Background Drug–drug interactions (DDIs) remain a major source of preventable harm, yet many computational DDI resources are hard to reproduce, difficult to audit, or constrained by redistribution licenses. We created RxPairEvid-50 K to provide a small, license-clean, model-ready matrix of canonical drug pairs with conservative pharmacovigilance signal summaries and a rationale pointer that supports human interpretation. Methods RxPairEvid is derived from the FDA Adverse Event Reporting System (FAERS) by resolving drug mentions to a stable 14-character InChIKey stem (IK14), enumerating co-medication pairs per case, joining outcomes at the MedDRA Preferred Term (PT) code level, and computing disproportionality statistics (PRR, ROR, and the continuity-corrected lower 95% confidence bound of ROR) for each pair–PT. Signals are rolled up to per-pair features under strict count floors (aᵣaw≥3, pair≥10, PT ≥ 10). RxPairEvid-50 K is a deterministic stratified sample from the strict matrix. Conclusions RxPairEvid-50 K contains 50, 000 drug–drug pairs with stable identifiers, strict-regime FAERS signal features, PT-code rationale pointers, and audit artifacts. It is intended to support benchmarking, label construction, and exploratory modeling of interaction risk with transparent, reproducible processing steps.
Hashir et al. (Mon,) studied this question.