Development of a Population Pharmacokinetic Model for the Diroximel Fumarate Metabolites Monomethyl Fumarate and 2-Hydroxyethyl Succinimide Following Oral Administration of Diroximel Fumarate in Healthy Participants and Patients with Multiple Sclerosis

Abstract

Introduction: Diroximel fumarate (DRF) is a next-generation oral fumarate that is indicated in the USA for relapsing forms of multiple sclerosis (MS). A joint population pharmacokinetic model was developed for the major active metabolite (monomethyl fumarate, MMF) and the major inactive metabolite (2-hydroxyethyl succinimide, HES) of DRF.

Methods: MMF and HES data were included from 341 healthy volunteers and 48 patients with MS across 11 phase I and III studies in which DRF was administered as single or multiple doses. Population modeling was performed with NONMEM version 7.3 with the first-order conditional estimation method.

Results: Estimated MMF clearance (CL_MMF), volume of distribution, and absorption rate constant (Ka) were 13.5 L/h, 30.4 L, and 5.04 h^-1, respectively. CL_MMF and HES clearance (CL_HES) increased with increasing body weight. CL_HES decreased with decreasing renal function. CL_MMF and CL_HES were 28% and 12% lower in patients with MS than in healthy volunteers, respectively. Ka was reduced in the presence of low-, medium-, and high-fat meals by 37%, 51%, and 67%, respectively, for MMF; and by 34%, 49%, and 62%, respectively, for HES.

Conclusions: Age, sex, race, and baseline liver function parameters such as total bilirubin, albumin, and aspartate aminotransferase were not considered to be significant predictors of MMF or HES disposition.

Keywords: 2-Hydroxyethyl succinimide; Diroximel fumarate; Monomethyl fumarate; Multiple sclerosis; Pharmacokinetics; Population pharmacokinetics.

Fig. 1

Pharmacokinetic model (a) and summary of model development steps (b). A single term was estimated for the Vc in the population PK model (i.e., V2 = V3). CL_HES clearance of HES, CL_MMF clearance of MMF, CMT compartment, eGFR estimated glomerular filtration rate, F1 bioavailability of MMF, F4 bioavailability of HES, HES 2-hydroxyethyl succinimide, IOV interoccasion variability, K20 elimination rate constant for MMF (= CL_MMF/V2), K30 elimination rate constant for HES (= CL_HES/V3), Ka_HES absorption rate constant of HES, Ka_MMF absorption rate constant of MMF, MMF monomethyl fumarate, PK pharmacokinetics, PM evening dose, V2 central CMT distribution volume of MMF, V3 central CMT distribution volume of HES, Vc central volume of distribution, WT body weight

Fig. 2

Illustration of covariate effects on steady state exposure of MMF (a) and HES (b) in healthy participants. Blue circles show the ratio of the median parameter value under the test conditions compared with the reference healthy participant with median body weight of 78 kg (and median eGFR of 111.9 mL/min), for (b), receiving DRF in a fasted state. Test conditions for body weight include the 5th, 25th, 75th, and 95th percentiles of body weight among participants in the analysis dataset. Test conditions for dietary fat include administration of DRF with a low-, medium-, and high-fat meal. Test conditions for renal function include four values of eGFR within each renal function category: normal (eGFR = 120, 110, 100, 90 mL/min); mild impairment (eGFR = 89, 80, 70, 60 mL/min); moderate impairment (59, 50, 40, 30 mL/min); and severe impairment (eGFR = 29, 25, 20, 15 mL/min), summarized within each category. The blue line segments represent the corresponding 90% prediction interval for the reference conditions. Vertical dashed lines indicate the 90% prediction interval for the reference conditions. Simulations (N = 1000) were performed for virtual participants (one per test condition and reference), with parameter values fixed to the final model parameter estimates and incorporating interindividual variability (i.e., individual population-predicted–derived concentration–time profiles were generated). AUC_0–12h,ss steady state area under the plasma drug concentration–time curve over the 0–12-h dosing interval, C_{max0–12h,ss} steady state maximum plasma drug concentration over the 0–12-h dosing interval, DRF diroximel fumarate, eGFR estimated glomerular filtration rate, HES 2-hydroxyethyl succinimide, MMF monomethyl fumarate, P05 5th percentile, P25 25th percentile, P75 75th percentile, P95 95th percentile

Fig. 3

Model-based simulation of MMF concentration–time profiles (a) and MMF C_{max0–12h,ss} (b) with meal fat content in healthy participants and patients with MS following administration of DRF 462 mg BID. Reference: in the simulations for a, participants had body weight of 78 kg and eGFR of 111.9 mL/min. Reference: in the simulations for b, individual population-predicted–derived concentration–time profiles were generated for participants with body weight of 78 kg and eGFR of 111.9 mL/min. Simulation: four virtual healthy participants (one fasted and on per meal fat content category: low, medium, high) and one virtual patient (unknown meal fat content); N = 1000 per participant. Dose: 462 mg DRF BID for 7 days. BID twice daily, C_max0-12h,ss, steady state maximum concentration for the 0–12-h dosing interval following a morning dose, DRF diroximel fumarate, eGFR estimated glomerular filtration rate, HV healthy volunteer, MMF monomethyl fumarate, MS multiple sclerosis