Integrating Machine Learning with Computational Fluid Dynamics Models of Orally Inhaled Drug Products (U01) Clinical Trials Not Allowed
Food and Drug Administration
Description
This grant opportunity aims to develop methods that integrate machine learning with computational fluid dynamics (CFD) models, specifically for generic orally inhaled drug products (OIDPs). By combining ML with CFD, the goal is to improve and speed up the development and approval processes for these generic inhalers, overcoming current limitations like computational time and data processing challenges.
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 compl…
Source
Grant ID
FOR-FD-24-001
Funding Source
Food and Drug Administration
Eligibility
The following categories of applicants are invited to apply:
- For profit organizations other than small businesses
- Public and State controlled institutions of higher education
- Special district governments
- County governments
- Native American tribal governments (Federally recognized)
- Private institutions of higher education
- Native American tribal organizations (other than Federally recognized tribal governments)
- State governments
- City or township governments
- Public housing authorities/Indian housing authorities
- Independent school districts
- Nonprofits that do not have a 501(c)(3) status with the IRS, other than institutions of higher education
- Small businesses
- Nonprofits having a 501(c)(3) status with the IRS, other than institutions of higher education
Awards & Funding
Total Funding
$600,000
Funding Amount
Discretionary
Links
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