  Adverse drug reactions (ADRs) induced from high-order drug-drug interactions
(DDIs) due to polypharmacy represent a significant public health problem. In
this paper, we formally formulate the to-avoid and safe (with respect to ADRs)
drug recommendation problems when multiple drugs have been taken
simultaneously. We develop a joint model with a recommendation component and an
ADR label prediction component to recommend for a prescription a set of
to-avoid drugs that will induce ADRs if taken together with the prescription.
We also develop real drug-drug interaction datasets and corresponding
evaluation protocols. Our experimental results on real datasets demonstrate the
strong performance of the joint model compared to other baseline methods.
