Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach

Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, David Page, Sriraam Natarajan

Abstract: Most approaches for predicting drug-drug interactions (DDIs) have focused on text. We present the first work that uses multiple drug structure data - images, string representations and relationship representations. We exploit the recent advances in deep networks to integrate these varied sources of inputs in predicting DDIs. Our empirical evaluations clearly demonstrate the efficacy of combining heterogeneous data in predicting DDIs.