A Systematic Framework for Drug Repurposing based on Literature Mining

Drug repurposing, referring to the discovery of new indications for an existing drug, has become an important aspect of drug development. This study seeks to extract hidden disease-drug associations from existing literature. Specifically, we propose a systematic framework assuming that a drug has a new use for a certain disease if the clinical disease symptoms and clinical drug effects complement each other. Via literature mining, we generate two vectors to describe clinical disease symptoms and clinical drug effects. Then we use a logistic regression model to predict how effectively the drug counteracts the disease based on the generated disease/drug vectors. Comprehensive experiments show the effectiveness of proposed framework. According to our results, there are many hidden disease-drug associations which can be the candidates for drug repurposing.