RT Journal Article
T1 Detection of drug-drug interactions by modeling interaction profile fingerprints
A1 Vilar Varela, Santiago
A1 Uriarte Villares, Eugenio
A1 Santana Penín, María Lourdes
A1 Tatonetti, Nicholas P.
A1 Friedman, Carol
AB Drug-drug interactions (DDIs) constitute an important problem in postmarketing pharmacovigilance and in the development of new drugs. The effectiveness or toxicity of a medication could be affected by the co-administration of other drugs that share pharmacokinetic or pharmacodynamic pathways. For this reason, a great effort is being made to develop new methodologies to detect and assess DDIs. In this article, we present a novel method based on drug interaction profile fingerprints (IPFs) with successful application to DDI detection. IPFs were generated based on the DrugBank database, which provided 9,454 well-established DDIs as a primary source of interaction data. The model uses IPFs to measure the similarity of pairs of drugs and generates new putative DDIs from the non-intersecting interactions of a pair. We described as part of our analysis the pharmacological and biological effects associated with the putative interactions; for example, the interaction between haloperidol and dicyclomine can cause increased risk of psychosis and tardive dyskinesia. First, we evaluated the method through hold-out validation and then by using four independent test sets that did not overlap with DrugBank. Precision for the test sets ranged from 0.4–0.5 with more than two fold enrichment factor enhancement. In conclusion, we demonstrated the usefulness of the method in pharmacovigilance as a DDI predictor, and created a dataset of potential DDIs, highlighting the etiology or pharmacological effect of the DDI, and providing an exploratory tool to facilitate decision support in DDI detection and patient safety.
PB PLOS
YR 2013
FD 2013
LK http://hdl.handle.net/10347/22256
UL http://hdl.handle.net/10347/22256
LA eng
NO Vilar S, Uriarte E, Santana L, Tatonetti NP, Friedman C (2013) Detection of Drug-Drug Interactions by Modeling Interaction Profile Fingerprints. PLoS ONE 8(3): e58321. https://doi.org/10.1371/journal.pone.0058321
NO This work was supported by grants R01 LM010016 (CF), R01 LM010016-0S1 (CF), R01 LM010016-0S2 (CF), R01 LM008635 (CF), “Plan Galego de Investigación, Innovación e Crece-mento 2011–2015 (I2C)”, European Social Fund (ESF) and Angeles Alvariño program from Xunta de Galicia (Spain)
DS Minerva
RD 28 abr 2026