Automation in pharmacovigilance-a review
Keywords:
automation, pharmacovigilance, ADRAbstract
The pharmacovigilance (PV) function is undergoing a rapid transformation as automated technologies—ranging from robotic process automation (RPA) and natural language processing (NLP) to machine learning (ML) and large language models (LLMs)—are adopted across the safety lifecycle. Drivers include rising case volumes, expanding real-world data (RWD) sources, evolving global data standards, and increasing regulatory expectations for quality, timeliness, and traceability. This review synthesizes how automation is reshaping case intake and processing, coding and deduplication, literature surveillance, signal detection and evaluation, and regulatory reporting. It also outlines governance and validation practices for compliant deployment, and highlights emerging opportunities and limitations.
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References
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