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Current Topics in Pharmacology   Volumes    Volume 24 
Regression-based model for the evaluation of CYP2D6-mediated drug-drug interactions
Roberto Lozano, Alberto Apesteguía, Alberto Frutos, Alejandro Martínez, María-Angeles Alcazar, María-Esther Franco
Pages: 21 - 25
Number of pages: 5
Current Topics in Pharmacology
Volume 24 

Copyright © 2020 Research Trends. All rights reserved

We aimed to construct a linear regression-based model between area-under-curve (AUCr) and the therapeutic range-to-inhibition constant ratio (TR-to-Ki). As result, a linear log-log regression model, between the averaged AUCr, calculated as the mean from the values of different drug-drug interactions (DDIs) between several victim-drugs with the same inhibitor (AUCr avg), and the mean TR-to-Ki ratio (TRm-to-Ki), calculated as the mean value between the maximum and minimum TR of the inhibitor divided by its Ki, obtained the best correlation (r2 = 0.72; p = 0.0116). Accordingly, a drug-drug interaction involving reversible inhibitory drugs of CYP2D6 could be managed by adjusting dose of victim and/or inhibitory drug to the magnitude of the desired change, by applying data of TR and Ki of inhibitor to the equation of regression line presented here.
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