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3D Pharmacophoric Similarity improves Multi Adverse Drug Event Identification in Pharmacovigilance

Santiago Vilar Varela; Nicholas P. Tatonetti; George M. Hripcsak

Title:
3D Pharmacophoric Similarity improves Multi Adverse Drug Event Identification in Pharmacovigilance
Author(s):
Vilar Varela, Santiago
Tatonetti, Nicholas P.
Hripcsak, George M.
Date:
Type:
Articles
Department(s):
Biomedical Informatics
Volume:
5
Persistent URL:
Book/Journal Title:
Scientific Reports
Abstract:
Adverse drugs events (ADEs) detection constitutes a considerable concern in patient safety and public health care. For this reason, it is important to develop methods that improve ADE signal detection in pharmacovigilance databases. Our objective is to apply 3D pharmacophoric similarity models to enhance ADE recognition in Offsides, a pharmacovigilance resource with drug-ADE associations extracted from the FDA Adverse Event Reporting System (FAERS). We developed a multi-ADE predictor implementing 3D drug similarity based on a pharmacophoric approach, with an ADE reference standard extracted from the SIDER database. The results showed that the application of our 3D multi-type ADE predictor to the pharmacovigilance data in Offsides improved ADE identification and generated enriched sets of drug-ADE signals. The global ROC curve for the Offsides ADE candidates ranked with the 3D similarity score showed an area of 0.7. The 3D predictor also allows the identification of the most similar drug that causes the ADE under study, which could provide hypotheses about mechanisms of action and ADE etiology. Our method is useful in drug development, screening potential adverse effects in experimental drugs, and in drug safety, applicable to the evaluation of ADE signals selected through pharmacovigilance data mining.
Subject(s):
Drugs--Side effects
Medical care
Bioinformatics
Medicine
Publisher DOI:
https://doi.org/10.1038/srep08809
Item views
48
Metadata:
text | xml
Suggested Citation:
Santiago Vilar Varela, Nicholas P. Tatonetti, George M. Hripcsak, , 3D Pharmacophoric Similarity improves Multi Adverse Drug Event Identification in Pharmacovigilance, Columbia University Academic Commons, .

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