Standardizing drug adverse event reporting data

Liwei Wang, Guoqian Jiang, Dingcheng Li, Hongfang Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations


Normalizing data in the Adverse Event Reporting System (AERS), an FDA database, would improve the mining capacity of AERS for drug safety signal detection. In this study, we aim to normalize AERS and build a publicly available normalized Adverse drug events (ADE) data source.he drug information in AERS is normalized to RxNorm, a standard terminology source for medication. Drug class information is then obtained from the National Drug File-Reference Terminology (NDF-RT). Adverse drug events (ADE) are aggregated through mapping with the PT (Preferred Term) and SOC (System Organ Class) codes of MedDRA. Our study yields an aggregated knowledge-enhanced AERS data mining set (AERS-DM). The AERS-DM could provide more perspectives to mine AERS database for drug safety signal detection and could be used by research community in the data mining field.

Original languageEnglish (US)
Title of host publicationMEDINFO 2013 - Proceedings of the 14th World Congress on Medical and Health Informatics
PublisherIOS Press
Number of pages1
ISBN (Print)9781614992882
StatePublished - 2013
Event14th World Congress on Medical and Health Informatics, MEDINFO 2013 - Copenhagen, Denmark
Duration: Aug 20 2013Aug 23 2013

Publication series

NameStudies in Health Technology and Informatics
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365


Other14th World Congress on Medical and Health Informatics, MEDINFO 2013


  • Adverse drug events
  • adverse event reporting system (AERS)
  • data mining
  • data normalization
  • knowledge discovery

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management


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