Author(s): Yates P, Eng H, Di L, Obach RS
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Abstract Time-dependent inhibition (TDI) of cytochrome P450 (P450) enzymes, especially CYP3A4, is an important attribute of drugs in evaluating the potential for pharmacokinetic drug-drug interactions. The analysis of TDI data for P450 enzymes can be challenging, yet it is important to be able to reliably evaluate whether a drug is a TDI or not, and if so, how best to derive the inactivation kinetic parameters K(I) and k(inact). In the present investigation a two-step statistical evaluation was developed to evaluate CYP3A4 TDI data. In the first step, a two-sided two-sample z-test is used to compare the k(obs) values measured in the absence and presence of the test compound to answer the question of whether the test compound is a TDI or not. In the second step, k(obs) values are plotted versus both [I] and ln[I] to determine whether a significant correlation exists, which can then inform the investigator of whether the inactivation kinetic parameters, K(I) and k(inact), can be reliably estimated. Use of this two-step statistical evaluation is illustrated with the examination of five drugs of varying capabilities to inactivate CYP3A4: ketoconazole, erythromycin, raloxifene, rosiglitazone, and pioglitazone. The use of a set statistical algorithm offers a more robust and objective approach to the analysis of P450 TDI data than frequently employed empirically derived or heuristic approaches.
This article was published in Drug Metab Dispos
and referenced in Journal of Clinical & Experimental Pharmacology