We’re only a few weeks into the new year, and the Food and Drug Administration will soon make a decision that will affect pharmaceutical regulation for decades.
Last year, after failing an FDA-required futility test, Biogen abandoned its efforts to develop an Alzheimer’s treatment named aducanumab. However, after conducting an analysis using an expanded dataset, Biogen found the drug successfully curbed memory loss and helped maintain cognitive abilities
Biogen’s findings come at a critical time. About ten percent of the U.S. senior population suffers from Alzheimer’s. Medical researchers and drug developers have not been able to develop a new treatment for the disease over the past ten years. As one researcher notes, “People affected by Alzheimer’s have waited a long time for a life-changing new treatment, and this exciting announcement offers new hope that one could be in sight.”
But before aducanumab can reach patients, the FDA must decide whether Biogen’s findings from its expanded data set provide enough evidence for approval. Normally the agency requires drugs to pass numerous positive trials. Biogen is providing one, and it comes from combining numerous tests across various trials.
It seems unlikely the FDA will deny Biogen’s request to reconsider aducanumab for approval. As one STAT article headlines, “Biogen’s top scientist nearly dares FDA not to approve Alzheimer’s drug.” Further, the agency has approved drugs that did not meet the usual approval standards based on medical need and availability of treatment options.
From a policy standpoint, approving aducanumab would provide other drug producers with a way to utilize big data analysis to navigate through the FDA’s drug approval process.
Data analysis in healthcare uses various statistical techniques and empirical methods to find important relationships from large, complex data sets. The private sector currently uses findings from big-data analytics to streamline healthcare profiles, cut overhead costs, and better manage patient care. Drug providers use similar procedures to manage R&D costs and find new blockbuster drugs to help patients.
The FDA has previously considered implementing findings from big-data analysis in its approval process. Unfortunately, it has failed to implement meaningful changes to its approval process. Its decision whether to approve aducanumab based on Biogen’s analysis would be a tremendous step for the FDA to embrace big data. Although the analysis is complex, the decision should be a no-brainer.