ABSTRACT:Recombinant cytochrome P450 (P450) phenotyping, different approaches for estimating fraction metabolized (f m ), and multiple measures of in vivo inhibitor exposure were tested for their ability to predict drug interaction magnitude in dogs. In previous reports, midazolam-ketoconazole interaction studies in dogs have been attributed to inhibition of CYP3A pathways. However, in vitro phenotyping studies demonstrated higher apparent intrinsic clearances (CL int,app ) of midazolam with canine CYP2B11 and CYP2C21. Application of activity correction factors and isoform hepatic abundance to liver microsome CL int,app values further implicated CYP2B11 (f m > 0.89) as the dog enzyme responsible for midazolam-and temazepam-ketoconazole interactions in vivo. Mean area under the curve (AUC) in the presence of the inhibitor/AUC ratios from intravenous and oral midazolam interaction studies were predicted well with unbound K i and estimates of unbound hepatic inlet inhibitor concentrations and intestinal metabolism using the AUC-competitive inhibitor relationship. No interactions were observed in vivo with bufuralol, although significant interactions with bufuralol were predicted with fluoxetine via CYP2D and CYP2C pathways (>2.45-fold) but not with clomipramine (<2-fold). The minor caffeine-fluvoxamine interaction (1.78-fold) was slightly higher than predicted values based on determination of a moderate f m value for CYP1A1, although CYP1A2 may also be involved in caffeine metabolism. The findings suggest promise for in vitro approaches to drug interaction assessment in dogs, but they also highlight the need to identify improved substrate and inhibitor probes for canine P450s.Metabolism-mediated drug interactions are an important consideration during preclinical drug lead optimization. Inhibitors of drugmetabolizing enzymes such as cytochromes P450 (P450) may be capable of decreasing the clearance of coadministered drugs when their clearance is metabolic. Therefore, it is important to evaluate new chemical entities as substrates and inhibitors of P450. To speed up this evaluation process, in vitro-in vivo extrapolation methods aimed at predicting metabolic drug interactions have continued to evolve. For instance, the choice of inhibition values (e.g., K i versus unbound K i ) (Brown et al., 2006), inhibitor absorption rates (Kanamitsu et al., 2000;Brown et al., 2005), P450 induction , and the choice of in vivo concentrations of P450 inhibitors (Brown et al., 2005;Obach et al., 2005) have all been studied with respect to in vitro-based drug-drug interaction (DDI) predictions. Irreversible enzyme inhibition mechanisms, although recognized for some time, have increasingly been added to in vitro-based drug interaction extrapolation methods with assumptions about the turnover rates of P450 isoforms (Mayhew et al., 2000;Venkatakrishnan and Obach, 2007). Several of these in vitro findings or approaches have even been integrated into several commercial software packages as biology continues to advance toward more physiolog...