A multimodal deep learning framework for predicting drug-drug interaction events

Yifan Deng, Xinran Xu, Yang Qiu, Jingbo Xia, Wen Zhang, Shichao Liu

Abstract: Drug–drug interactions (DDIs) are one of the major concerns in pharmaceutical research. Many machine learning based methods have been proposed for the DDI prediction, but most of them predict whether two drugs interact or not. The studies revealed that DDIs could cause different subsequent events, and predicting DDI-associated events is more useful for investigating the mechanism hidden behind the combined drug usage or adverse reactions.