CPT Pharmacometrics Syst Pharmacol. 2022 Oct 30. doi: 10.1002/psp4.12877. Online ahead of print.
The analysis aimed at identifying subject-specific characteristics (covariates) influencing exposure to daridorexant and quantification of covariate effects to determine clinical relevance. Data from 13 Phase 1, 2 Phase 2, and 2 Phase 3 studies were pooled to develop a population pharmacokinetic model describing daridorexant concentration over time. Covariate effects were quantified based on model predictions. A two-compartment model with dose-dependent bioavailability, absorption lag time, linear absorption, and nonlinear elimination described the data best. Statistically significant covariates were food status on absorption (lag time and rate constant), time of drug administration (morning, bedtime) on absorption rate constant, lean body weight on central volume of distribution and elimination, fat mass on peripheral volume of distribution and intercompartmental drug transfer, and age and alkaline phosphatase on elimination. Age, lean body weight, fat mass, and alkaline phosphatase influence exposure (AUC, tmax , Cmax , and next-morning concentration) to a limited extent, i.e., less than 20% difference from a typical subject. Morning administration is not relevant for daridorexant use by insomnia patients. The food effect with simultaneous intake of high-fat high-calorie food is an extreme-case scenario unlikely to occur in clinical practice. Body composition, alkaline phosphatase, and age showed clinically negligible effects on exposure to daridorexant. Lean body weight and fat mass described the pharmacokinetics of daridorexant better than other body size descriptors (body weight, height, body mass index), suggesting a convenient physiological alternative to reduce the number of covariates in population pharmacokinetic models. The results indicate that differences between subjects do not require dose adjustments.