Predicting the side effects of drugs using matrix factorization on spontaneous reporting database.

ABSTRACT: The severe side effects of some drugs can threaten the lives of patients and financially jeopardize pharmaceutical companies. Computational methods utilizing chemical, biological, and phenotypic features have been used to address this problem by predicting the side effects. Among these methods, the matrix factorization method, which utilizes the side-effect history of different drugs, has yielded promising results. However, approaches that encapsulate all the characteristics of side-effect prediction have not been investigated to date. To address this gap, we applied the logistic matrix factorization algorithm to a database of spontaneous reports to construct a prediction with higher accuracy. We expressed the distinction in the importance of drug-side effect pairs by a weighting strategy

SUBMITTER: Fukuto K 

PROVIDER: S-EPMC8671428 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature