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Companion Biomarkers in Drug Development

TriMark Publications
April 1, 2009
320 Pages - SKU: TRI2207024

Abstract Table of Contents Related Reports

Companion Biomarkers in Drug Development

The term “companion biomarker” means that a particular diagnostic test is specifically linked to a therapeutic drug either in drug development or in the clinic. Biomarkers of disease have long played an important role in diagnostic medicine as evidenced by the intense use of specific clinical laboratory tests in the diagnosis of disease. Biomarkers can be used in five very distinct ways in drug development: 1) companion biomarkers can be correlated with biological events during drug development in order to validate drug targets or to predict drug response; 2) biomarkers can be used as companion diagnostics in drug development to characterize patient populations in order to better understand the extent to which new drugs reach intended therapeutic targets can alter proposed therapeutic pathways and achieve successful clinical outcomes; 3) biomarkers can be used to stratify patient populations for drug response in primary prevention or disease-modification studies, particularly in specific clinical areas such as neuron degeneration and cancer; 4) clinically useful biomarkers are becoming increasingly useful to make proper therapeutic decisions regarding candidate drugs; and 5) clinically useful biomarkers are becoming increasingly required by the FDA and other outside authorities to make proper regulatory decisions regarding candidate drugs. This TriMark Publications report describes new biomarker technology platforms developed for the analyses of drug targets that are connected to the effectiveness of therapeutic agents in a clinical setting. The emphasis is on those companies that are actively developing and marketing new companion diagnostic tests for performing biomarker tests during drug development, as opposed to the more routine and clinically accepted companion markers that are manufactured and marketed by large diagnostic companies for routine clinical use.

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; 2.2 Biomarkers in Different Phases of Drug Development; 2.3 Drug Targets; 2.4 Biomarkers in Drug Discovery, Development and Clinical Diagnostics; 2.5 World Pharmaceutical Markets; 2.9 Future Developments
3. Biomarker Development Tools: 3.1 New Technologies in Functional Genomics; 3.2 Overview of Microarrays; 3.3 Theranostics; 3.4 Pharmaceutical Development and Bioanalytical Services; 3.5 Metabolomics in Drug Discovery; 3.6 Bioinformatics; 3.7 Biomarkers and Proteomics; 3.8 Toxicogenomics
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; 4.9 Targeting Hepatotoxicity; 4.10 Biomarker Application in Oncology Clinical Development; 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; 5.2 Molecular Imaging; 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; 5.7 IT Solutions for Imaging Biomarkers in Biopharmaceutical Research and Development
6. Clinical Biomarkers Improving Trial Design: 6.1 Strategies to Improve the Measurement of Biomarkers for Drug Trials; 6.2 Key Opportunities in Biomarker Discovery, Development and Commercialization; 6.3 What Strategies Help Translate Biomarkers from Preclinical to Clinical Development?; 6.4 How Should Biomarker Data Be Compared to “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; 7.3 Improving the Efficacy of Clinical Surrogate End Points Using Biomarkers; 7.4 Surrogate Endpoint Validation; 7.5 Effective Use of Surrogates; 7.6 Conclusions
8. Market Size, Collaborations and Future Directions for Companion Diagnostics: in Drug Development; 8.1 Strategies to Improve the Measurement of Biomarkers for Drug Trials; 8.2 What is the Best Balance of Resources to Have the Most Efficient Pathway to Develop 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; 9.2 FDA Perspective of Biomarkers in Clinical Trials; 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; 9.8 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 to Determine; 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 Do Business Strategies, Such as Those Relating to Acquisition, 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 to Acquisition 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 to Clinical 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 to Reduce 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 to Maximize 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 BioMérieux; 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 Dako A/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 Meso Scale 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 Perbio Science; 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 Textco BioSoftware; 11.193 TG Services; 11.194 Thermo Fisher 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 to Sponsors 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 to a New NDA, BLA, or Supplement; A 1.4.3 Submission to a 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 to Drug 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 to Pharmaceutical 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 to Maximize 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

Companion Biomarkers in Drug Development

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