosis
  • 4.10 Biomarker Application in Oncology Clinical Development
    • 4.10.1 Specific Example of Companion Biomarkers in Clinical Oncology
    • 4.10.2 Integration of a Companion Diagnostic Strategy intOncology Drug Development
      • 4.10.2.1 Lilly tCo-Develop Companion IVDs for Cancer Drugs
      • 4.10.2.2 Celera tWork on Companion Diagnostics for Merck Cancer Drugs
      • 4.10.2.3 BioMrieux tDevelop Companion Test for Ipsen's New Breast Cancer Drug
      • 4.10.2.4 Perlegen and Roche's 454 Develop Companion Tests
      • 4.10.2.5 Ventana Medical Systems and the Critical Path Institute
      • 4.10.2.6 Biomarkers in Recentin/AZD 2171 Development
      • 4.10.2.7 Biomarkers in Development of Iressa
      • 4.10.2.8 Epigenomics' Methylation Biomarker Septin
  • 4.11 Targeting Diabetes Related Heart Disease
  • 4.12 Key Challenges and Opportunities in Developing Targeted Therapeutics
• 5. Imaging Biomarkers in Drug Discovery
  • 5.1 Introduction
    • 5.1.1 Validation of Imaging Biomarkers
    • 5.1.2 Types of Imaging Used in Drug Development
    • 5.1.3 Development of Imaging Technologies
  • 5.2 Molecular Imaging
    • 5.2.1 Use in Drug Discovery
    • 5.2.2 Use in Clinical Applications
    • 5.2.3 Use in Clinical Trials
    • 5.2.4 Cell-based Screening Technologies in Drug Development
    • 5.2.5 Optical Biomarkers
  • 5.3 Magnetic Resonance Imaging
  • 5.4 Positron Emission Tomography
  • 5.5 FDG-PET Patient Phase I Studies
  • 5.6 Imaging Biomarkers as Study Endpoints
    • 5.6.1 Oncology
    • 5.6.2 Parkinson's Disease
    • 5.6.3 Cardiac Disease
  • 5.7 IT Solutions for Imaging Biomarkers in Biopharmaceutical Research and Development
• 6. Clinical Biomarkers Improving Trial Design
  • 6.1 Strategies tImprove the Measurement of Biomarkers for Drug Trials
  • 6.2 Key Opportunities in Biomarker Discovery, Development and Commercialization
    • 6.2.1 Contract Research Companies
  • 6.3 What Strategies Help Translate Biomarkers from Preclinical tClinical Development?
  • 6.4 How Should Biomarker Data Be Compared t""Traditional"" Safety and Efficacy Data?
• 7. Biomarkers as Surrogate Endpoints
  • 7.1 What is a Surrogate Endpoint?
  • 7.2 Benefits and Drawbacks of Surrogate Endpoints
    • 7.2.1 Benefits
    • 7.2.2 Drawbacks
  • 7.3 Improving the Efficacy of Clinical Surrogate End Points Using Biomarkers
  • 7.4 Surrogate Endpoint Validation
  • 7.5 Effective Use of Surrogates
    • 7.5.1 FDG-PET as a Surrogate Endpoint in Oncology Studies
  • 7.6 Conclusions
• 8. Market Size, Collaborations and Future Directions for Companion Diagnostics
  • in Drug Development
  • 8.1 Strategies tImprove the Measurement of Biomarkers for Drug Trials
    • 8.1.1 Key Opportunities in Biomarker Discovery, Development and Commercialization
    • 8.1.2 The Rationale behind Biomarker Strategy
    • 8.1.3 New Development Strategies and Their Implications for Deal Making
    • 8.1.4 How Biomarkers Are Being Used tReduce Attrition in Development
    • 8.1.5 Combined Therapeutics and Diagnostics Biomarker Business Makes Sense
    • 8.1.6 Use of Biomarkers in House or Partner with a Diagnostics Company
  • 8.2 What is the Best Balance of Resources tHave the Most Efficient Pathway tDevelop Biomarkers?
  • 8.3 Current and Future Trends in Drug Development
  • 8.4 Future Role of Biomarkers in Healthcare
  • 8.5 What are the Current Organizational Obstacles in Biomarker Implementation?
