自动提取药品说明书安全信息，更新药物警戒数据库。
PVLens: Enhancing Pharmacovigilance Through Automated Label Extraction
- 从FDA药品说明书自动提取安全标签，映射至MedDRA术语
- 在97个药品标签上达到0.882的F1分数，召回率达0.983
- 适合药物安全监测、医学研究及需要实时数据的机构使用
可靠的药物安全参考数据库对药物警戒至关重要，但现有资源如SIDER存在过时和静态问题。我们提出PVLens，一个自动化系统，从FDA结构化产品标签（SPLs）中提取带标签的安全信息，并将其映射到MedDRA术语体系。PVLens通过基于网页的审核工具实现自动化与专家审查的结合。在97个药品标签的验证中，PVLens的F1得分为0.882，召回率高达0.983，精确率为0.799。该系统提供了可扩展、更准确且持续更新的替代方案，优于SIDER，显著提升药物警戒的实时性与准确性。
原文摘要 · Abstract (English)
Reliable drug safety reference databases are essential for pharmacovigilance, yet existing resources like SIDER are outdated and static.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. PVLens integrates automation with expert oversight through a web-based review tool. 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.
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