Reinforcement learning as an innovative model-based approach: Examples from precision dosing, digital health and computational psychiatry.

ABSTRACT: Model-based approaches are instrumental for successful drug development and use. Anchored within pharmacological principles, through mathematical modeling they contribute to the quantification of drug response variability and enables precision dosing. Reinforcement learning (RL)-a set of computational methods addressing optimization problems as a continuous learning process-shows relevance for precision dosing with high flexibility for dosing rule adaptation and for coping with high dimensional efficacy and/or safety markers, constituting a relevant approach to take advantage of data from digital health technologies. RL can also support contributions to the successful development of digital health applications, recognized as key players of the future healthcare systems, in particular for r

SUBMITTER: Ribba B 

PROVIDER: S-EPMC9981647 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature