Statistical methods for analysis of time-dependent inhibition of cytochrome p450 enzymes

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.