Evaluation of Calibration Curve–Based Approaches to Predict Clinical Inducers and Noninducers of CYP3A4 with Plated Human Hepatocytes

Abstract

Cytochrome P450 (P450) induction is often considered a liability in drug development. Using calibration curve-based approaches, we assessed the induction parameters R 3 (a term indicating the amount of P450 induction in the liver, expressed as a ratio between 0 and 1), relative induction score, C max /EC 50 , and area under the curve (AUC)/F 2 (the concentration causing 2-fold increase from baseline of the doseresponse curve), derived from concentration-response curves of CYP3A4 mRNA and enzyme activity data in vitro, as predictors of CYP3A4 induction potential in vivo. Plated cryopreserved human hepatocytes from three donors were treated with 20 test compounds, including several clinical inducers and noninducers of CYP3A4. After the 2-day treatment, CYP3A4 mRNA levels and testosterone 6b-hydroxylase activity were determined by real-time reverse transcription polymerase chain reaction and liquid chromatographytandem mass spectrometry analysis, respectively. Our results demonstrated a strong and predictive relationship between the extent of midazolam AUC change in humans and the various parameters calculated from both CYP3A4 mRNA and enzyme activity. The relationships exhibited with non-midazolam in vivo probes, in aggregate, were unsatisfactory. In general, the models yielded better fits when unbound rather than total plasma C max was used to calculate the induction parameters, as evidenced by higher R 2 and lower root mean square error (RMSE) and geometric mean fold error. With midazolam, the R 3 cut-off value of 0.9, as suggested by US Food and Drug Administration guidance, effectively categorized strong inducers but was less effective in classifying midrange or weak inducers. This study supports the use of calibration curves generated from in vitro mRNA induction response curves to predict CYP3A4 induction potential in human. With the caveat that most compounds evaluated here were not strong inhibitors of enzyme activity, testosterone 6b-hydroxylase activity was also demonstrated to be a strong predictor of CYP3A4 induction potential in this assay model.

Application of Micropatterned Cocultured Hepatocytes to Evaluate the Inductive Potential and Degradation Rate of Major Xenobiotic Metabolizing Enzymes

“…Several publications have highlighted the utility of 2D or sandwich-cultured models using cryopreserved human hepatocytes to assess the CYP3A4-induction-based drug-drug interaction (DDI) risk of new chemical entities (NCEs) by conducting retrospective analyses on compounds that are known to be CYP3A4 inducers or noninducers in the clinic (Fahmi et al, 2010;Einolf et al, 2014;Zhang et al, 2014). Although these models have proven to be invaluable in understanding the CYP3A4-induction-based DDI risk of NCEs in both a practical and cost-effective way, the 2D substratum forces hepatocytes to alter their cytoskeleton toward a flattened morphology (Buxboim et al, 2010).…”

Quantitative Prediction of CYP3A4 Induction: Impact of Measured, Free, and Intracellular Perpetrator Concentrations from Human Hepatocyte Induction Studies on Drug-Drug Interaction Predictions

“…One caveat of including BSA in induction medium is that it can lower the concentration of free drug. Although inducer depletion and binding have previously been accounted for in induction predictions (Zhang et al, 2014;Chang et al, 2016), to date, no comprehensive study has been conducted to systematically investigate the impact of binding and depletion on induction predictions across multiple inducers and prediction methods. In the current evaluation, we sought to determine the measured and free concentrations of six clinical inducers and one noninducer of CYP3A4 in hepatocyte culture medium, and determine whether correction for these parameters can improve the accuracy of CYP3A4 induction predictions.…”

“…introduction Drug-drug interactions (DDIs) related to CYP3A4 induction remain a concern for the pharmaceutical industry given that induction can affect the safety and efficacy of coadministered drugs (Lin, 2006;Zhang et al, 2014). Typically, the concentration-response data used in these models rely on the nominal concentration of the applied new chemical entities (NCEs).…”

“…Using this method, the predicted magnitudes of induction for multiple inducers, including rifampicin and phenobarbital, were in agreement with the clinically observed DDI. In another study, Zhang et al (2014) considered the stability of the inducers that were evaluated. However, the inducer concentration was only measured at the 24-hour time point on the last day of incubation, which may result in an overestimation of the induction potency if there is substantial inducer depletion during the dosing interval.…”

Effect of honokiol on the induction of drug-metabolizing enzymes in human hepatocytes

“…Moreover, drug interaction knowledge might increase efficacy of a drug and reduce its undesirable side effects and toxicity. According to the US Food and Drug Administration (FDA) and European Medicines Agency (EMA) guidelines for drug–drug interactions, the effect of a drug on CYP mRNA levels in fresh or cryopreserved human hepatocytes is critical for CYP-induced drug interactions 28,29. Numerous drug–drug interaction studies using primary or cryopreserved human hepatocyte culture systems have been reported 30–35…”