Pharmacokinetic and Pharmacodynamic Modeling and Simulation Analysis of Nesuparib (JPI-547) in Patients with Advanced Solid Tumor
Seung Chan Choi(1,2), Sang Min Lee(1,2), Moon Hee Lee(1,2), Soo-Min Jung(1,2),John Kim(3), Hyunju Cha(3), Hyeoung-Seok Lim(1,2)
(1) Department of Clinical Pharmacology and Therapeutics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea, (2) Department of Medical Science and Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea, (3) Onconic therapeutics, Seoul 06236, Republic of Korea
Introduction:
Nesuparib (JPI-547) is an anti-cancer agent under development that acts as a dual inhibitor of poly(ADP-ribose) polymerase and tankyrase. Reduction of poly(ADP-ribose) (PAR) concentration in peripheral blood mononuclear cell (PBMC) is the biomarker reflecting the proposed mechanism of action. To identify the optimal dosing regimen, PK-PD modeling and simulation of JPI-547 were performed.
Objectives:
1) To characterize PK of JPI-547 for JPI-547 (Parent) and M1 (a Metabolite)
2) To characterize PD of JPI-547 for PAR concentration in PBMC
3) To explore the PK-PD over time following JPI-547
4) To predict plasma JPI-547 concentration over time following various dosing regimens of JPI-547
5) To predict PAR concentration over time following various dosing regimens of JPI-547
6) To characterize exposure-PAR concentration relationship of JPI-547
Methods:
The concentrations of JPI-547 and its metabolite M1 in plasma and PAR in PBMC were measured for 22 patients with advanced solid tumor who received multiple oral doses of 50, 100, 150 or 200 mg JPI-547 in phase 1 clinical trial (NCT04335604). Mixed effect PK-PD model was established sequentially using NONMEM® 7.4.3 (ICON plc, Gaithersburg, MD). PK model was built first, and then PK-PD model was established by fixing the parameters in PK part of the model at the population PK parameter estimates (θ, ω2 and σ2) of the PK model. PK model was fit for JPI-547 and its metabolite, M1 simultaneously. Due to unidentifiability problem, central volume of distribution of M1 was fixed at the individual volume of distribution of JPI-547. Response surface model to characterize effect of both JPI-547 and its metabolite, M1 on PAR level changes simultaneously taking the interaction between the two compounds into account. Monte Carlo simulations of exposure and response were conducted for various dosing regimens with the established PK-PD model.
Results:
PAR level decreased rapidly soon after oral administration of JPI-547 and clear exposure-response relationship was observed. One-compartment PK model with absorption delay and mixed first- and zero-order absorption kinetics best described the observed concentration of parent and metabolite. Response-surface PD model well described the simultaneous effects of JPI-547 and M1 on PAR level. The half maximal inhibitory concentration (IC50) was estimated to be 67.8 nmol/L for JPI-547 and 145.0 nmol/L for M1. For daily dosing of 25 mg for 5 days in a 7-day cycle, simulation study showed that steady-state average concentration of JPI-547 was 562.5 nmol/L and that of M1 was 323.7 nmol/L, which exceeded respective IC50 values.
Conclusions:
The PK-PD model of JPI-547 was successful and the potencies of JPI-547 and M1 were estimated. Simulation study suggests that JPI-547 is expected to exert pharmacologic effect at relatively low doses. The current modeling and simulation analyses characterized PK and PD of JPI-547, which will be useful in guiding efficient drug development.
References:
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[3] R Development Core Team. R: A language and environment for statistical computing. In, Vienna, Autria, 2018.