Use Case 33: History of drug approvals for analytics

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Use case summary


  • Need data on FDA's drug approval history to build models identifying optimized investing in pharma approvals, especially when multiple competitors for the same indication are present. The model is described in this paper: It requires downloading of an entire dataset going back as far in history as possible. Crucial to the analysis is to have the year of approval and disease indication, which are not easily extracted at this time.


  • Value to customer: ___
  • Value to industry/public: ___


  • University of Chicago (Booth School of Business, Harris School of Public Policy)

Current data and limitation

  • Data source: FDA’s Orangebook query tool
    • How it's used: To retrieve drug approval history
    • Limitations:
      • Query input is limited to very specific parameters (active ingredient, applicant holder etc), rather than allowing bulk download by year
      • Query results don't include disease indication or approval date
      • Only record detail contains approval date, making it difficult to extract on a larger scale


  • Fields:
    • Approval Date, Proprietary Name, Applicant, Disease Indication, Therapeutic Area
  • Update frequency: Monthly
  • Joins between datasets: _______
  • Lag time: _______
  • History: _______
  • Delivery mechanism: _______


Short term workaround

  • ___

Long term implementation

  • ___