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Coming Soon·Opens soon·Synced from source July 6, 2026

Integrating Machine Learning with Computational Fluid Dynamics Models of Orally Inhaled Drug Products (U01) Clinical Trials Not Allowed

Food and Drug Administration

Posted
Oct 23, 2025
Closes
No deadline published by the funder
Last verified
Jul 6, 2026

Classification and identifiers

Solicitation number
FOR-FD-24-001
Assistance listing (CFDA)
93.103

Amount

Amount not published by the funder

Who can apply

Public universitiesFor-profitsNonprofits (non-501c3)Special districtsLocal governmentsSmall business

State governments, Independent school districts, County governments, Private institutions of higher education, Public and State controlled institutions of higher education, Nonprofits that do not have a 501(c)(3) status with the IRS, other than institutions of higher education, For profit organizations other than small businesses, Public housing authorities/Indian housing authorities, Small businesses, 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, City or township governments, Native American tribal governments (Federally recognized), Special district governments…

About this opportunity

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...

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