Originally published July 25.
In a document outlining its future research and scientific needs, the US Food and Drug Administration's Center for Drug Evaluation and Research has acknowledged that it needs to improve its understanding of biomarkers to foster greater advanced in personalized medicine.
"We need to improve our understanding of the safety and efficacy of pharmacotherapy as it applies to individual patients and patient subsets," the agency states in the report released this week, titled "Identifying CDER's Science and Research Needs."
The report calls for the identification and validation of efficacy and safety biomarkers. "More generally, we need to identify particular characteristics (genetic/genomic or proteomic) that predict favorable or unfavorable responses," the report states, adding that "robust" statistical methods are needed to help validate the utility of biomarkers in gauging best responders in drug trials.
The report notes that biomarkers "are currently guiding decisions in a number of clinical domains important for pharmacotherapy, including dosing, patient selection for efficacy, and patient exclusion for safety," but adds that additional biomarker development is necessary "for a broad range of applications related to the development of new drugs, as well as to their appropriate postmarket use." In particular, the report states, "we need approaches that can identify additional biomarkers that predict drug-induced organ and system toxicities and those that may predict favorable responses."
The report, which is focused on CDER-specific regulatory science goals, follows the FDA's release of a dossier in October that laid out its agency-wide regulatory science priorities (PGx Reporter 10/06/2010) and precedes the release of a "cross-cutting strategic plan for regulatory science" that FDA said it aims to release "soon." Ultimately, by publicly outlining its research needs and main areas of focus, the agency is hoping to attract research collaborations with external partners to advance its goals.
CDER's Science Prioritization and Review Committee interviewed more than 200 officials from various offices at the agency in order to identify the questions that the drug division needed to address in terms of regulatory science. FDA Commissioner Margaret Hamburg championed the need to improve regulatory science soon after her appointment in 2009.
The committee asked FDA officials to identify scientific challenges that are dealt with currently on a case-by-case basis that should have a more formalized approach; scientific issues that are challenging across divisions at the agency; and emerging scientific challenges. Based on the survey results, leadership at CDER identified seven major areas that needed improvement, including the analyses of postmarket data; risk management strategies; regulatory communications; product quality performance; predictive models; design, analysis, and monitoring of clinical trials; and individualization of patient treatment.
Throughout the report, there are several areas where the agency identifies the need to gather pharmacogenomics data to improve pre- and postmarket evaluation of drugs in patient subsets. For example, in a section discussing postmarket surveillance of drugs, the agency notes that new data sources, such as "genetic/genomic data to better understand response to drug products in specific populations," can be valuable in supporting regulatory analyses of drugs after market launch.
CDER outlines the need to investigate the strengths of novel clinical trial models, such as adaptive designs, N-of-1 trials, and non-inferiority trials to figure out when best to apply these strategies in drug development. Personalized medicine advocates within the FDA and outside the agency have often acknowledged the need for new clinical trial models, beyond the prospective, randomized-controlled trial, to address the unique challenges of developing drugs targeted at smaller, genetically defined patient populations.
While CDER notes in the report that retrospective analysis may sometimes be useful for defining patient subpopulations, it favors prospective analysis when it comes to validating predictive biomarkers that will be used to guide therapy.
Retrospective analysis of data from clinical trials "may help to better define the use conditions and doses for certain patient populations, may lead to identification of predictors of disease response or recurrence, or improve the design of future trials," the report states, adding that it would also help in investigating relationships between biomarkers and outcomes.
For studies from submissions that contain genetic/genomic information, additional considerations would include whether the spectrum of response and genetic variability is adequate to discern patterns. "Nonclinical studies could be retrospectively evaluated for related safety signals in subsequent clinical trials," the agency notes in the report. However, "the process of qualifying new biomarkers may require prospective studies to verify their sensitivity and specificity, and to assess the predictive nature of profiles versus single markers."
The agency notes that large collaborations will be key in advancing predictive biomarkers for differential drug dosing and selecting best responders. "By partnering with academics, industry, other government agencies and nonprofits we can facilitate the identification and validation of novel biomarkers."