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FDA is exploring policies to incorporate genomic information into the regulatory process.
The 50th anniversary of the discovery of the double helix in April 2003 also marked the completion of the Human Genome Project. Leaders of this landmark undertaking unveiled the finished version of the human genome sequence and mapped plans for tackling the next challenge: translating genomic research into medical treatments. The project identified more than 1400 disease genes and studied how human genetic make-up may affect ethical, legal, and social issues. Francis Collins, MD, PhD, director of the National Human Genome Research Institute (NHGRI) at the National Institutes of Health (NIH), declared that it was time to move from large-scale DNA sequencing to more specific research projects.
Collins and colleagues describe the immense task of translating initial genome research into medical treatments in a recent Nature article, A Vision for the Future of Genomics Research.1 This blueprint for future genomics research examines the resources and technological developments critical to developing powerful new therapeutic approaches to disease.
Further success in defining genetic networks and protein pathways and how they contribute to cellular and organism phenotypes is expected to contribute fundamentally to the design and testing of new therapies. One approach may be to explore gene variants that contribute to good health and resistance to disease. This could involve identifying a healthy cohort of individuals with unusually good health that could be compared with cohorts of individuals with diseases to examine genetic variants linked to disease.
To promote prevention and early detection of disease, scientists are exploring ways to develop genome-based approaches to predicting disease susceptibility and drug response, which may lead to development of individualized preventive medicine. Related research is focusing on further technological advances that would reduce the cost of genotyping. New molecular taxonomy may improve early detection of disease and could lead to more effective and less costly treatment. Such sentinel methods might include analysis of gene expression in circulating leukocytes, proteomic analysis of body fluids, and advanced molecular analysis of tissue biopsies.
Changes & challenges
Such activities raise new issues regarding the proper conduct of research involving genetic analysis of study participants and the resulting information. The ability to identify genetic traits of population groups and of individuals raises concerns about the need for community consultation and for obtaining consent from non-examined family members. An obvious issue is the potential for using genetic information to discriminate in employment and insurance coverage.
In addition, gene expression studies that predict toxicity of candidate compounds and identify biomarkers for toxicity and drug response may help define study populations and avoid overloading trials with inappropriate subjects. Although such approaches may reduce potential injury and make studies safer, they also may be criticized as attempts to merely improve study results.
Pharma companies now regularly examine how genomic data may provide clues about how and why individuals respond differently to a pharmaceutical. Pharmacogenomic (PG) research increasingly is being used to:
Such analyses have the potential to revise drug development processes and produce more effective, less toxic drugs more quickly and more efficiently, commented Janet Woodcock, MD, director of FDAs Center for Drug Evaluation and Research (CDER) at the April meeting of FDAs Science Board. However, FDA is concerned that companies are not presenting pharmacogenomic (PG) analysis to the agency for fear that it may prompt requests for even more data and only delay new product approval. Woodcock wants to clarify FDA regulatory policies to encourage PG analysis and also to gain access to information that could advance scientific discovery.
Woodcock seeks to overcome industrys dont tell attitude by issuing new guidances on how PG data relates to the regulatory process. She envisions policy statements on co-development of drugs and diagnostic tests and on general pharmacogenomic study standards and techniques. A key guidance will address when PG data will have a regulatory impact by identifying which PG studies should be submitted to FDA, and when study data will not be required in investigational or new drug applications. FDA says it is likely to request formal evaluation of PG information used in:
Alternatively, FDA wants to define a research information package that manufacturers would share with FDA, but would not have any impact on application review. Such data would be discussed separately by a new Interdisciplinary Pharmacogenomic Review Group (IPGRG) composed of representatives from all FDA Centers. Data collected for research use that would not affect regulatory and approval decisions might include:
Woodcock anticipates plenty of public discussion of PG issues through the guidance development process, beginning with a public workshop this fall. Manufacturers already are expressing concerns about new FDA rules in this area. Brian Spear, Phd, director of pharmacogenomics at Abbott Laboratories, told the Science Board that most pharma companies are exploring how PG analysis may help design clinical trials and interpret study data, but they fear that such information could be misinterpreted by regulatory officials if submitted as part of market applications. Spear expressed interest in FDAs idea of establishing a group of agency experts to review pharmacogenomic (PG) studies separately from the review process, but emphasized the need for clearer definition of pharmacogenomic data and research exemption. Without a more explicit policy, manufacturers will worry that FDA and other regulatory authorities could expand requirements later for what studies and data analysis they require for product registration. And while standardization of research approaches may appear useful, increased standardization also carries the risk of encouraging both regulators and manufacturers to favor certain procedures, which may inhibit innovation over the long run.
Another industry concern is that PG data could be used to narrow product marketing opportunities. A genetic study showing, for example, that 30% of patients could fail to respond to a certain treatment may lead to restrictive product labeling even if the drug appears safe and effective for a general population. Or, data indicating that certain patients respond to a treatment might lead to required diagnostic testing of participants in clinical trials and of potential subjects. In the end, industry willingness to underwrite more PG studies may prompt FDA to require genetic analysis as a regular component of drug development programs.
These are difficult issues, and FDA is building its internal capacity and expertise for analyzing and understanding genomic data, explained Frank Sistare, PhD, acting director of CDERs Office of Testing and Research. CDER has established an internal Nonclinical Pharmacogenomics subcommittee and is expanding reviewer training in this area. The panel will help develop standards for submission, review, and integration of pharmacogenomic (PG) data, and also will work with other government agencies and outside scientists to further develop these initiatives. FDA is seeking input from advisory committees and experts on ways to better understand and assess relevant information as genomics discoveries evolve.
The potential of pharmacogenomic research for making more new cost-effective therapies available to those patients who can benefit most from them has made PG development an important issue for FDA commissioner Mark McClellan. At the April Science Board meeting, he acknowledged that drug developers fear that data from molecular genomics doesnt fit the regulatory process and may raise red flags with reviewers. But he urged industry to share results with FDA so that these issues can be discussed openly and collaboratively.
1. Francis S. Collins, et al., A Vision for the Future of Genomics Research, Nature, 24 April 2003, 835847.