Search

Established guidelines have recommended a number of methods based on in vitro data to assess the CYP3A induction risk of new chemical entities in clinical practice. In this study, we evaluated the predictability of various assessment methods. We collected in vitro parameters from a variety of literature that includes data on 19 batches of hepatocytes. Clinical CYP3A induction was predicted using 3 direct approaches-the fold-change, basic model, and mechanistic static models-as well as 5 correlation approaches, including the relative induction score (RIS) and the relative factor (RF) method. These predictions were then compared with data from 30 clinical inductions. Collected in vitro parameters varied greatly between hepatocyte batches. Direct assessment methods using fixed cut-off values provided a lot of false predictions due to hepatocyte variability, which can overlook induction risk or lead to needless clinical drug-drug interaction (DDI) studies. On the other hand, correlation methods with the cut-off values set for each batch of hepatocytes accurately predicted the induction risk. Among these, the AUCu/inducer concentrations for half the maximum induction (EC50) and the RF methods which use the area under the curve (AUC) of the unbound inducers for calculating induction potential showed an especially good correlation with clinical induction. Correlation methods were better at predicting clinical induction risk than the other methods, regardless of hepatocyte variability. The AUCu/EC50 and the RF methods in particular had a small number of false predictions, and can therefore be used to assess induction risk along with the other correlation methods recommended in guidelines.

By using the Relative Factor (RF) method-a method that can simply assess cytochrome P450 (CYP) induction risk based on a maximum induction effect model-we evaluated the risk of CYP2C9 induction and examined its relationship with risk of CYP3A4 induction. In cryopreserved human hepatocytes, the magnitude of CYP2C9 induction by eight drugs known to induce CYP3A4 was lower than the magnitude of CYP3A4 induction, but the magnitudes of induction of both were correlated. The RF values determined for CYP2C9 had a one-to-one linear relationship with values determined for CYP3A4, supporting reports that the induction mechanism of both enzymes is the same. Furthermore, clinical CYP2C9 induction data of compounds reported to induce CYP2C9 clinically were shown to be lower than those of CYP3A4. The thresholds for CYP2C9 induction risk assessment by the RF approach were determined to be at higher steady-state plasma concentrations than those for CYP3A4. Based on these results, induction of CYP2C9 was correlated with that of CYP3A4, and induction risk could be evaluated by the RF method using hepatocytes. The CYP2C9 induction risk of a compound was confirmed to be lower than its CYP3A4 induction risk.

This is the first report quantitatively evaluating the clinical induction of CYP3A in the liver and the intestine.To evaluate hepatic induction, we collected literature data on endogenous biomarkers of hepatic CYP3A induction which we then used to calculate the fold-induction (inducer-mediated change in biomarker level). Literature data on decreases in the area under the curve (AUC) of alfentanil, a CYP3A substrate, caused by CYP3A inducers were also collected. We used the hepatic intrinsic clearance of alfentanil to calculate the hepatic induction ratio (inducer-mediated change in intrinsic clearance). For intestinal induction, the intestinal bioavailability (Fg) of alfentanil was used to calculate the intestinal induction ratio. We determined in vivo maximum induction (Emax) and the average unbound plasma concentration (Cav,u) required for half the maximum induction (EC50) for inducers using an Emax model analysis.In our results, fold-induction was comparable to the induction ratio at several inducer concentrations, and almost the maximum induction was achieved by a therapeutic dose. Induction ratios in the intestine were similar to the liver.Our findings suggest that, by knowing only hepatic induction ratios for common inducers, we can quantitatively predict the decreases in the AUC of substrates by CYP3A induction. This is the first report quantitatively evaluating the clinical induction of CYP3A in the liver and the intestine. To evaluate hepatic induction, we collected literature data on endogenous biomarkers of hepatic CYP3A induction which we then used to calculate the fold-induction (inducer-mediated change in biomarker level). Literature data on decreases in the area under the curve (AUC) of alfentanil, a CYP3A substrate, caused by CYP3A inducers were also collected. We used the hepatic intrinsic clearance of alfentanil to calculate the hepatic induction ratio (inducer-mediated change in intrinsic clearance). For intestinal induction, the intestinal bioavailability (Fg) of alfentanil was used to calculate the intestinal induction ratio. We determined in vivo maximum induction (Emax) and the average unbound plasma concentration (Cav,u) required for half the maximum induction (EC50) for inducers using an Emax model analysis. In our results, fold-induction was comparable to the induction ratio at several inducer concentrations, and almost the maximum induction was achieved by a therapeutic dose. Induction ratios in the intestine were similar to the liver. Our findings suggest that, by knowing only hepatic induction ratios for common inducers, we can quantitatively predict the decreases in the AUC of substrates by CYP3A induction.

We investigated the robustness and utility of the relative factor (RF) approach based on the maximum induction effect (Emax) model, using the mRNA induction data of 10 typical CYP3A4 inducers in cryopreserved human hepatocytes. The RF value is designated as the ratio of the induction detection limit concentration (IDLC) for a standard inducer, such as rifampicin (RIF) or phenobarbital (PB), to that for the compound (e.g., RFRIF is IDLCRIF/IDLCcpd; RFPB is IDLCPB/IDLCcpd). An important feature of the RF approach is that the profiles of the induction response curves on the logarithmic scale remain unchanged irrespective of inducers but are shifted parallel depending on the EC50 values. A key step in the RF approach is to convert the induction response curve by finding the IDLC of a standard inducer. The relative induction score was estimated not only from Emax and EC50 values but also from those calculated by the RF approach. These values showed good correlation, with a correlation coefficient of more than 0.974, which revealed the RF approach to be a robust analysis irrespective of its simplicity. Furthermore, the relationship between RFRIF or RFPB multiplied by the steady-state unbound plasma concentration and the in vivo induction ratio plotted using 10 typical inducers gives adequate thresholds for CYP3A4 drug-drug interaction risk assessment. In light of these findings, the simple RF approach using the IDLC value could be a useful method to adequately assess the risk of CYP3A4 induction in humans during drug discovery and development without evaluation of Emax and EC50.