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Prediction of Severity of Drug-Drug Interactions Caused by Enzyme Inhibition and Activation
- Source :
- Molecules, Vol 24, Iss 21, p 3955 (2019)
- Publication Year :
- 2019
- Publisher :
- MDPI AG, 2019.
-
Abstract
- Drug-drug interactions (DDIs) severity assessment is a crucial problem because polypharmacy is increasingly common in modern medical practice. Many DDIs are caused by alterations of the plasma concentrations of one drug due to another drug inhibiting and/or inducing the metabolism or transporter-mediated disposition of the victim drug. Accurate assessment of clinically relevant DDIs for novel drug candidates represents one of the significant tasks of contemporary drug research and development and is important for practicing physicians. This work is a development of our previous investigations and aimed to create a model for the severity of DDIs prediction. PASS program and PoSMNA descriptors were implemented for prediction of all five classes of DDIs severity according to OpeRational ClassificAtion (ORCA) system: contraindicated (class 1), provisionally contraindicated (class 2), conditional (class 3), minimal risk (class 4), no interaction (class 5). Prediction can be carried out both for known drugs and for new, not yet synthesized substances using only their structural formulas. Created model provides an assessment of DDIs severity by prediction of different ORCA classes from the first most dangerous class to the fifth class when DDIs do not take place in the human organism. The average accuracy of DDIs class prediction is about 0.75.
- Subjects :
- drug interactions
ddis
adverse drug reaction
adr
Organic chemistry
QD241-441
Subjects
Details
- Language :
- English
- ISSN :
- 14203049
- Volume :
- 24
- Issue :
- 21
- Database :
- Directory of Open Access Journals
- Journal :
- Molecules
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.1e91bccf6e24c32be87ddd2d9fc62c7
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/molecules24213955