Computational methods for inference and prediction of novel drug-drug interactions

Abstract

Abstract. It is critically important for drug development and clinical safety to identify and assess drug-drug interactions (DDIs) early and accurately. In addition to in vitro laboratory studies, in silico methods exist that may supplement the screening and detection of DDIs in large-scale databases. Here we review recent novel approaches that uncover underlying DDIs from the databases constructed with drug information, adverse event reports, electronic medical records, and other sources to give revelation to the researchers for further surveys.