There are provisions for accelerated approval by the Federal Drug Administration (FDA) of new drugs for patients with serious illnesses. As an example, Genentech’s Avastin for metastatic breast cancer received accelerated approval on February 22, 2008. On June 29, 2011, the FDA’s Oncologic Drugs Advisory Committee recommended 6 to 0 that the approval be withdrawn. As of this posting, the FDA has not announced a decision.
The approval was based on standard research for this type of medicine and showed sufficient benefit that accelerated approval was granted. Subsequent similar studies raised questions about effectiveness and risks that led to the recommendation for withdrawal.
Standard research methods have been tested and generally provide the required information for FDA action. However, samples are small—the largest sample in this series of tests was fewer than 800. Most of the critical measures are in the low single digit percentages which mean that errors induced by small sample size can be significant.
Recent advances in electronic healthcare records (EHRs) are creating a new parallel path to provide much larger samples to assist in the assessment of traditional research. What ERHs lack in precision, they make up in breadth in both the research target group and control groups. This greater breadth allows for analysis of factors that may contribute to adverse events or produce higher rates of effectiveness among sub-groups in the target population.
There are, according to material presented at the hearings, 45,000 patients diagnosed with HER2-negative matasticised breast cancer every year. All of these patients have healthcares records although most of them are probably not yet in electronic format. Reasonable projections based on recent history and the continued efforts by the US government to encourage the use of electronic records suggest that EHR sample sizes for a population of this size could be well over 1,000 records in the immediate future and in the foreseeable future significantly greater.
Research based on EHRs is relatively inexpensive compared to traditional research because the cost of data collection has already been covered. There are additional advantages as outlined in EHRs Meet Pharma’s Need for Longitudinal Research. I am not suggesting replacing traditional research with EHR based research, but rather, doing both in parallel. A model of such a testing program might look like this:
During Drug Development: Use EHR based research to assist in defining the scope and nature of the potential market for a new drug as soon as there is high probability that a request for FDA accelerated approval will be made. Begin to build a control group that includes all potential variables including current and prior medications used for the target disease. Maximize the size of the control group to minimize sampling error there. Include relevant findings from this analysis as part of the request for accelerated approval and agree to continue the research after approval with the addition of patients for whom the product is prescribed.
At Launch: Begin tracking weekly for market research to gain insights about who is prescribing it and for which patients. Also track any adverse events to manage risk.
Three To Six Months Out: Reduce the frequency of reports to monthly or quarterly depending on market research needs and medical research requirements. Look for clusters of adverse results and clusters of effectiveness. Expand the control group with sub-groups to maintain sampling validity as smaller clusters are explored in depth. Explore options to reduce adverse effects including notices. Explore opportunities to focus marketing aimed at other clusters to improve overall performance in terms of satisfying FDA requirements and improving market penetration.
Map the EHR results to those from traditional research to build credibility for the smaller sample sizes of the traditional research or to explain any differences and their significance for FDA review and approval.
After FDA Approval: Continue the EHR research to manage risks associated with adverse events, continue to develop the market, and find new opportunities for new or improved products.
The rapid evolution and implementation of Web based, fully networked, database driven EHRs like Practice Fusion are creating a new set of tools to facilitate accelerated release and post-release research leading to final approval.
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