• 9. Regulatory Issues for Biomarkers in Drug Development
  • 9.1 Introduction
    • 9.1.1 Role of Regulatory Agencies in Development of Biomarkers
  • 9.2 FDA Perspective of Biomarkers in Clinical Trials
    • 9.2.1 FDA as a Gatekeeper of Companion Biomarkers
    • 9.2.2 FDA Criteria for a Valid Biomarker
    • 9.2.3 FDA Product Submission and Review Process
    • 9.2.4 FDA Pipeline for Biomarker Tests
    • 9.2.5 Adaptive Clinical Trial Design
    • 9.2.6 Orphan Drug Act and Biomarkers: Options and Opportunities
  • 9.3 Role of StaRT-PCR in Increasing Value of Pharmacogenomic Data
  • 9.4 Supporting IND, NDA, and BLA Submissions
  • 9.5 Performance Characteristics of Biomarker Tools
  • 9.6 Biomarker Initiative and VGDs
  • 9.7 Biomarker Qualification Pilot Process at the FDA
    • 9.7.1 Introduction
    • 9.7.2 Biomarker is Validity
    • 9.7.3 Biomarker Qualification Process Map
    • 9.7.4 Biomarker Qualification Pilot Process
    • 9.7.5 The Pipeline Problem
    • 9.7.6 FDA Critical Path
      • 9.7.6.1 Challenge and Opportunity on the Critical Path tNew Medical Products
      • 9.7.6.2 The NIH Roadmap
      • 9.7.6.3 Predictive Safety Testing Consortium
    • 9.7.7 Negotiating the Critical Path
    • 9.7.8 Technical Dimensions along the Critical Path
    • 9.7.9 Product Development Toolkit
    • 9.7.10 Tools for Assessing Safety
    • 9.7.11 Tools for Demonstrating Medical Utility
    • 9.7.12 Tools for Manufacturing
    • 9.7.13 Orphan Products Grant Program
    • 9.7.14 Slowdown in New Medical Products
    • 9.7.15 Factors Contributing tthe Decline in New Product Applications
    • 9.7.16 Factors that Cause Unnecessary Delays in New Product Approvals
    • 9.7.17 Reducing Avoidable Delays in Time tApproval
    • 9.7.18 Reducing Delays in Medical Device Reviews
    • 9.7.19 Reducing Delays in Animal Drug Reviews
    • 9.7.20 Quality Systems Approach tMedical Product Review
      • 9.7.20.1 Instituting Quality Systems in Review of New Drugs and Biologics
      • 9.7.20.2 Implementing of the Common Technical Document (CTD) and the electronic CTD
      • 9.7.20.3 Implementing Medical Device Quality Initiatives
    • 9.7.21 Case Study: Nephrotoxicity Biomarkers
    • 9.7.22 Role of the FDA
  • 9.8 CMS Regulatory Responsibilities
  • 9.9 Role of National Institute of Standards and Technology in Validation of Biomarkers
  • 9.10 Biomarkers and FDA's Voluntary Genomic Data Submission
  • 9.11 Federal Health Oncology Biomarker Qualification Initiative
  • 9.12 Orphan Drug Act and Pharmacogenomics: Options and Opportunities
  • 9.13 Post-market Covigilance Programs
  • 9.14 Technology Options, Potential Diagnostic Partners and Regulatory Hurdles
  • 9.15 What Regulatory Guidance Is Needed for Companion Biomarkers?
  • 9.16 U.S. Patent and Trademark Office (USPTO)
  • 9.17 IRB Approval in Clinical Trials
• 10. Business Decisions Using Companion Biomarkers in Drug Development
  • 10.1 Advantages of a Pharmacogenomic Assessment of Biomarkers tDetermine Clinical Dose
  • 10.2 Key Opportunities in Biomarker Discovery, Development and Commercialization
  • 10.3 What Are the Current Obstacles in Biomarker Implementation?
  • 10.4 How DBusiness Strategies, Such as Those Relating tAcquisition, Drive Biomarker Strategies?
  • 10.5 What is the Right Balance between Using External Partnerships and Developing Internal Infrastructure?
  • 10.6 How Might Novel Biomarker Development Lead tAcquisition Strategies and Their Implications for Deal Making?
  • 10.7 Which Types of Biomarkers Should Be Developed at Various Stages in the Drug Pipeline?
  • 10.8 What Strategies Help Translate Biomarkers from Preclinical tClinical Development?
  • 10.9 in What Class of Drugs Is the Value of Using Biomarkers in Decision Making the Highest?
