Predicting the Effects of Drug Combinations Using Probabilistic Matrix Factorization.

ABSTRACT: Drug development is costly and time-consuming, and developing novel practical strategies for creating more effective treatments is imperative. One possible solution is to prescribe drugs in combination. Synergistic drug combinations could allow lower doses of each constituent drug, reducing adverse reactions and drug resistance. However, it is not feasible to sufficiently test every combination of drugs for a given illness to determine promising synergistic combinations. Since there is a finite amount of time and resources available for finding synergistic combinations, a model that can identify synergistic combinations from a limited subset of all available combinations could accelerate development of therapeutics. By applying recommender algorithms, such as the low-rank matrix completion

SUBMITTER: Nafshi R 

PROVIDER: S-EPMC9581062 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature