An HCV nucleoside inhibitor MK-3682 minimal PBPK-PD model for application in hypothesis generation regarding metabolic pathways and perturbations under various conditions
Paul van den Berg (1), Teun M. Post (1), Wei Gao (2), Randy Miller (2), Filippos Kesisoglou (2), Leticia Arrington (2), Matthew L. Rizk (2)
(1) LAP&P Consultants Leiden, The Netherlands, (2) Merck & Co., Inc., Kenilworth, NJ, USA
Objectives: MK-3682 is a uridine nucleoside monophosphate prodrug inhibitor of HCV NS5B RNA polymerase. To support the understanding of its metabolism and perturbations therein linked to efficacy, a minimal physiologically based pharmacokinetic-pharmacodynamic model was developed. This framework integrated the complex interplay between MK-3682 and its C- and U-nucleoside metabolites’ (M5 and M6) plasma pharmacokinetics (PK). Following metabolism in the liver, the projected active phosphorylated form (nucleoside triphosphate; NTP), which does not circulate, was linked to efficacy. The in vitro and clinical data of various intrinsic and extrinsic factors, such as formulation (tablet, capsule, IV), DDI with CYP3A4/P-gp perpetrator itraconazole and subject status (healthy volunteers or HCV patients) were included.
Methods: A minimal PBPK model approach, based on Brill et al [1], was applied to characterize the PK of MK-3682 and its metabolism to M5 and M6 in both the gut wall and the liver. PK data from five phase I studies and one phase I/IIa study were used (n=217 subjects). Phase I studies included PK data after IV and oral (capsule or tablet) administration, and after administration of MK-3682 in the presence of the strong CYP3A4/P-gp inhibitor itraconazole. The phase I/IIa study included data from healthy volunteers and HCV patients, including an itraconazole DDI arm in HCV patients. Dose levels of orally administered MK-3682 ranged from 50-750 mg given as single and multiple doses. The minimal PBPK model was developed in a stepwise approach. First, the base structure of the model was established using IV and tablet data after MK-3682 monotherapy in healthy volunteers. Subsequently, the influence of formulation, HCV status and itraconazole coadministration on the PK of MK-3682, M5 and M6 were investigated. Finally, the individual posthoc parameters from the PK model were used as input for investigating the link between the projected NTP and viral load (VL). The model was developed using the non-linear mixed-effects modelling software NONMEM V7.2.0 [2] and data processing was done using R [3] and RStudio [4].
Results: The minimal PBPK model leveraged knowledge of known/hypothesized metabolic pathways and provided a good fit to the PK data of MK-3682, M5 and M6. The model captured differences in PK between formulations, between HCV patients and healthy volunteers and between MK-3682 monotherapy or coadministration with itraconazole. The model consisted of gut wall, portal vein and liver compartments for MK-3682, while empirical compartments were used to describe the metabolic pathways to M5 and M6. Separate formation pathways of M5 and M6 in the gut wall and in liver could be identified. This was particularly important for investigating the link between PK and efficacy, as only M5 and M6 formed in liver are derivatives of NTP. In order to capture the less than proportional PK observed for M6 after oral dosing, M6 uptake in gut depended on the estimated gut M6 concentration. This did not affect MK-3682 and M5 PK, which increased linearly with dose. Although presence of an M5 gut formation route was not initially anticipated, inclusion of this route was needed to describe the PK for M5 after oral dosing. A concentration-dependent rate between the two NTP compartments in liver (UXP and CXP) was needed to fit single as well as multiple dose data simultaneously. The larger effect on viral load in the presence of itraconazole could be explained by the model as well. Due to inhibition of gut metabolism and/or inhibition of active transport from the gut wall via P-gp, more MK-3682 reaches the liver. This results in higher NTP concentrations, which explains the higher log drop in viral load.
Conclusions: The minimal PBPK model, in combination with the identified link between projected NTP and viral load, provided a better understanding of the complex hypothesized metabolism of MK-3682 and of the relationship between plasma PK and projected liver NTP. The model captured differences in PK between formulations and between patients and healthy volunteers. In addition, the enhanced efficacy observed in patients with HCV when itraconazole was coadministered with MK-3682 was explained by the model. Overall, this framework supported and guided hypothesis generation and understanding regarding underlying metabolic pathways and perturbations under various conditions, including impact on downstream viral load.
References:
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[2] Beal SL, Sheiner LB, Boeckmann AJ & Bauer RJ (Eds.) NONMEM Users Guides. 1989-2011. Icon Development Solutions, Ellicott City, Maryland, USA.
[3] R Core Team (2017). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org.
[4] RStudio Team (2017). RStudio: Integrated Development Environment for R. RStudio, Inc., Boston. URL http://www.RStudio.com/.
