Building a knowledge base of severe adverse drug events based on AERS reporting data using semantic Web technologies

Guoqian Jiang, Liwei Wang, Hongfang Liu, Harold R. Solbrig, Christopher G. Chute

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

9 Scopus citations

Abstract

A semantically coded knowledge base of adverse drug events (ADEs) with severity information is critical for clinical decision support systems and translational research applications. However it remains challenging to measure and identify the severity information of ADEs. The objective of the study is to develop and evaluate a semantic web based approach for building a knowledge base of severe ADEs based on the FDA Adverse Event Reporting System (AERS) reporting data. We utilized a normalized AERS reporting dataset and extracted putative drug-ADE pairs and their associated outcome codes in the domain of cardiac disorders. We validated the drug-ADE associations using ADE datasets from SIDe Effect Resource (SIDER) and the UMLS. We leveraged the Common Terminology Criteria for Adverse Event (CTCAE) grading system and classified the ADEs into the CTCAE in the Web Ontology Language (OWL). We identified and validated 2,444 unique Drug-ADE pairs in the domain of cardiac disorders, of which 760 pairs are in Grade 5, 775 pairs in Grade 4 and 2,196 pairs in Grade 3.

Original languageEnglish (US)
Title of host publicationMEDINFO 2013 - Proceedings of the 14th World Congress on Medical and Health Informatics
PublisherIOS Press
Pages496-500
Number of pages5
Edition1-2
ISBN (Print)9781614992882
DOIs
StatePublished - Jan 1 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
Number1-2
Volume192
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Other

Other14th World Congress on Medical and Health Informatics, MEDINFO 2013
CountryDenmark
CityCopenhagen
Period8/20/138/23/13

Keywords

  • Adverse Drug Events
  • Biomedical Ontologies
  • Pharmacogenomics
  • Semantic Web
  • Severity

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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  • Cite this

    Jiang, G., Wang, L., Liu, H., Solbrig, H. R., & Chute, C. G. (2013). Building a knowledge base of severe adverse drug events based on AERS reporting data using semantic Web technologies. In MEDINFO 2013 - Proceedings of the 14th World Congress on Medical and Health Informatics (1-2 ed., pp. 496-500). (Studies in Health Technology and Informatics; Vol. 192, No. 1-2). IOS Press. https://doi.org/10.3233/978-1-61499-289-9-496