Why pharmacovigilance is a strong AI-assistance use case

Pharmacovigilance teams process large volumes of structured and unstructured information across published literature, case narratives, internal safety sources and operational queues. AI can help prioritize and structure this information, but it should be designed as an assistive layer rather than an autonomous medical decision-maker.

Published and authorized unpublished data need different controls

Published literature can be screened for potential product-event associations, while authorized unpublished sources may include internal safety data, case information or controlled operational repositories. Access, privacy, provenance and retention controls should reflect the source and intended use.

AE and SAE identification should produce candidates for expert review

AI can classify passages, identify potential adverse events, extract product-event context and prioritize cases that may warrant safety-team attention. The output should be a traceable candidate signal or workflow item, not an unreviewed regulatory conclusion.

Human-in-the-loop is part of the architecture

Medical and pharmacovigilance experts remain accountable for case validity, seriousness, causality and reportability. AI workflows should therefore expose source evidence, confidence or rationale, allow correction and capture reviewer decisions for auditability.

Evaluation must use representative safety scenarios

Testing should cover precision and recall for event identification, seriousness cues, duplicate or ambiguous cases, product association, source citations, missing information and false-positive behavior. Performance should be monitored as data and models change.

A practical production pattern

A production workflow can combine source ingestion, document parsing, entity/event extraction, retrieval, classification, case prioritization, reviewer interface, audit trail and downstream safety-system integration. Security and validation controls should be proportionate to intended use and regulatory impact.