Population pharmacokinetic modelling of NS2330 (tesofensine) and its major metabolite in patients with Alzheimer's disease

Abstract

To develop a population pharmacokinetic model for NS2330 and its major metabolite M1 based on data from a 14 week proof of concept study in patients with Alzheimer's disease, and to identify covariates that might influence the pharmacokinetic characteristics of the drug and/or its metabolite. Plasma data from 320 subjects undergoing multiple oral dosing, and consisting of 1969 NS2330 and 1714 metabolite concentrations were fitted simultaneously using NONMEM. Plasma concentration-time profiles of NS2330 and M1 were best described by one-compartment models with first-order elimination for both compounds. Absorption of NS2330 was best modelled by a first-order process. Low apparent clearances together with large apparent volumes of distribution resulted in long half-lives of 234 h (NS2330) and 374 h (M1). The covariate analysis identified weight, sex, CL(CR), BMI and age as influencing the pharmacokinetics of NS2330 and/or M1. However, simulations performed revealed that only CL(CR) and sex had a significant effect on the steady-state plasma concentration-time profiles. Females with a creatinine clearance of 35.6 ml min(-1) showed a 62% increased exposure compared with males without renal impairment. The robustness and accuracy of the model were demonstrated by the successful predictivity of an external dataset. A descriptive, robust and predictive model for NS2330 and its M1 metabolite was developed. Important covariates influencing pharmacokinetics were identified, which might guide the further development of NS2330 and optimize its long-term use in the treatment of Alzheimer's disease.