Zero-friction Adverse Drug Reaction Reporting from Clinical Instant Messaging Using Hybrid NLP

This manuscript presents a proof-of-concept hybrid NLP pipeline for adverse drug reaction (ADR) signal detection and information extraction from clinical instant messaging data. It combines a keyword-based rule engine with a locally deployed LLM in a zero-shot setting to support low-friction pharmacovigilance reporting workflows.

Working paper (under review at Drug Safety)