  • 10.10 Increased Clinical Trial Costs in Targeted Phase I Trials
  • 10.11 How Can Big Pharma Co-develop Biomarkers in a Cost-sharing Model for Regulatory Acceptance?
  • 10.12 How Are Biomarkers Being Used tReduce the Attrition Rate in Drug Development?
  • 10.13 How Is ROI Measured Using Biomarkers in Drug Development?
  • 10.14 How Might Organizational Structures Limit the Use of Biomarkers in Drug Development and How Should R&D Organizations Address This Problem?
  • 10.15 How tMaximize Business Development through Biomarker Strategies
  • 10.16 What Is the Best Type of Business Model for Developing Biomarkers?
  • 10.17 What Are Organizational Impediments Limiting the Use of Biomarkers in Drug Development?
  • 10.18 What Are Internal Capabilities for Novel Biomarker Development and Application?
  • 10.19 How Can Key Biomarker Technical Expertise Be Applied across a Complex and Highly-Stratified R&D Value Chain?
  • 10.20 at What Stage of Drug Development Have Biomarkers Provided the Most Benefit?
  • 10.21 What Companies Are the most Innovative in Development of Biomarkers?
  • 10.22 Best Values for Biomarkers in Drug Development and in Diagnostics
  • 10.23 Companion Biomarkers Can Increase Value in an Associated Drug
• 11. Company Profiles
  • 11.1 Abbott Laboratories
  • 11.2 Accelrys
  • 11.3 Affymetrix
  • 11.4 Agilent Technologies
  • 11.5 Amgen
  • 11.6 Ananomouse
  • 11.7 Applied Maths
  • 11.8 Ariadne Genomics
  • 11.9 ArrayIt (Integrated Media Holdings)
  • 11.10 AstraZeneca
  • 11.11 AutoGenomics
  • 11.12 Axontologic
  • 11.13 Beckman Coulter
  • 11.14 BD
  • 11.15 Bender MedSystems
  • 11.16 Bioalma
  • 11.17 BioAnalytics Group
  • 11.18 BioCat GmbH
  • 11.19 Biocept
  • 11.20 BioChain
  • 11.21 BioData
  • 11.22 BioDiscovery
  • 11.23 BioForce Nanosciences
  • 11.24 BioGenex
  • 11.25 Bioinformatics Solutions
  • 11.26 Biomax Informatics
  • 11.27 BioMrieux
  • 11.28 Biomind
  • 11.29 Bio-Rad Laboratories
  • 11.30 Biosite
  • 11.31 BioSystems International
  • 11.32 Biotrin
  • 11.33 BioWisdom
  • 11.34 Bristol-Myers Squibb Company
  • 11.35 Caliper Life Sciences
  • 11.36 Caprion Proteomics
  • 11.37 Carestream Health
  • 11.38 Celera
  • 11.39 Cepheid
  • 11.40 Chang Bioscience
  • 11.41 Clontech Laboratories
  • 11.42 CombiMatrix
  • 11.43 Compugen
  • 11.44 Corimbia
  • 11.45 Covance
  • 11.46 Cybrdi
  • 11.47 CyVera
  • 11.48 DakA/S
  • 11.49 Decodon
  • 11.50 Definiens
  • 11.51 DiagnoSwiss
  • 11.52 Discerna
  • 11.53 DNAStar
  • 11.54 DNATools
  • 11.55 Eidogen-Sertanty
  • 11.56 Electric Genetics
  • 11.57 Eli Lilly and Company
  • 11.58 Entelos
  • 11.59 ePitope Informatics
  • 11.60 Eurogentec
  • 11.61 Exiqon A/S
  • 11.62 Forensic Bioinformatics
  • 11.63 Fujitsu
  • 11.64 Future Diagnostics
  • 11.65 Genaissance Pharmaceuticals
  • 11.66 Gene Codes
  • 11.67 Genedata
  • 11.68 GeneGo
  • 11.69 Gene Network Sciences
  • 11.70 Geneva Bioinformatics
  • 11.71 Genomatica
  • 11.72 Genomic Solutions
  • 11.73 Genomining
  • 11.74 Gen-Probe
  • 11.75 GE Healthcare
  • 11.76 GeneStudio
  • 11.77 Genomatix Software
  • 11.78 GenomeQuest
  • 11.79 Genus BioSystems
  • 11.80 Genzyme
  • 11.81 Geospiza
  • 11.82 GlaxoSmithKline
  • 11.83 Golden Helix
  • 11.84 Grace Bio-Labs
  • 11.85 Gyros AB
