Development of a model selection method for population pharmacokinetics analysis by deep-learning based reinforcement learning (U01) Clinical Trials Not Allowed
ArchivedFood and Drug Administration
Description
The purpose of this project is to develop a model selection method for the population pharmacokinetics (popPK) analysis using a deep-learning based reinforcement learning (RL) algorithm. The development of the method encompasses method validation and performance verification by simulations as well as real pharmacokinetics (PK) data sets.
Who can apply
- 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)
- Nonprofits with 501(c)(3) status (other than higher education)
- Nonprofits without 501(c)(3) status (other than higher education)
- Private institutions of higher education
- For-profit organizations other than small businesses
- Small businesses
- Others
Contact
Shashi Malhotra <br/>Grants Management Specialist <br/>Phone 2404027592
shashi.malhotra@fda.hhs.gov
- PostedJan 7, 2021
- ClosesMar 18, 2021
- Award floor$125,000
- Award ceiling$250,000
- Expected awards1
- CFDA93.103
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