AI and automation in pharmacovigilance

 A pharmacovigilance team managing multiple products globally runs hundreds of literature searches each week. They log adverse event reports from call centers, emails, patient portals, and clinical trial feeds. Every day, cases arrive that require review, coding, triage, narrative writing, duplicate checking, and regulatory submission — all under strict timelines that most health authorities will not extend.



For years, the industry’s answer to this workload was more personnel, more spreadsheets, and more manual reviews. That answer no longer holds.

The efficiency case for AI-assisted literature screening in pharmacovigilance is well supported by research. A synthesis published in Frontiers in Pharmacology in January 2025, drawing on multiple structured literature review automation studies, found that AI-assisted screening tools can reduce the volume of articles requiring human review to as low as 23% of the total retrieved, with time savings per review cycle ranging from 7 to 86 hours. While this isn’t exactly a theoretical reduction, it changes what pharmacovigilance professionals are doing each week and determines whether recovered hours are allocated to high-value medical analysis or returned to the same manual queue.

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