Unbound liver concentration is the true inhibitor concentration that determines cytochrome P450-mediated drug–drug interactions in rat liver

Risk prediction of drug-drug interaction potential of phenytoin and miconazole topical formulations

The drug-drug interaction (DDI) risk of phenytoin with several topical formulations of miconazole is still unclear. The present investigation conducted in vitro-in vivo extrapolation to predict the potential risks. Our data indicated that miconazole potently inhibited phenytoin hydroxylation in both pooled human liver microsomes (HLMs) and recombinant cytochrome P450 2C9 (CYP2C9) with the K_i values of 125 ± 7 nM and 30 ± 2 nM, respectively. Quantitative prediction of DDI risk suggests that, beside intravenous administration or swallowed tablet, combination of phenytoin and miconazole high dose oral gel or buccal tablet may also result in a clinically significant increase of phenytoin AUC (>53%) by the inhibition of miconazole against phenytoin hydroxylation, consequently a higher frequency of adverse events, while the coadministration of miconazole vaginal formulation and phenytoin will be safe.

Impact of Intracellular Concentrations on Metabolic Drug-Drug Interaction Studies

Accurate prediction of drug-drug interactions (DDI) is a challenging task in drug discovery and development. It requires determination of enzyme inhibition in vitro which is highly system-dependent for many compounds. The aim of this study was to investigate whether the determination of intracellular unbound concentrations in primary human hepatocytes can be used to bridge discrepancies between results obtained using human liver microsomes and hepatocytes. Specifically, we investigated if Kp_uu could reconcile differences in CYP enzyme inhibition values (K_i or IC₅₀). Firstly, our methodology for determination of Kp_uu was optimized for human hepatocytes, using four well-studied reference compounds. Secondly, the methodology was applied to a series of structurally related CYP2C9 inhibitors from a Roche discovery project. Lastly, the Kp_uu values of three commonly used CYP3A4 inhibitors—ketoconazole, itraconazole, and posaconazole—were determined and compared to compound-specific hepatic enrichment factors obtained from physiologically based modeling of clinical DDI studies with these three compounds. Kp_uu obtained in suspended human hepatocytes gave good predictions of system-dependent differences in vitro. The Kp_uu was also in fair agreement with the compound-specific hepatic enrichment factors in DDI models and can therefore be used to improve estimations of enrichment factors in physiologically based pharmacokinetic modeling.

Application of unbound liver-to-plasma concentration ratio to quantitative projection of cytochrome P450-mediated drug-drug interactions using physiologically based pharmacokinetic modelling approach

1. This study evaluated the prediction accuracy of cytochrome P450 (CYP)-mediated drug-drug interaction (DDI) using minimal physiologically-based pharmacokinetic (PBPK) modelling incorporating the hepatic accumulation factor of an inhibitor (i.e. unbound liver/unbound plasma concentration ratio [K_p,uu,liver]) based on 22 clinical DDI studies. 2. K_p,uu,liver values were estimated using three methods: (1) ratio of cell-to-medium ratio in human cryopreserved hepatocytes (C/M_u) at 37 °C to that on ice (K_p,uu,C/M), (2) multiplication of total liver/unbound plasma concentration ratio (K_p,u,liver) estimated from C/M_u at 37 °C with unbound fraction in human liver homogenate (K_p,uu,cell) and (3) observed K_p,uu,liver in rats after intravenous infusion (K_p,uu,rat). 3. PBPK model using each K_p,uu,liver projected the area under the curve (AUC) increase of substrates more accurately than the model assuming a K_p,uu,liver of 1 for the average fold error and root mean square error did. Particularly, the model with a K_p,uu,liver of 1 underestimated the AUC increase of triazolam following co-administration with CYP3A4 inhibitor itraconazole by five-fold, whereas the AUC increase projected using the model incorporating the K_p,uu,C/M, K_p,uu,cell, or K_p,uu,rat of itraconazole and hydroxyitraconazole was within approximately two-fold of the actual value. 4. The results indicated that incorporating K_p,uu,liver into the PBPK model improved the accuracy of DDI projection.

Quantitative prediction of the extent of drug-drug interaction using a physiologically based pharmacokinetic model that includes inhibition of drug metabolism determined in cryopreserved hepatocytes

1. A physiologically based pharmacokinetic (PBPK) model that includes inhibition constant evaluated in cryopreserved hepatocytes was used to predict drug-drug interactions (DDIs) between orally administered nifedipine, a CYP substrate, and fluconazole or ketoconazole, CYP inhibitors, in rats. 2. The Kp,uu, ratio of unbound inhibitor concentration in liver ([I]liver,u) to that in plasma ([I]sys,u), of fluconazole and ketoconazole was 1.0 and 13.0, indicating that ketoconazole accumulates in liver. The ratios of inhibition constants in rat liver microsomes (Ki,mic,u) to that in rat cryopreserved hepatocytes (Ki,hep,u) for fluconazole and ketoconazole were 1.5 and 25.5, which were similar to the Kp,uu and suggested that cryopreserved hepatocytes could mimic the hepatic accumulation of inhibitors. 3. The increases in AUC of nifedipine predicted by the minimal PBPK model using [I]liver,u/Ki,mic,u and [I]sys,u/Ki,hep,u were within 1.5-fold of the observed values for both inhibitors, whereas the model using [I]sys,u/Ki,mic,u underestimated the AUC increase caused by ketoconazole 21-fold. 4. These results indicated that hepatic accumulation factor of an inhibitor is required for a precise DDI projection and that cryopreserved hepatocytes would be useful to obtain the Ki including hepatic accumulation factor. It was demonstrated that PBPK model using Ki,hep,u could be a valuable approach for quantitative DDI projection.