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 (U01) Clinical Trial Not Allowed
ID: 351805Type: Posted
Overview

Buyer

Food and Drug Administration (HHS-FDA)

Award Range

$0 - $300K

Eligible Applicants

Unrestricted

Funding Category

Food and Nutrition

Funding Instrument

Cooperative Agreement

Opportunity Category

Discretionary

Cost Sharing or Matching Requirement

Yes
Timeline
  1. 1
    Forecast Posted Not available
  2. 2
    Forecast Due Not available
  3. 3
    Posted Jan 15, 2024 12:00 AM
  4. 4
    Due Apr 8, 2024 12:00 AM
Description

The Food and Drug Administration (FDA) has posted a federal grant opportunity titled "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 (U01) Clinical Trial Not Allowed". This funding opportunity falls under the category of Food and Nutrition.

The purpose of this grant is to develop and test an AI- or ML-based algorithmic Real-World Data (RWD) model for post-market surveillance of complex generic drug products. Complex generic drug products are becoming more prevalent in the generic marketplace and may have distinct user interface differences compared to reference listed drug (RLD) products. Therefore, a modernized post-market surveillance approach is needed to compare clinical outcomes between complex generic products and their corresponding RLD products. This will help monitor for potential issues with therapeutic equivalence and inform regulatory decision making.

The use of real-world data combined with machine learning (ML) and/or artificial intelligence (AI) can efficiently identify post-market signals in an automated and repeatable fashion. This will facilitate timely regulatory action. The FDA is seeking proposals to develop and test an AI- or ML-based algorithmic RWD model that can assess post-market clinical outcomes in patients switching among therapeutically equivalent complex generic drug products and reference listed drugs.

The grant has an award ceiling of $300,000 and there is no cost sharing or matching requirement. The estimated total program funding is also $300,000. The FDA expects to make one award for this grant opportunity. The closing date for applications is April 8, 2024, and the archive date is April 30, 2024.

For more information and to access the funding opportunity announcement, please visit the following link: RFA-FD-24-007 Funding Opportunity Announcement. If you have any questions, you can contact Terrin Brown, the grantor, at terrin.brown@fda.hhs.gov.

Point(s) of Contact
Files
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