Development of a model selection method for population pharmacokinetics analysis by deep-learning based reinforcement learning (U01) Clinical Trials Not Allowed

Archived

Food 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

Key dates & funding
  • PostedJan 7, 2021
  • ClosesMar 18, 2021
  • Award floor$125,000
  • Award ceiling$250,000
  • Expected awards1
  • CFDA93.103

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