Regression-Based Model for the Evaluation of CYP2D6-Mediated Drug-Drug Interactions

Linear regression-based model between area-under-curve (AUCr) and thetherapeutic 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 DDIs between severalvictim-drugs with the same inhibitor (AUCr avg), and the mean TR-to-Ki ratio (TRm-to-Ki), calculated asthe mean value between the maximum and minimum TR of the inhibitor divided by its Ki, obtained thebest correlation (r2= 0.72; p=0.0116). Accordingly, a drug-drug interaction involving reversible inhibitorydrugs of CYP2D6 could be manage by adjusting dose of victim and/or inhibitory drug to the magnitudeof the desired change, by applying data of TR and Ki of inhibitor to the equation of regression linepresented here.