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Background: Quantitative predictions of in vivo drug-drug interactions (DDIs) resulting from metabolic inhibition are commonly made based upon the inhibitor concentration at the enzyme active site [I] and the in vitro inhibition constant (K(i)). Previous studies have involved the use of various plasma inhibitor concentrations as surrogates for [I] along with K(i) values obtained from published literature. Although this approach has resulted in a high proportion of successful predictions, a number of falsely predicted interactions are also observed.Objectives: To focus on three issues that may influence the predictive value of the [I]/K(i) ratio approach: (i) the use of unbound K(i) (K(i,u)) values generated from standardised in vitro experiments compared with literature values; (ii) the selection of an appropriate [I]; and (iii) incorporation of the impact of intestinal metabolic inhibition for cytochrome P450 (CYP) 3A4 predictions. To this end we have selected eight inhibitors of CYP2C9, CYP2D6 and CYP3A4 and 18 victim drugs from a previous database analysis to allow prediction of 45 clinical DDI studies.Methods: In vitro kinetic and inhibition studies were performed in human liver microsomes using prototypic probe substrates of CYP2C9 and CYP2D6, with various inhibitors (miconazole, sulfaphenazole, fluconazole, ketoconazole, quinidine, fluoxetine, fluvoxamine). The K(i) estimates obtained were corrected for non-specific microsomal binding, and the K(i,u) was incorporated into in vivo predictions using various [I] values. Predictions for CYP3A4 were based upon in vitro data obtained from a previous publication within our laboratory, and an assessment of the impact of the interaction in the gut wall is included. Predictions were validated against 45 in vivo studies and those within 2-fold of the in vivo ratio of area under the plasma concentration-time curve of the substrate, in the presence and absence of the inhibitor (AUC(i)/AUC) were considered successful.Results: Predictions based upon the average systemic total plasma drug concentration ([I](av)) [incorporating the effects of parallel drug elimination pathways] and the K(i,u) value resulted in 91% of studies predicted to within 2-fold of the in vivo AUC(i)/AUC. This represents a 35% improvement in prediction accuracy compared with predictions based upon total K(i) values obtained from various published literature sources. A corresponding reduction in bias and an increase in precision were also observed compared with the use of other [I] surrogates (e.g. the total and new unbound maximum hepatic input plasma concentrations). No significant improvement in prediction accuracy was observed by incorporating consideration of gut wall inhibition for CYP3A4.Conclusion: DDI predictions based upon the use of K(i,u) data obtained under a set of optimal standardised conditions were significantly improved compared with predictions using in vitro data collated from various sources. The use of [I](av) as the [I] surrogate generated the most successful predictions as judged by several criteria. Incorporation of either plasma protein binding of inhibitor or gut wall CYP3A4 inhibition did not result in a general improvement of DDI predictions. [ABSTRACT FROM AUTHOR]

Aims Success of the quantitative prediction of drug–drug interactions via inhibition of CYP-mediated metabolism from the inhibitor concentration at the enzyme active site ([ I]) and the in vitro inhibition constant ( K i) is variable. The aim of this study was to examine the impact of the fraction of victim drug metabolized by a particular CYP ( f mCYP) and the inhibitor absorption rate constant ( k a) on prediction accuracy. Methods Drug–drug interaction studies involving inhibition of CYP2C9, CYP2D6 and CYP3A4 ( n = 115) were investigated. Data on f mCYP for the probe substrates of each enzyme and k a values for the inhibitors were incorporated into in vivo predictions, alone or in combination, using either the maximum hepatic input or the average systemic plasma concentration as a surrogate for [ I]. The success of prediction (AUC ratio predicted within twofold of in vivo value) was compared using nominal values of f mCY P = 1 and k a = 0.1 min−1. Results The incorporation of f mCYP values into in vivo predictions using the hepatic input plasma concentration resulted in 84% of studies within twofold of in vivo value. The effect of k a values alone significantly reduced the number of over-predictions for CYP2D6 and CYP3A4; however, less precision was observed compared with the f mCYP. The incorporation of both f mCYP and k a values resulted in 81% of studies within twofold of in vivo value. Conclusions The incorporation of substrate and inhibitor-related information, namely f mCYP and k a, markedly improved prediction of 115 interaction studies with CYP2C9, CYP2D6 and CYP3A4 in comparison with [ I]/ K i ratio alone. [ABSTRACT FROM AUTHOR]

In theory, the magnitude of an in vivo drug–drug interaction arising from the inhibition of metabolic clearance can be predicted using the ratio of inhibitor concentration ([I]) to inhibition constant ( Ki). The aim of this study was to construct a database for the prediction of drug–drug interactions from in vitro data and to evaluate the use of the various estimates for the inhibitor concentrations in the term [I]/ Ki. One hundred and ninety-three in vivo drug–drug interaction studies involving inhibition of CYP3A4, CYP2D6 or CYP2C9 were collated from the literature together with in vitro Ki values and pharmacokinetic parameters for inhibitors, to allow calculation of average/maximum systemic plasma concentration during the dosing interval and maximum hepatic input plasma concentration (both total and unbound concentration). The observed increase in AUC (decreased clearance) was plotted against the estimated [I]/ Ki ratio for qualitative zoning of the predictions. The incidence of false negative predictions (AUC ratio > 2, [I]/ Ki < 1) was largest using the average unbound plasma concentration and smallest using the hepatic input total plasma concentration of inhibitor for each of the CYP enzymes. Excluding mechanism-based inhibition, the use of total hepatic input concentration resulted in essentially no false negative predictions, though several false positive predictions (AUC ratio < 2, [I]/ Ki > 1) were found. The incidence of true positive predictions (AUC ratio > 2, [I]/ Ki > 1) was also highest using the total hepatic input concentration. The use of the total hepatic input concentration of inhibitor together with in vitro Ki values was the most successful method for the categorization of putative CYP inhibitors and for identifying negative drug–drug interactions. However this approach should be considered as an initial discriminating screen, as it is empirical and requires subsequent mechanistic studies to provide a comprehensive evaluation of a positive result. [ABSTRACT FROM AUTHOR]

Abstract: A series of conformationally restricted GPR119 agonists were prepared based around a 3,8-diazabicyclo[3.2.1]octane scaffold. Examples were found to have markedly different pharmacology in mouse and human despite similar levels of binding to the receptor. This highlights the large effects on GPCR phamacology that can result from small structural changes in the ligand, together with inter-species differences between receptors. [Copyright &y& Elsevier]