This article examines how artificial intelligence supports drug safety activities, from adverse event detection to safety data analytics, while regulatory oversight, human decision authority, and clear AI governance frameworks remain central to compliant pharmacovigilance operations.

This article explores pharmacovigilance as a structured safety governance system that integrates safety data, regulatory oversight, and decision accountability. It explains how governance-driven models improve inspection readiness, strengthen regulatory trust, and support consistent post-marketing safety decisions across the product lifecycle.

Running a LIMS and a separate environmental monitoring (EM) tool often feels fine—until the bill for the second stack shows up in licenses, servers, validation cycles, and the time your teams spend reconciling data.