Exploring adverse drug events at the class level
- Stanford Univ., CA (United States). Center for Biomedical Informatics Research
- U.S. Food and Drug Administration (FDA), Silver Spring, MD (United States). Center for Drug Evaluation and Research
- National Inst. of Health (NIH), Bethesda, MD (United States). National Library of Medicine. Lister Hill National Center for Biomedical Communications
Background: While the association between a drug and an adverse event (ADE) is generally detected at the level of individual drugs, ADEs are often discussed at the class level, i.e., at the level of pharmacologic classes (e.g., in drug labels). We propose two approaches, one visual and one computational, to exploring the contribution of individual drugs to the class signal. Methods: Having established a dataset of ADEs from MEDLINE, we aggregate drugs into ATC classes and ADEs into high-level MeSH terms. We compute statistical associations between drugs and ADEs at the drug level and at the class level. Finally, we visualize the signals at increasing levels of resolution using heat maps. We also automate the exploration of drug-ADE associations at the class level using clustering techniques. Results: Using our visual approach, we were able to uncover known associations, e.g., between fluoroquinolones and tendon injuries, and between statins and rhabdomyolysis. Using our computational approach, we systematically analyzed 488 associations between a drug class and an ADE. Conclusions: The findings gained from our exploratory techniques should be of interest to the curators of ADE repositories and drug safety professionals. Our approach can be applied to different drug-ADE datasets, using different drug classification systems and different signal detection algorithms.
- Research Organization:
- Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC)
- Grant/Contract Number:
- SC0014664
- OSTI ID:
- 1627028
- Journal Information:
- Journal of Biomedical Semantics, Vol. 6, Issue 1; ISSN 2041-1480
- Publisher:
- BioMed CentralCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Similar Records
Study of serious adverse drug reactions using FDA-approved drug labeling and MedDRA
Molecular Assemblies, Genes and Genomics Integrated Efficiently (MAGGIE)