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
Food and Drug Administration · Department of Health and Human Services · FOR-FD-24-003
In plain English
Food and Drug Administration (Department of Health and Human Services) has announced this as a forecast: an opportunity it expects to post. It is not open for applications yet.
Awards are up to $300,000 each and the agency expects to make 1 award.
Eligibility is listed as unrestricted (open to any type of applicant), subject to any clarification in the listing.
The listing says cost sharing or matching is not required.
Built only from the fields in the Grants.gov listing. Always confirm on the official listing.
Key facts
| Status | Forecasted: not open yet |
|---|---|
| Estimated posting date | Not stated |
| Estimated application due date | Not stated |
| Fiscal year | 2024 |
| Forecast posted | Nov 24, 2023 |
| Opportunity number | FOR-FD-24-003 |
| Agency | Food and Drug Administration (Department of Health and Human Services) |
| Funding instrument | Cooperative agreement |
| Category | Agriculture, Consumer Protection, Food and Nutrition |
| Opportunity category | Discretionary |
| Award ceiling (max per award) | $300,000 |
| Award floor (min per award) | $300,000 |
| Estimated total program funding | Not stated |
| Expected number of awards | 1 |
| Cost sharing or matching required | No |
| Assistance listing (CFDA/ALN) | 93.103 – Food and Drug Administration Research |
| Last updated on Grants.gov | Nov 24, 2023 |
Who can apply
Browse similar: Nonprofits · Small businesses · For-profit companies · State governments · Local governments · Tribal governments & organizations · Colleges & universities · School districts · Public housing authorities
- 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 with 501(c)(3) status (other than institutions of higher education)
- Nonprofits without 501(c)(3) status (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 above, subject to clarification in the listing)
Additional eligibility information (excerpt from the listing):
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 …
Description
Excerpt from the official forecast on Grants.gov (shortened; read the full text on 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.
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