  • 11.86 HealthCare IT
  • 11.87 High Throughput Genomics
  • 11.88 Human Genome Sciences
  • 11.89 Illumina
  • 11.90 Imgenex
  • 11.91 Imaxia
  • 11.92 INCOGEN
  • 11.93 Incyte
  • 11.94 InforSense
  • 11.95 Ingenuity Systems
  • 11.96 InPharmix
  • 11.97 Insightful Corporation
  • 11.98 Integromics, S.L
  • 11.99 IBM
  • 11.100 IO Informatics
  • 11.101 Ipsen
  • 11.102 Jerini AG
  • 11.103 Johnson & Johnson
  • 11.104 Koada Technology
  • 11.105 KOOPrime
  • 11.106 Life Technologies Corporation
  • 11.107 LINCO Research
  • 11.108 Luminex
  • 11.109 Marligen Biosciences
  • 11.110 Matrix Science
  • 11.111 MDS
  • 11.112 Merck & Company
  • 11.113 Merck KGaA
  • 11.114 MesScale Discovery
  • 11.115 Metabolon
  • 11.116 Microbionix
  • 11.117 MicroDiscovery
  • 11.118 Millennium Pharmaceuticals
  • 11.119 Millipore
  • 11.120 MiraiBio
  • 11.121 Molecular Connections
  • 11.122 MolMine AS
  • 11.123 Molsoft
  • 11.124 Monogram Biosciences
  • 11.125 MTR Scientific
  • 11.126 Multimetrix
  • 11.127 Nanogen
  • 11.128 Nanosphere
  • 11.129 NetGenics
  • 11.130 NextGen Sciences
  • 11.131 NimbleGen Systems
  • 11.132 Nonlinear Dynamics
  • 11.133 Novartis
  • 11.134 Nuvera Biosciences
  • 11.135 Ocimum Biosolutions
  • 11.136 OmniViz
  • 11.137 One Lambda
  • 11.138 Oracle
  • 11.139 Ore Pharmaceuticals
  • 11.140 Orla Protein Technologies
  • 11.141 Osmetech
  • 11.142 Oxonica
  • 11.143 PamGene BV
  • 11.144 Panomics
  • 11.145 Partek
  • 11.146 Pepscan
  • 11.147 PerbiScience
  • 11.148 Perlegen Sciences
  • 11.149 Pfizer
  • 11.150 PharmaSeq
  • 11.151 Pierce Biotechnology
  • 11.152 Platypus Technologies
  • 11.153 Predictive Patterns Software
  • 11.154 Proceryon
  • 11.155 Protagen AG
  • 11.156 ProteinOne
  • 11.157 Proteome Sciences
  • 11.158 PubGene
  • 11.159 Qiagen
  • 11.160 Radix BioSolutions
  • 11.161 Randox Laboratories
  • 11.162 RayBiotech
  • 11.163 Redasoft
  • 11.164 RedStorm Scientific
  • 11.165 Reel Two
  • 11.166 Rescentris
  • 11.167 Roche
  • 11.168 Rosetta Biosoftware
  • 11.169 Rules-Based Medicine
  • 11.170 SAS
  • 11.171 Schleicher & Schuell BioScience
  • 11.172 SciTegic
  • 11.173 Semantx Life Sciences
  • 11.174 Sequenom
  • 11.175 Sigma-Aldrich
  • 11.176 Silicon Genetics
  • 11.177 Singulex
  • 11.178 Softberry
  • 11.179 SoftGenetics
  • 11.180 SomaLogic
  • 11.181 Spotfire
  • 11.182 SPSS
  • 11.183 Strand Life Sciences
  • 11.184 Stratagene
  • 11.185 SuperBioChips Laboratories
  • 11.186 SurroMed
  • 11.187 Sun Microsystems
  • 11.188 Sygnis Pharma AG
  • 11.189 Techne Corporation
  • 11.190 Tepnel Life Sciences
  • 11.191 Teranode
  • 11.192 TextcBioSoftware
  • 11.193 TG Services
  • 11.194 ThermFisher Scientific
  • 11.195 Third Wave Technologies
  • 11.196 TIBCO Software
  • 11.197 TimeLogic
  • 11.198 TriStar Technology Group
  • 11.199 Tyrian Diagnostics (formerly Proteome Systems)
  • 11.200 VBC-Genomics Bioscience Research GmbH
  • 11.201 Ventana Medical Systems
  • 11.202 ViaLogy
  • 11.203 Wyeth
  • 11.204 Zeptosens
  • 11.205 Zeus Scientific
  • 11.206 Zyagen
• Appendix 1: FDA Guidance for Industry: Pharmacogenomic Data Submission
  • A 1.1 Introduction
  • A 1.2 Background
  • A 1.3 Submission Policy
  • A 1.3.1 General Principles
