Forecasted · Cooperative Agreement, Grant
Integrating Machine Learning with Computational Fluid Dynamics Models of Orally Inhaled Drug Products (U01) Clinical Trials Not Allowed
Food and Drug Administration, Department of Health and Human Services
Key facts
Copied from the official Grants.gov record. Last verified October 29, 2026.
- Program name
- Integrating Machine Learning with Computational Fluid Dynamics Models of Orally Inhaled Drug Products (U01) Clinical Trials Not Allowed
- Issuing agency
- Food and Drug Administration (Department of Health and Human Services)
- Opportunity number
- FOR-FD-24-001
- Funding type
- Cooperative Agreement, Grant
- Funding purpose
- Health, Food and Nutrition
- Status
- Forecasted
- Application deadline
- Forecasted · no application dates yet
- Published award range
- Not published by the agency
- Estimated total program funding
- $600,000
- 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
- Relevant to
- Businesses and NonprofitsHow we determined this: 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/351059 ↗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 351059 · Funding opportunity number FOR-FD-24-001
- Posted
- November 20, 2023 · Source last updated November 20, 2023
- Last verified
- October 29, 2026 (against Grants.gov)
- Data completeness
- 75% of key fields published by the sourceNot published: published funding range, eligibility criteria text, application dates.
- Record confidence
- mediumforecast — dates and amounts are agency estimates.
Description (from the official listing)
Computational fluid dynamics (CFD) has played a crucial role in providing an alternative bioequivalence (BE) approach for generic orally inhaled drug products (OIDPs), in addition to comparative clinical endpoint or pharmacodynamic BE studies, as a relatively cost- and time-efficient complement to benchtop and clinical experiments that has been widely used in developing and assessing generic inhaler devices. However, despite the advances in the power of modern computers, there are still some bottlenecks in using CFD due to computational time, limited grid resolution, pre- and post-processing of large simulation data sets, model parameter estimations, and uncertainty quantifications. Machine learning (ML) has been gaining more attention as a potential tool to alleviate such limitations that arise in CFD. The purpose of this grant is to develop a methodology to integrate ML with CFD models of OIDPs to promote alternative BE studies to enhance and accelerate the development and approval of generic OIDPs.
Agency contact
Terrin Brown Grants Management Specialist
terrin.brown@fda.hhs.gov