Abstract

Traditional cytochrome P450 (P450) based drug-drug interaction (DDI) predictions are based on the ratio of an inhibitor's physiological concentration [I] and its inhibition constant K_i. Determining [I] at the enzymatic site, although critical for predicting clinical DDIs, remains a technical challenge. In our previous study, a novel approach using cryopreserved human hepatocytes suspended in human plasma was investigated to mimic the in vivo concentration of ketoconazole at the enzymatic site (Lu et al., 2007), effectively eliminating the estimation of the elusive [I] value. P450 inhibition in this system appears to model that in vivo. Using the ketoconazole inhibition information in a human hepatocyte-plasma suspension together with quantitative P450 phenotypic information, we successfully predicted the pharmacokinetic DDIs for a small set of drugs, such as theophylline, tolbutamide, omeprazole, desipramine, midazolam, loratadine, cyclosporine, and alprazolam, as well as an investigational compound. For the applicability of this model on a wider scale the in vitro-in vivo correlation data set needed to be expanded. However, for most drugs in the literature there is not enough quantitative information on the involvement of individual P450s to predict DDIs retrospectively. To facilitate that, in this study we determined quantitative P450 phenotyping for seven marketed drugs: budesonide, buprenorphine, loratadine, sirolimus, tacrolimus, docetaxel, and methylprednisolone. Augmentation of the new data set with the one generated previously produced broader a database that provided further support for the wider applicability of this approach using ketoconazole as a potent CYP3A inhibitor. This application is predicted to be equally effective with other P450 inhibitors that are not substrates of efflux pumps.