  • A 1.3.2 Specific Uses of Pharmacogenomic Data in Drug Development and Labeling
  • A 1.3.3 Benefits of Voluntary Submissions tSponsors and FDA
  • A 1.4 Submission of Pharmacogenomic Data
  • A 1.4.1 Submission of Pharmacogenomic Data during the IND Phase
  • A 1.4.2 Submission of Pharmacogenomic Data ta New NDA, BLA, or Supplement
  • A 1.4.3 Submission ta Previously Approved NDA or BLA
  • A 1.4.4 Compliance with 21 CFR Part 58
  • A 1.4.5 Submission of Voluntary Genomic Data from Application-Independent Research
  • A 1.5 Format and Content of a VGDS
  • A 1.6 Process for Submitting Pharmacogenomic Data
  • A 1.7 Agency Review of VGDSs
  • Glossary
• Index of Figures
  • Figure 2.1: Drug Discovery and Development Paradigm
  • Figure 2.2: Paradigm of Drug Discovery and Development Illustrating the Central and Essential Role of Biomarkers in Screening
  • Figure 2.3: Functional Genomic Process for Drug Development
  • Figure 2.4: Reimbursement for Diagnostics in Healthcare Decision Making
  • Figure 2.5: Market Growth and Evolution of Companion Biomarkers
  • Figure 2.6: Medical Product Development Models
  • Figure 2.7: Segmentation of the Biomarker Development Market
  • Figure 2.8: Medical Research in the U.S. Outpaces the Rest of the World
  • Figure 2.9: Worldwide Pharmaceutical Products Markets
  • Figure 2.10: Biomarkers Market Drivers
  • Figure 2.11: Challenges in the Biomarkers Space
  • Figure 2.12: FDA Co-Developed Products
  • Figure 3.1: Informatics Applications along the Drug Discovery Value Chain
  • Figure 3.2: Bioinformatics Software Flow Chart
  • Figure 3.3: Growth of GenBank, 1982 - 2008
  • Figure 3.4: Role of Bioinformatics in the Drug Discovery Value Chain
  • Figure 3.5: Challenges in the Study or Utilization of Proteomic Biomarkers
  • Figure 3.6: Challenges in the Study or Utilization of Companion Diagnostic Biomarkers
  • Figure 3.7: Top Unmet Needs in Products in the Biomarkers Space
  • Figure 4.1: Growth and Evolution of the Biomarker Space
  • Figure 4.2: Revenue Forecast Projections for Global Biomarker Markets by Segments, 2005 - 2012
  • Figure 4.3: Biomarker Discovery by Therapeutic Area
  • Figure 4.4: Kidney Biomarker Paradigm
  • Figure 4.5: Hepatic Biomarker Paradigm
  • Figure 9.1: IPRG Biomarker Qualification Process
  • Figure 9.2: Critical Path for Drug Development
  • Figure 9.3: Path for R&D Product Development
  • Figure 9.4: Dimensions of the Critical Path
  • Figure 9.5: FDA Interactions during Drug Development
  • Figure 9.6: Problem Resolution during the FDA Review Process
  • Figure 9.7: VGDS Process Flow
  • Figure 10.1: Discovery, Validation and Use of Biomarkers
• Index of Tables
  • Table 2.1: Utility of Biomarkers as Companion Diagnostics tDrug Development
  • Table 2.2: Biomarker End Points in Drug Development
  • Table 2.3: Value of Biomarkers in Phase II Clinical Trials
  • Table 2.4: Comparative Genome Sizes of Humans and Other Organisms
  • Table 2.5: Global Pharmaceutical Drug Sales, 2004 - 2012
  • Table 2.6: Worldwide Generic Pharmaceutical Drug Market, 2003 - 2012
  • Table 2.7: Worldwide OTC Pharmaceutical Drug Market, 2003 - 2012
  • Table 2.8: Worldwide Biopharmaceutical Drug Market, 2003 - 2012
  • Table 2.9: Top Ten Pharmaceutical Companies by Worldwide Sales, 2008
