FOR-FD-24-003: FDA Grant for Real-World Data Analysis of Complex Generic Drug Products

The Food and Drug Administration (FDA) has announced a grant opportunity under the number FOR-FD-24-003, focusing on the utilization of real-world data (RWD) and algorithmic analyses to assess post-market clinical outcomes in patients switching among complex generic drug products and reference listed drugs. This cooperative agreement is designed to modernize post-market surveillance approaches for complex generic drugs, a growing segment in the pharmaceutical market. It aims to ensure therapeutic equivalence and inform regulatory decision-making by using advanced technologies like machine learning (ML) and artificial intelligence (AI).

Eligibility for this funding opportunity is broad, encompassing a variety of entities including state governments, educational institutions, small businesses, non-profits, and others. The primary objective of this grant is to develop and test an AI- or ML-based algorithmic RWD model that can efficiently and automatically identify post-market signals, thus facilitating timely regulatory actions. With an award ceiling of $300,000, this funding initiative underscores the FDA’s commitment to leveraging cutting-edge technology in ensuring the safety and efficacy of generic drug products. This approach is critical in the context of the complex generic drug market, where subtle differences in user interfaces compared to reference drugs might impact clinical outcomes. The initiative represents a significant step in enhancing the FDA’s capabilities in monitoring and ensuring public health safety in the rapidly evolving landscape of generic medications.