PBPK modelling of the DDI between a Drug X and gemfibrozil
Elisa A. M. Calvier (1), Olivier Nicolas (1), Jean-Marie Martinez (1)
Pharmacokinetics-Dynamics and Metabolism (PKDM), Translational Medicine and Early Development, Sanofi R&D, Montpellier, France
Objectives:
A PBPK model for drug X and its active metabolite was built in Simcyp V20. The parent drug was an orally administered compound (fast release tablet) with a high extraction ratio, high plasma protein binding, and mainly eliminated through CYP3A4 and CYP2C8. Part of the CYP2C8 metabolism leads to the formation of a pharmacologically active metabolite. This metabolite is mainly eliminated through CYP2D6 and CYP3A4 metabolism. The parent and metabolite were found not to be transporters substrates. CYP-specific fraction metabolized (fm) of the parent and metabolite, originally based on in vitro data, were refined using clinical data from itraconazole and gemfibrozil DDI studies and human mass balance data. Regarding enzyme inhibition, itraconazole and OH-itraconazole are CYP3A and CYP3A4 inhibitors respectively, while gemfibrozil and its glucuronide metabolite both inhibit CYP2C8. Gemfibrozil also inhibit CYP2C9.
The developed PBPK model reasonably predicted the exposure and observed DDI for the parent drug as well as the exposure of the metabolite but led to a 10-fold and 2-fold overprediction of the metabolite AUC ratios (AUCr) for gemfibrozil and itraconazole DDI studies respectively. It was not possible to explain the observed DDI data by changing the PBPK parameters of the parent and metabolite. Therefore, it was hypothesized that the CYP2C8 inhibitory constants from the gemfibrozil Simcyp V20 model (includes both gemfibrozil and one of its glucuronides) might not be suitable, and the objective of this work was to update and qualify these constants using our parent and metabolite PBPK model and DDI data.
Methods:
First, the sensitivity of the predicted AUCr and Cmax ratio (Cmaxr) of CYP2C8 substrates to the decrease in gemfibrozil Ki was explored. Published clinical DDI data with gemfibrozil with CYP2C8 substrates rosiglitazone [1], repaglinide [2-6], dasabuvir [7], pioglitazone [8-10], and montelukast [11, 12], which CYP2C8 is responsible for 55, 60, 61, 63 and 79% of drug metabolism, respectively. Three scenarios were simulated: 1) default Ki values, 2) competitive Ki’s 15-fold decrease for gemfibrozil and its glucuronide (1.61µM and 0.325 µM respectively) or 3) 5-fold decrease in competitive Ki for gemfibrozil and its glucuronide (4.82 µM and 0.976µM respectively) and in mechanism-based inhibition parameter Kapp for gemfibrozil glucuronide (5.42µM). Additionally, for montelukast, a 200-fold change in Ki was investigated. For each drug, AUCr and Cmaxr were compared to observation by computing predicted/observed ratios (P/O_AUCr and P/O_Cmaxr).
Subsequently, further refinement of the gemfibrozil and drug X parent-metabolite PBPK models using the parent and metabolite DDI data of the compound X were performed.
Results:
The median P/O AUCr and Cmaxr for rosiglitazone, repaglinide, dasabuvir, pioglitazone, and montelukast increased as the gemfibrozil and glucuronide inhibitory constants were decreased for both scenario 2 and 3 as compared to scenario 1. For scenario 3, this increase was higher but small, with the maximum changes being noted between scenario 1 and 3 for P/O_AUCr of 37.3% corresponding to dasabuvir and of P/O_Cmaxr of 10.9% corresponding to repaglinide. For scenario 3, maximum P/O_Cmaxr was 1.52 and maximum P/O_AUCr was 1.28, for repaglinide and montelukast respectively. A 200-fold change in gemfibrozil CYP2C8 Ki (from 24.10 (initial value) to 0.12 µM) did not significantly impact AUC and Cmax ratios in DDI simulations with montelukast (<25%). Decreasing the gemfibrozil and metabolite Ki and Kinact values (15 and 5-fold respectively) together with fm refinement of drug X and its metabolite, it was possible to accurately simulate the accurate AUC and Cmax ratios predictions and concentration time curve predictions for both the parent compound and its active metabolite. Allocation of decrease in CYP2C8 inhibition across the three inhibitory constants was arbitrary due to identifiability issues.
Conclusions: Currently 5 available CYP2C8 substrates are not sensitive to changes in gemfibrozil CYP2C8 inhibitory constants for predicted DDI effects of gemfibrozil, unlike the active metabolite of drug X. Gemfibrozil compound file optimization could benefit from in vitro CYP2C8 Ki calibration [13].
Acknowledgement: Iain Gardner designed and performed the sensitivity analysis with each CYP2C8 substrates.
References:
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