Title
Facilitating adverse drug event detection in pharmacovigilance databases using molecular structure similarity: application to rhabdomyolysis.
Abstract
Background Adverse drug events (ADE) cause considerable harm to patients, and consequently their detection is critical for patient safety. The US Food and Drug Administration maintains an adverse event reporting system (AERS) to facilitate the detection of ADE in drugs. Various data mining approaches have been developed that use AERS to detect signals identifying associations between drugs and ADE. The signals must then be monitored further by domain experts, which is a time-consuming task. Objective To develop a new methodology that combines existing data mining algorithms with chemical information by analysis of molecular fingerprints to enhance initial ADE signals generated from AERS, and to provide a decision support mechanism to facilitate the identification of novel adverse events. Results The method achieved a significant improvement in precision in identifying known ADE, and a more than twofold signal enhancement when applied to the ADE rhabdomyolysis. The simplicity of the method assists in highlighting the etiology of the ADE by identifying structurally similar drugs. A set of drugs with strong evidence from both AERS and molecular fingerprint-based modeling is constructed for further analysis. Conclusion The results demonstrate that the proposed methodology could be used as a pharmacovigilance decision support tool to facilitate ADE detection.
Year
DOI
Venue
2011
10.1136/amiajnl-2011-000417
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
Keywords
Field
DocType
data mining,molecular structure,pharmacovigilance,algorithms
Data mining,Informatics,Adverse Event Reporting System,Molecular Fingerprint,Decision support system,Pharmacovigilance,Drug,Medicine,Database,Drug administration,False positive paradox
Journal
Volume
Issue
ISSN
18
SUPnan
1067-5027
Citations 
PageRank 
References 
9
1.35
3
Authors
6
Name
Order
Citations
PageRank
Santiago Vilar11069.12
Rave Harpaz220713.18
Herbert S Chase317114.04
Stefano Costanzi4163.01
Raul Rabadan5808.83
Carol Friedman61618147.25