  • Table 2.10: Pharmaceutical Companies' Drug Sales as Percent of the Worldwide Market, 2008
  • Table 2.11: Threats tPharmaceutical Industry Productivity
  • Table 2.12: Competitive Forces Governing the Pharmaceutical Industry
  • Table 2.13: Time Line for Development of Companion Diagnostics
  • Table 2.14: Leading Therapy Classes for R&D, 2008
  • Table 2.15: Global Pharmaceutical Industry R&D Spending, 1995 - 2008
  • Table 2.16: Pharmaceutical R&D Expenditures by World Region, 1990 - 2006
  • Table 2.17: U.S. Government NIH Research Budget, 1995 - 2008
  • Table 2.18: Pharmaceutical Companies Ranked by Total R&D Expenditures, 2006
  • Table 2.19: Global Pharmaceutical Sales by Region, 2007
  • Table 2.20: World's Top-Selling Drugs, 2007
  • Table 2.21: Top Pharmaceutical Companies by Healthcare Revenue, 2008
  • Table 2.22: Leading Therapy Classes by Global Pharmaceutical Sales, 2007
  • Table 2.23: Leading Ten Therapeutic Classes by U.S. Sales, 2003, 2006 and 2007
  • Table 2.24: Top Ten Therapeutic Classes by U.S. Dispensed Prescriptions, 2006 and 2007
  • Table 2.25: Top Ten Brand Drugs by Retail Dollars, 2007
  • Table 2.26: Pharmaceuticals Industry Challenges
  • Table 2.27: Reasons for Developing Phase I Biomarkers
  • Table 2.28: Percentage of Non-Responders in Various Drug Classes
  • Table 2.31: High Profile Drug Withdrawals from the Marketplace
  • Table 2.30: Market Opportunities in Biomarkers
  • Table 2.31: Challenges for Market Adoption of the Various Biomarkers Tests
  • Table 2.32: Biomarkers Industry SWOT
  • Table 3.1: Worldwide Microarray Market Size, 2004 - 2012
  • Table 3.2: List of DNA Array Manufacturers
  • Table 3.3: U.S. qRT-PCR Market, 2007 - 2013
  • Table 3.4: Theranostics Technology Platforms-Timeline of Impact
  • Table 3.5: Impact of Personalized Medicine on Various Therapeutic Areas
  • Table 3.6: Hurdles in Biomarkers Development in Therapeutic Areas
  • Table 3.7: Data Source and Bioinformatic Investigations
  • Table 3.8: Drivers and Challenges of the Bioinformatics Industry
  • Table 3.9: Bioinformatics Activities, Sub-Activities and Key Players
  • Table 3.10: Concentration of Some Abundant Proteins, New Cancer Biomarkers Identified by SELDI-TOF, and Classical Cancer Biomarkers in Serum
  • Table 3.11: Device Submission Elements for the FDA
  • Table 3.12: Toxicogenomic Standards and Their Organizations
  • Table 3.13: Genomic and Proteomic Technologies
  • Table 4.1: Companion Biomarker Market Size, 2008 - 2013
  • Table 4.2: Kidney Biomarkers
  • Table 4.3: Herceptin Worldwide Sales, 1999 - 2007
  • Table 4.4: Characteristics of Different Cancer Biomarker Types and Associated Market Opportunities
  • Table 4.5: Segmentation of the Cancer Biomarker Market by Type of Cancer Biomarkers and Market Size
  • Table 4.6: Cancer Biomarker Market Estimates by Tissue of Origin
  • Table 4.7: Companies Developing New Proteomic Cancer Biomarker Technology Platforms
  • Table 4.8: Cancer Biomarkers Used tMaximize Likelihood of Response
  • Table 4.9: Biomarkers for Monitoring Therapeutic Effectiveness and Resistance
  • Table 6.1: Contract Research Companies
  • Table 8.1: Stakeholders in Biomarker Development
  • Table 9.1: Structure of the Critical Path
  • Table 9.2: Device Submission Elements for the FDA