Population pharmacokinetic analysis of tepotinib, an oral MET kinase inhibitor, including data from the VISION study

Abstract

Purpose: Tepotinib is a highly selective, potent, mesenchymal-epithelial transition factor (MET) inhibitor, approved for the treatment of non-small cell lung cancer (NSCLC) harboring MET exon 14 skipping. Objectives of this population pharmacokinetic (PK) analysis were to evaluate the dose-exposure relationship of tepotinib and its major circulating metabolite, MSC2571109A, and to identify the intrinsic/extrinsic factors that are predictive of PK variability.

Methods: Data were included from 12 studies in patients with cancer and in healthy participants. A sequential modeling approach was used to analyze the parent and metabolite data, including covariate analyses. Potential associations between observed covariates and PK parameters were illustrated using bootstrap analysis-based forest plots.

Results: A two-compartment model with sequential zero- and first-order absorption, and a first-order elimination from the central compartment, best described the plasma PK of tepotinib in humans across the dose range of 30-1400 mg. The bioavailability of tepotinib was shown to be dose dependent, although bioavailability decreased primarily at doses above the therapeutic dose of 500 mg. The intrinsic factors of race, age, sex, body weight, mild/moderate hepatic impairment and mild/moderate renal impairment, along with the extrinsic factors of opioid analgesic and gefitinib intake, had no relevant effect on tepotinib PK. Tepotinib has a long effective half-life of ~ 32 h.

Conclusions: Tepotinib shows dose proportionality up to at least the therapeutic dose, and time-independent clearance with a profile appropriate for once-daily dosing. None of the covariates identified had a clinically meaningful effect on tepotinib exposure or required dose adjustments.

Trial registration: ClinicalTrials.gov NCT02864992.

Keywords: MET kinase inhibitor; NSCLC; Population PK; Tepotinib.

Conflict of interest statement

Wenyuan Xiong was employed by the Merck Institute of Pharmacometrics, Lausanne, Switzerland, an affiliate of Merck KGaA for the duration of the study. Orestis Papasouliotis and Pascal Girard are employees of the Merck Institute of Pharmacometrics, Lausanne, Switzerland, an affiliate of Merck KGaA. Rainer Strotmann is an employee of Merck Healthcare KGaA, Darmstadt, Germany. E. Niclas Jonsson is an employee of Pharmetheus AB, Sweden.

© 2022. The Author(s).

Figures

Fig. 1

Illustration of the base population pharmacokinetics model for tepotinib and MSC2571109A. CL clearance, D1 zero-order absorption duration, FM fraction of tepotinib metabolized to MSC2571109A, ka first-order absorption rate constant, met metabolite, par parent, Q inter-compartmental clearance, Vc central volume of distribution, Vp peripheral volume of distribution

Fig. 2

Predicted tepotinib AUCss versus dose, with and without the estimated dose effect on Fpar. The blue line represents the relationship between AUCss and dose according to the final tepotinib model, while the grey, dashed line displays the theoretical relationship between tepotinib AUCss and dose if the dose had no impact on Fpar. AUCss area under the curve at steady state, par parent, eGFR estimated glomerular filtration rate, INR international normalized ratio, NSCLC non-small cell lung cancer, QD once daily, TF tablet formulation. Note: The prediction is for a typical patient with NSCLC (59 years, 72 kg, serum albumin = 40 g/L, eGFR = 97.28 mL/min/1.73 m2, INR = 1.06) receiving 500 mg QD tepotinib TF3 with food

Fig. 3

Simulation of tepotinib PK profile for a typical patient with NSCLC (59 years, 72 kg, serum albumin = 40 g/L, eGFR = 97.28 mL/min/1.73 m2, INR = 1.06) receiving 500 mg QD tepotinib TF3 with food. The solid black line represents the median prediction of the PK time profile, and the green shaded area represents a simulation-based 5–95% prediction interval for PK time profile. eGFR estimated glomerular filtration rate, INR international normalized ratio, NSCLC non-small cell lung cancer, PK pharmacokinetics, QD once daily, TF tablet formulation

Fig. 4

The distribution of tepotinib AUCss stratified by selected race categories, based on the final tepotinib population PK model and using the analysis data set. The predictions of AUCτ,ss are for Caucasian, Other East Asian and Japanese participants in the tepotinib analysis data set receiving 500 mg tepotinib with the TF1 or TF2 formulation and having a standard breakfast. The horizontal line in the box indicates the median value, the box edges represent the 25th and 75th percentiles, and the whiskers extend from the box to the furthest data points still within a distance of 1.5 times the interquartile range from the box. Data points, which are jittered in the horizontal direction, show the individually predicted AUCss values. The numbers represent the number of individuals in each strata. AUCss area under the curve at steady state, PK pharmacokinetics, TF tablet formulation

Fig. 5

Forest plot showing the association of the predicted tepotinib AUCss and covariates assuming a dosing regimen of 500 mg tepotinib daily, based on the final tepotinib population PK model, for cancer patients in the analysis data set. The closed symbols represent the mean ratio of individual parameter estimates for the applicable covariate category or value (5th or 95th percentile for continuous covariates) percentile relative to the mean parameter estimate (vertical solid line) for cancer patients in the analysis dataset. The whiskers represent the 90% CI of the mean values, based on 100 bootstrap samples. AUCss area under the curve at steady state, CI confidence interval, ECOG Eastern Cooperative Oncology Group, eGFR estimated glomerular filtration rate, NCI-ODG National Cancer Institute Organ Dysfunction Group, PK pharmacokinetic