The Impact of Genomics on Clinical Trials and Medical Practice: A CHA Advances MONITOR Series Report

The Impact of Genomics on Clinical Trials and Medical Practice evaluates the potential of clinical genomics to transform drug development and the practice of medicine. The report projects significant growth opportunities in this field, balanced with a realistic assessment of the challenges and hurdles to bringing clinical genomics to mainstream medicine.

Clinical genomics is the application of large-scale, high-throughput genomics technologies in clinical settings, such as clinical trials or primary care of patients. Clinical genomics promises to allow a molecular understanding of disease and drug response, with benefits in all areas of medicine.

Contributing to the growth of genomics, in 2005 the FDA issued guidelines for applications of genomics in drug development, with the stated hope that genomics will improve the safety and effectiveness of medicines. Given this mandate, clinical genomics applications appear to have crossed a threshold with the recent approval of several clinical genomics products. These approvals are expected to provide important precedents for other product approvals in the near future.

Examples reviewed in the report include the following:

Roche Diagnostics’ AmpliChip Cytochrome P450 Genotyping Test: In 2004 this test, a DNA chip that identifies variations in two genes affecting response to a wide variety of drugs, became the first microarray approved for treatment decisions by the FDA.
Third Wave Technologies’ Invader UGT1A1 Test: This test for detecting heightened risk of adverse reaction to the chemotherapy drug irinotecan was FDA-approved in 2005 as the first pharmacogenetic companion diagnostic paired with a specific drug therapy.

Genomics applications in clinical trials are also dramatically rising. It is now estimated that about 20% of U.S. clinical trials use some sort of genomics approach, with the highest percentage in oncology trials. While this trend is expected to accelerate during the next few years, the field still faces considerable regulatory, technical, economic, and sociological hurdles. The full promise of clinical genomics applications may not be fully realized for at least another ten to fifteen years. However, as genomics transitions away from primarily research to more clinical applications, the field will be ripe with business opportunities and the report examines some of the business and strategic factors relevant to the further adoption of genomics technologies in clinical trials and medical practice.

This report is part of the CHA Advances MONITOR series. The CHA Advances MONITOR series singles out markets, technologies, and industry sectors that are characterized by propulsive growth and by the potential to change the basis of competition in the pharmaceutical industry. We plan to visit these subjects approximately every 2 years.

About the Author

Gwen Acton, Ph.D., is president of Vivo Group, a consulting firm specializing in evaluation and management of genomics and life science technology. Prior to this, Dr. Acton served as Director of Scientific Development at the Whitehead Institute for Biomedical Research, and ran the operations of the Functional Genomics Program at the Whitehead Institute/M.I.T. Center for Genome Research. Dr. Acton received a doctorate in molecular biology and genetics from M.I.T. and served as a faculty member at Harvard University in the Department of Molecular and Cellular Biology.

