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

doi:10.3233/978-1-61499-289-9-496

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 proceeding › Conference contribution

10 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 language	English (US)
Title of host publication	MEDINFO 2013 - Proceedings of the 14th World Congress on Medical and Health Informatics
Publisher	IOS Press
Pages	496-500
Number of pages	5
Edition	1-2
ISBN (Print)	9781614992882
DOIs	https://doi.org/10.3233/978-1-61499-289-9-496
State	Published - 2013
Event	14th World Congress on Medical and Health Informatics, MEDINFO 2013 - Copenhagen, Denmark Duration: Aug 20 2013 → Aug 23 2013

Publication series

Name	Studies in Health Technology and Informatics
Number	1-2
Volume	192
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Other

Other	14th World Congress on Medical and Health Informatics, MEDINFO 2013
Country/Territory	Denmark
City	Copenhagen
Period	8/20/13 → 8/23/13

Keywords

Adverse Drug Events
Biomedical Ontologies
Pharmacogenomics
Semantic Web
Severity

ASJC Scopus subject areas

Biomedical Engineering
Health Informatics
Health Information Management

Access to Document

10.3233/978-1-61499-289-9-496

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

Building a knowledge base of severe adverse drug events based on AERS reporting data using semantic Web technologies. / Jiang, Guoqian; Wang, Liwei; Liu, Hongfang et al.
MEDINFO 2013 - Proceedings of the 14th World Congress on Medical and Health Informatics. 1-2. ed. IOS Press, 2013. p. 496-500 (Studies in Health Technology and Informatics; Vol. 192, No. 1-2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Jiang, G, Wang, L, Liu, H, Solbrig, HR & Chute, CG 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 edn, Studies in Health Technology and Informatics, no. 1-2, vol. 192, IOS Press, pp. 496-500, 14th World Congress on Medical and Health Informatics, MEDINFO 2013, Copenhagen, Denmark, 8/20/13. https://doi.org/10.3233/978-1-61499-289-9-496

Jiang G, Wang L, Liu H, Solbrig HR, Chute CG. 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. IOS Press. 2013. p. 496-500. (Studies in Health Technology and Informatics; 1-2). doi: 10.3233/978-1-61499-289-9-496

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

Abstract

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Keywords

ASJC Scopus subject areas

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