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Companion Biomarkers in Drug Development

Published by: TriMark Publications

Published: Apr. 1, 2009 - 320 Pages


Table of Contents


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 to Reduce 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 to Replace 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 Macro Trends 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 to Use 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 to Bioinformatics 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 to Biomarker Discovery

3.7.2.1 Challenges Facing Biomarker Developers

3.7.3 Limitations of Proteomic Approaches to Biomarker 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 to the 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 to Toxicogenomics

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 into Oncology Drug Development

4.10.2.1 Lilly to Co-Develop Companion IVDs for Cancer Drugs

4.10.2.2 Celera to Work on Companion Diagnostics for Merck Cancer Drugs

4.10.2.3 BioMérieux to Develop 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 to Improve 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 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

7.2.1 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 to Improve 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 To Reduce 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 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

9.1.1 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 to New 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 to the 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 to Approval

9.7.18 Reducing Delays in Medical Device Reviews

9.7.19 Reducing Delays in Animal Drug Reviews

9.7.20 Quality Systems Approach to Medical 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 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

Abstract

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.

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