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A Novel Model for the Prediction of Drug-Drug Interactions in Humans Based on in Vitro Cytochrome P450 Phenotypic Data

Ketoconazole has generally been used as a standard inhibitor for studying clinical pharmacokinetic drug-drug interactions (DDIs) of drugs that are primarily metabolized by CYP3A4/5. However, ketoconazole at therapeutic, high concentrations also inhibits cytochromes P450 (P450) other than CYP3A4/5, which has made the predictions of DDIs less accurate. Determining the in vivo inhibitor concentration at the enzymatic site is critical for predicting the clinical DDI, but it remains a technical challenge. Various approaches have been used in the literature to estimate the human hepatic free concentrations of this inhibitor, and application of those to predict DDIs has shown some success. In the present study, a novel approach using cryopreserved human hepatocytes suspended in human plasma was applied to mimic the in vivo concentration of ketoconazole at the enzymatic site. The involvement of various P450s in the metabolism of compounds of interest was quantitatively determined (reactive phenotyping). Likewise, the effect of ketoconazole on various P450s was quantitated. Using this information, P450-mediated change in the area under the curve has been predicted without the need of estimating the inhibitor concentrations at the enzyme active site or the Ki. This approach successfully estimated the magnitude of the clinical DDI of an investigational compound, MLX, which is cleared by multiple P450-mediated metabolism. It also successfully predicted the pharmacokinetic DDIs for several marketed drugs (theophylline, tolbutamide, omeprazole, desipramine, midazolam, alprazolam, cyclosporine, and loratadine) with a correlation coefficient (r2) of 0.992. Thus, this approach provides a simple method to more precisely predict the DDIs for P450 substrates when coadministered with ketoconazole or any other competitive P450 inhibitors in humans.