Leveraging FDA Labeling Documents and Large Language Model to Enhance Annotation, Profiling, and Classification of Drug Adverse Events with AskFDALabel

Wu, Leihong; Fang, Hong; Qu, Yanyan; Xu, Joshua; Tong, Weida

doi:10.1007/s40264-025-01520-1

Leveraging FDA Labeling Documents and Large Language Model to Enhance Annotation, Profiling, and Classification of Drug Adverse Events with AskFDALabel

Background Drug adverse events (AEs) represent a significant public health concern. US Food and Drug Administration (FDA) drug labeling documents are an essential resource for studying drug safety such as assessing a drug’s likelihood to cause certain organ toxicities; however, the manual extract…