Chapter 1. Introduction: 1.1. Overview; 1.2. The Impact of Genomics in the Clinic; 1.3. Impact of Data from the Human Genome; 1.4. The Promise of Clinical Genomics; 1.5. Challenges in the Field
Chapter 2. Applications of Genomics in Clinical Trials and Medicine: 2.1. Prediction, Detection, and Diagnosis of Disease; 2.2. Predicting Response to Drugs; 2.3. Factors Influencing Response to Drugs; 2.4. Personalized Medicine; 2.5. Toxicogenomics; 2.6. Determining Risk of Disease; 2.7. Gene Therapy; 2.8. Identifying Individuals; 2.9. Proteomics
Chapter 3. Genomic Technologies for the Clinic: 3.1. Overview; 3.2. Detecting DNA Variation; 3.3. SNP Genotyping Methods; 3.4. Gene Expression Detection; 3.5. RNA Interference; 3.6. Other Technologies
Chapter 4. Advances in Clinical Genomics Applications: 4.1. Overview; 4.2. Toxicogenomics; 4.3. Clinical Trials; 4.4. Clinical Oncology; 4.5. Infectious Diseases; 4.6. Newborn Screening; 4.7. Genomics and Race; 4.8. Genomics and Drug Labeling
Chapter 5. Business and Strategic Factors: 5.1. Overview; 5.2. Patient Stratification; 5.3. Scientific Issues; 5.4. Standardization and Quality Control; 5.5. Physician and Payer Response; 5.6. Drug-Diagnostic Codevelopment: Theranostics; 5.7. The Regulatory Environment; 5.8. Cost-Benefit Analysis; 5.9. Niche Markets for Clinical Genomics
Chapter 6. Expert Interviews: Edward Abrahams, PhD, Executive Director, Personalized Medicine Coalition (PMC); Charles R. Cantor, PhD, Chief Scientific Officer SEQUENOM; Mickie Henshall, Product Manager, Molecular Diagnostics, Illumina, Inc.; William Craumer, Director, Corporate and Marketing Communications, Illumina, Inc.; Mark A. McCamish, MD, PhD, Chief Medical Officer, Perlegen Sciences
Chapter 7. Selected Company Profiles: Affymetrix; Agendia; Alnylam Pharmaceuticals; Applied Biosystems Group (ABI); Agilent; Beckman Coulter, Inc.; Brinkmann Instruments (A Member of the Eppendorf Group); CombiMatrix Corporation; DnaPrint Genomics Inc.; Encode (Subsidiary of deCODE)6; Epigenomics AG; ExonHit Therapeutics; Genaissance Pharmaceuticals; Gene Logic; Genomic Health; Genpathway Inc.; Gentris; Iconix Pharmaceuticals, Inc.; Illumina; Invitrogen; Myriad Genetics; Nanogen; NitroMed, Inc.; PathWork Informatics; Perlegen Sciences; PTC Therapeutics, Inc.; Roche Molecular Diagnostics; SEQUENOM, Inc.; Sirna Therapeutics; Third Wave Technologies, Inc.; Vanda Pharmaceuticals
References
Index
List of Tables: Table 1.1. Stages of Clinical Trials; Table 2.1. Genomic Features with Clinical Applications; Table 2.2. Genetic Pathways That Could Alter Drug Efficacy and Safety: ADME; Table 2.3. Classes of Genetic Variation in Drug Metabolism; Table 2.4. Examples of Cytochrome P450 Gene Variation and Drug Interaction; Table 2.5. Examples of Genetic Variation in Drug Targets Affecting Drug Response; Table 2.6. Selected Toxicogenomics Databases; Table 2.7. Examples of Monogenic Diseases for Which Clinical Tests Are Available; Table 2.8. Examples of Genes Contributing to Complex Diseases; Table 2.9. Cancers with a Strong Genetic Component; Table 3.1. Types of DNA Variation; Table 3.2. Factors Influencing Genotyping Costs; Table 3.3. Criteria for Evaluating SNP Genotyping Accuracy; Table 3.4. Steps in Microarray Experiments; Table 3.5. Informatics Issues Associated with Microarrays; Table 3.6. Selected Companies Marketing Microarrays or Related Tools or Services; Table 4.1. Correlation of UGT1A1 Variants with Risk of Toxicity; Table 4.2. Selected Assays Used to Screen Newborns for Genetic Diseases; Table 4.3. Examples of Drugs Reported to Evoke Different Responses in Different Racial or Ethnic Groups; Table 4.4. Selected Drugs for Which the Target Population May Be Determined by Genetic Testing (U.S. prescribing information); Table 4.5. Prescribing Information for Drug-Metabolizing Enzyme Genotypes; Table 5.1. Savings Resulting from Patient Stratification in a Breast Cancer Study; Table 5.2. Efforts to Standardize Gene Expression Data; Table 5.3. Factors Increasing or Decreasing Costs Associated With Genomic Technology; Table 5.4. Quick Reference on Pharmacogenomic Submissions; Table 5.5. Framework for Evaluating the Potential Cost-Effectiveness of Clinical Genomics Therapies
List of Figures: Figure 1.1. Preclinical Versus Clinical Applications of Genomics; Figure 1.2. Personalized Medicine; Figure 1.3. Taking Genomics to the Clinic; Figure 2.1. Estimated U.S. Cancer Deaths by Type, 2005; Figure 3.1. Single Nucleotide Polymorphisms; Figure 3.2. A Haplotype Block; Figure 3.3. Functional Genomic Analysis of Gene Expression; Figure 3.4. Microarray Analysis; Figure 3.5. Diagram of Short Interfering RNAs; Figure 4.1. Distribution of Drug-Metabolizing Enzymes in the Population; Figure 4.2. Roche Diagnostics' AmpliChip CYP450; Figure 4.3. Effect of UGT1A1 on Irinotecan Metabolism; Figure 4.4. Distribution of TPMT Activity in Unrelated Adults; Figure 4.5. Estimated Growth of Genomics in U.S. Clinical Trials; Figure 4.6. Applications of Genomics in Drug Development; Figure 4.7. Application of Gene Expression Testing in Breast Cancer; Figure 5.1. How Patient Stratification Using Genomics Can Be Beneficial; Figure 5.2. Impact of Various Factors on Variation of Patient Response to Warfarin; Figure 5.3. Breakdown of Spending on Health Care in the United States, 2002; Figure 5.4. Codevelopment of Drugs and Diagnostics; Figure 5.5. Current and Possible Future Applications of Diagnostics; Figure 5.6. Limits to Genomic Predictions of Drug Efficacy; Figure 5.7. RNAi Market Forecast