Utilizing Real-World Data and Algorithmic Analyses to Assess Post-Market Clinical Outcomes in Patients Switching Amongst Therapeutically Equivalent Complex Generic Drug Products and Reference Listed Drugs

Funding Opportunity Number: RFA-FD-24-007

Deadlines:
February 15, 2024
March 31, 2024

Award Amount: Up to $300,000

Background

Post-marketing surveillance of generic drugs is conducted to assess for drug quality and therapeutic equivalence safety issues. Current post-marketing surveillance for generic drug products relies on adverse event reporting from healthcare professionals, consumers, and manufacturers. Limitations of the current reporting-based approach for generic drugs include potential biases in reporting and a small dataset relative to the number of dispensed prescriptions. FDA published a Draft Guidance for Industry on Best Practices in Drug and Biological Product Postmarket Safety Surveillance for FDA Staff in November of 2019 (https://www.fda.gov/media/130216/download. When final, it will represent the Agency’s current thinking on this topic. The draft guidance identifies a specific difficulty with the reporting approach for generic drugs in differentiating between the innovator and generic product, as well as differentiating between generic products in situations where there is more than one approved generic. The draft guidance also notes that there are specific post-marketing concerns for complex generic drug products due to differences in the user interface compared to the innovator. These products include drug-device combination products, oral products with modified-release mechanisms, narrow therapeutic index products, and products without a highly correlated pharmacokinetic – pharmacodynamic relationship. The combination of increasing market availability of complex generic drugs and limitations of the current reporting-based surveillance approach may lead to less effective post-market surveillance of these products.

Objectives

The objective of this funding opportunity is to explore the use of RWD to compare clinical outcomes in patients who switch between a complex generic drug product(s) and the reference listed drug(s). The goal of this research is to develop an RWD algorithmic model to support generic product post-market surveillance that supplements the current reporting approach, facilitates timely and definitive regulatory action, and is able to be implemented in an automated and repeatable fashion.

Detailed Description

Meeting the objective of this funding opportunity will require familiarity with real-world datasets and expertise in the analysis of RWD, including an understanding of its strengths and limitations. Additionally, it is necessary to acquire and test AI/ML systems to develop an algorithmic approach to analyzing RWD in a repeatable fashion.

The intent of the cooperative agreement is that the award recipient will work collaboratively with FDA scientists to refine the research strategy proposed by the applicant, develop study designs and protocols, orchestrate study conduct, analyze data and publish the results. The final research strategy would be developed based upon the innovation and expertise of the award recipient, in collaboration with feedback from the FDA to ensure that the study designs are aligned with the objectives of the award.

 

For more information, please see the opportunity website.