• Christian Wagner, Yuzhuo Pan, Vicky Hsu, Vikram Sinha, and Ping Zhao.
• Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, 10903 New Hampshire Ave, Silver Spring, MD, 20993, USA.
• Clin Pharmacokinet. 2016 Apr 1; 55 (4): 475-83.

Background And ObjectiveWe recently published analyses regarding the predictive performance of physiologically based pharmacokinetic (PBPK) models, submitted to the US Food and Drug Administration (FDA), for the effect of cytochrome P450 (CYP) inhibitors on the pharmacokinetics of substrate drugs. We now analyze and summarize the predictive performance of PBPK models for the effect of CYP3A inducers on a substrate's pharmacokinetics.MethodsThis analysis was based on 11 substrate PBPK models, developed by six sponsors, using a commercial PBPK software, with 13 clinical interaction studies. Four CYP3A inducers were used: rifampicin, rifabutin, carbamazepine, and efavirenz. Sponsors either directly used the software-provided inducer models or verified these models' induction magnitude prior to use. The metric for assessing predictive performance was the R predicted/observed value [R predicted/observed = (predicted mean exposure ratio)/(observed mean exposure ratio)], with the exposure ratio defined as maximum plasma concentration (C max) or area under the plasma concentration-time curve (AUC) with and without an inducer.ResultsIn 77% (10/13; AUCR) and 83% (10/12; C max R) of the cases, the R predicted/observed values were within 1.25-fold of the observed data. Cases with R predicted/observed values >1.25-fold (>twofold for all three AUCR) were under-predictions as a result of using the PBPK software's default rifampicin model. Improved predictions were observed when the rifampicin model was modified by increasing the induction potency.ConclusionBased on submissions to the FDA, and similar to our previous findings for CYP inhibition, we observed good agreement between PBPK-predicted and observed effect of CYP3A inducers on substrate pharmacokinetics. Verification of the inducer model appears to be crucial for improved predictive performance.

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