PVLens: Enhancing Pharmacovigilance Through Automated Label Extraction

Reliable drug safety reference databases are essential for pharmacovigilance, yet existing resources like SIDER are outdated and static. We introduce PVLens, an automated system that extracts labeled safety information from FDA Structured Product Labels (SPLs) and maps terms to MedDRA. In validation against 97 drug labels, PVLens achieved an F1 score of 0.882, with high recall (0.983) and moderate precision (0.799). By offering a scalable, more accurate and continuously updated alternative to SIDER, PVLens enhances real-time pharamcovigilance with improved accuracy and contemporaneous insights. Keywords: Pharmacovigilance, Natural Language Processing (NLP), Drug Safety, ADR 1 Introduction A clear understanding of known adverse effects, along with continuous surveillance for emerging safety concerns, is essential for patients, healthcare professionals, and pharmacovigilance (PV) scientists.