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- Title
A Data-Driven Medical Decision Framework for Associating Adverse Drug Events with Drug-Drug Interaction Mechanisms.
- Authors
Noor, Adeeb
- Abstract
Adverse drug events (ADEs) occur when multiple drugs interact within an individual, thus causing effects that were not initially predicted. Such toxic interactions lead to morbidity and mortality. Contemporary research surrounding ADEs has tended to focus on the detection of potential ADEs without great concern for elucidating the associations of drug-drug interaction (DDI) mechanisms that can predict potential adverse drug reactions (ADRs). Such associations are of great practical importance for everyday pharmacovigilance efforts. This study presents a data-driven framework for conducting knowledge-driven data analysis that combines a semantic inference system and enrichment analysis in order to identify potential ADE mechanisms. The framework was used to rank mechanisms according to their relevance for DDIs and also to categorize ADEs based on the number of DDI mechanism associations identified through enrichment analysis. Its validity is demonstrated through using both commercial and publicly available DDI resources. The results of this study solidly prove the framework's effectiveness and highlight potential for future research by way of incorporating additional and broader data to deepen and expand its capabilities.
- Subjects
DRUG side effects; DRUG interactions; TOXICOLOGICAL interactions
- Publication
Journal of Healthcare Engineering, 2022, p1
- ISSN
2040-2295
- Publication type
Article
- DOI
10.1155/2022/9132477