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Development of a model selection method for population pharmacokinetics analysis by deep-learning based reinforcement learning
Rolling Submissions
HHS-FDA
Description
For generic drug development, population pharmacokinetics (popPK) analysis is a critical part of the emerging technology of model-based bioequivalence (BE) analysis. PopPK models provide support for generalizing the conclusion of BE to groups that were not included in a BE study. The popPK model selection is essentially a multiple-objectives/variables optimization problem. Recent years have witnessed the overwhelming success of the reinforcement learning (RL) approaches in addressing optimization problem. Thus, the objective of t...
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Eligible Applicants
- 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
Funding Type
Grant
Categories of Funding Activity
- Consumer Protection
- Health
- Science, Technology, and Research & Development
Opportunity Type
Discretionary
Grantor Contact Information
shashi.malhotra@fda.hhs.gov
Other Grantor Informaiton
Shashi Malhotra Grants Management Specialist
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