Predicting Adverse Drug Effects from Literature- and Database-Mined Assertions.

ABSTRACT: INTRODUCTION:Given that adverse drug effects (ADEs) have led to post-market patient harm and subsequent drug withdrawal, failure of candidate agents in the drug development process, and other negative outcomes, it is essential to attempt to forecast ADEs and other relevant drug-target-effect relationships as early as possible. Current pharmacologic data sources, providing multiple complementary perspectives on the drug-target-effect paradigm, can be integrated to facilitate the inference of relationships between these entities. OBJECTIVE:This study aims to identify both existing and unknown relationships between chemicals (C), protein targets (T), and ADEs (E) based on evidence in the literature. MATERIALS AND METHODS:Cheminformatics and data mining approaches were employed to integrate an

SUBMITTER: La MK 

PROVIDER: S-EPMC6212308 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature