Data-Driven Regulatory Science and Policy
While data is increasingly being used to support decision making in all fields, regulatory science and policy decisions could be further augmented by leveraging existing and hidden data sources. At Sanofi, I applied data science principles to analyze U.S. Food and Drug Administration policies and their results. In one project I identified a correlation between increased FDA regulations on type-2 diabetes clinical trials and decreased number of clinical trials, a proxy measure for capital investment, of drugs for the treatment of diabetes. Separately, I performed qualitative and quantitative analyses of FDA’s inconsistent use of patient experience data by the FDA in new drug approvals in their efforts to comply with Section 3001 of the 21st Century Cures Act. Also worked on methods to extract standardized data from regulatory PDF documents to support additional analyses.