作者: Juan M. Banda , Lee Evans , Rami S. Vanguri , Nicholas P. Tatonetti , Patrick B. Ryan
关键词: Drug 、 Resource (project management) 、 Computer science 、 Normalization (sociology) 、 RxNorm 、 MEDLINE 、 Adverse Event Reporting System 、 Data management 、 Identification (information) 、 Data science
摘要: Identification of adverse drug reactions (ADRs) during the post-marketing phase is one most important goals safety surveillance. Spontaneous reporting systems (SRS) data, which are mainstay traditional surveillance, used for hypothesis generation and to validate newer approaches. The publicly available US Food Drug Administration (FDA) Adverse Event Reporting System (FAERS) data requires substantial curation before they can be appropriately, applying different strategies cleaning normalization have material impact on analysis results. We provide a curated standardized version FAERS removing duplicate case records, vocabularies with names mapped RxNorm concepts outcomes SNOMED-CT concepts, pre-computed summary statistics about drug-outcome relationships general consumption. This resource, along source code, will accelerate research by reducing amount time spent performing management reports, improving quality underlying enabling analyses using common vocabularies.