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

Key facts

Copied from the official Grants.gov record. Last verified October 29, 2026.

Program name

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

Issuing agency

Food and Drug Administration (Department of Health and Human Services)

Opportunity number

FOR-FD-24-003

Funding type

Cooperative Agreement

Funding purpose

Agriculture, Food and Nutrition, Consumer Protection

Status

Forecasted

Application deadline

Forecasted · no application dates yet

Published award range

Up to $300,000

Expected number of awards

1

Cost sharing or match required

No

Eligible applicants (official categories)

• State governments
• County governments
• City or township governments
• Special district governments
• Independent school districts
• Public and State controlled institutions of higher education
• Native American tribal governments (Federally recognized)
• Public housing authorities/Indian housing authorities
• Native American tribal organizations (other than Federally recognized tribal governments)
• Nonprofits having a 501(c)(3) status with the IRS, other than institutions of higher education
• Nonprofits that do not have a 501(c)(3) status with the IRS, other than institutions of higher education
• Private institutions of higher education
• For profit organizations other than small businesses
• Small businesses
• Unrestricted (open to any type of entity, subject to any clarification in Additional Information on Eligibility)

Relevant to

Businesses and NonprofitsHow we determined this: Grants.gov lists eligibility as Unrestricted. Grants.gov eligibility includes small businesses or for-profit organizations. Grants.gov eligibility includes nonprofit organizations.

Geographic restrictions

None stated in structured data (federal opportunities are often nationwide). Check the eligibility details and full announcement for any limits.

Assistance Listing (CFDA)

93.103

Official source

View on Grants.gov ↗

Application URL

www.grants.gov/search-results-detail/351125 ↗Apply through Grants.gov (Workspace) using the application package on the official listing, unless the full announcement names a different submission system.

Source identifier

Grants.gov opportunity ID 351125 · Funding opportunity number FOR-FD-24-003

Posted

November 24, 2023 · Source last updated November 24, 2023

Last verified

October 29, 2026 (against Grants.gov)

Data completeness

92% of key fields published by the sourceNot published: application dates.

Record confidence

mediumforecast — dates and amounts are agency estimates.

Eligibility details (from the agency)

Applicant organizations may submit more than one application, provided that each application is scientifically distinct. The FDA will not accept duplicate or highly overlapping applications under review at the same time per 2.3.7.4 Submission of Resubmission Application. This means that the NIH or FDA will not accept:•A new (A0) application that is submitted before issuance of the summary statement from the review of an overlapping new (A0) or resubmission (A1) application.•A resubmission (A1) application that is submitted before issuance of the summary statement from the review of the previous new (A0) application.•An application that has substantial overlap with another application pending appeal of initial peer review (see 2.3.9.4 Similar, Essentially Identical, or Identical Applications).

Description (from the official listing)

Complex generic drug products represent an increasing share of the generic marketplace and may have distinct user interface differences compared to reference listed drug (RLD) products. A modernized post-market surveillance approach is needed to compare clinical outcomes between complex generic products and their corresponding RLD products to monitor for potential issues with therapeutic equivalence and to inform regulatory decision making. Real-world data (RWD) combined with machine learning (ML) and/or artificial intelligence (AI) could help to identify post-market signals efficiently in an automated and repeatable fashion, facilitating timely regulatory action. The purpose of this funding opportunity is to develop and test an AI- or ML-based algorithmic RWD model for post-market surveillance of complex generic drug products.

Agency contact

Terrin Brown Grantor
terrin.brown@fda.hhs.gov