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Mechanism-Based Inactivation of Human Cytochrome P450 Enzymes and the Prediction of Drug-Drug Interactions

Pharmacokinetics, Dynamics, and Drug Metabolism (R.S.O., R.L.W.) and Clinical Pharmacology (K.V.), Pfizer, Inc., Groton, Connecticut

The ability to use vitro inactivation kinetic parameters in scaling to in vivo drug-drug interactions (DDIs) for mechanism-based inactivators of human cytochrome P450 (P450) enzymes was examined using eight human P450-selective marker activities in pooled human liver microsomes. These data were combined with other parameters (systemic C_max, estimated hepatic inlet C_max, fraction unbound, in vivo P450 enzyme degradation rate constants estimated from clinical pharmacokinetic data, and fraction of the affected drug cleared by the inhibited enzyme) to predict increases in exposure to drugs, and the predictions were compared with in vivo DDIs gathered from clinical studies reported in the scientific literature. In general, the use of unbound systemic C_max as the inactivator concentration in vivo yielded the most accurate predictions of DDI with a mean -fold error of 1.64. Abbreviated in vitro approaches to identifying mechanism-based inactivators were developed. Testing potential inactivators at a single concentration (IC₂₅) in a 30-min preincubation with human liver microsomes in the absence and presence of NADPH followed by assessment of P450 marker activities readily identified those compounds known to be mechanism-based inactivators and represents an approach that can be used with greater throughput. Measurement of decreases in IC₅₀ occurring with a 30-min preincubation with liver microsomes and NADPH was also useful in identifying mechanism-based inactivators, and the IC₅₀ measured after such a preincubation was highly correlated with the k_inact/K_I ratio measured after a full characterization of inactivation. Overall, these findings support the conclusion that P450 in vitro inactivation data are valuable in predicting clinical DDIs that can occur via this mechanism.

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