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A computational approach to predict multi-pathway drug-drug interactions: A case study of irinotecan, a colon cancer medication
- Source :
- Saudi Pharmaceutical Journal : SPJ, Saudi Pharmaceutical Journal, Vol 28, Iss 12, Pp 1507-1513 (2020)
- Publication Year :
- 2020
- Publisher :
- Elsevier BV, 2020.
-
Abstract
- Drug-drug interactions (DDIs) are a potentially distressing corollary of drug interventions, and may result in discomfort, debilitating illness, or even death. Existing research predominantly considers only a single level of interaction; however, serious health complications may result from multi-pathway DDIs, and so new methods are needed to enable predicting and preventing complex DDIs. This article introduces a novel method for the prediction of DDIs at two pharmacological levels (metabolic and transporter interactions) by means of a rule-based model implemented with Semantic Web technologies. The chemotherapy agent irinotecan is used as a case study for demonstrating the validity of this approach. Mechanistic and interaction data were mined from available sources and then used to predict interactors of irinotecan, including potential DDIs mediated by previously unidentified mechanisms. The findings also draw attention to the profound variation between DDI resources, indicating that clinical practice would see significant value from the development of an evidence-based resource to support DDI identification.
- Subjects :
- 0301 basic medicine
Drug
Colorectal cancer
media_common.quotation_subject
Drug-drug interaction
Pharmaceutical Science
Single level
Irinotecan
Bioinformatics
030226 pharmacology & pharmacy
03 medical and health sciences
0302 clinical medicine
Medicine
Multi-pathway
media_common
Pharmacology
business.industry
lcsh:RM1-950
medicine.disease
Semantic web technologies
Colon cancer
Clinical Practice
lcsh:Therapeutics. Pharmacology
030104 developmental biology
Original Article
Prediction
business
medicine.drug
Subjects
Details
- ISSN :
- 13190164
- Volume :
- 28
- Database :
- OpenAIRE
- Journal :
- Saudi Pharmaceutical Journal
- Accession number :
- edsair.doi.dedup.....c48709defba9fa0cfd7691f4c6c63e41