Abstract

The analysis aimed at identifying subject-specific characteristics (covariates) influ-encing exposure to daridorexant and quantification of covariate effects to determineclinical relevance. Data from 13 phase I, two phase II, and two phase III studieswere pooled to develop a population pharmacokinetic model describing darido-rexant concentration over time. Covariate effects were quantified based on modelpredictions. A two- compartment model with dose- dependent bioavailability, ab-sorption lag time, linear absorption, and nonlinear elimination described the databest. Statistically significant covariates were food status on absorption (lag timeand rate constant), time of drug administration (morning, bedtime) on absorptionrate constant, lean body weight on central volume of distribution and elimination,fat mass on peripheral volume of distribution and intercompartmental drug trans-fer, and age and alkaline phosphatase on elimination. Age, lean body weight, fatmass, and alkaline phosphatase influence exposure (area under the curve, time ofmaximum concentration after dose administration, maximum plasma concentra-tion, and next- morning concentration) to a limited extent, that is, less than 20%difference from a typical subject. Morning administration is not relevant for dari-dorexant use by insomnia patients. The food effect with simultaneous intake of ahigh-fat, high-calorie food is an extreme-case scenario unlikely to occur in clinicalpractice. Body composition, alkaline phosphatase, and age showed clinically negli-gible effects on exposure to daridorexant. Lean body weight and fat mass describedthe pharmacokinetics of daridorexant better than other body size descriptors (bodyweight, height, body mass index), suggesting a convenient physiological alternativeto reduce the number of covariates in population pharmacokinetic models. Theresults indicate that differences between subjects do not require dose adjustments.

By Andreas Krause, Dominik Lott, Janneke M. Brussee, Clemens Muehlan, Jasper Dingemanse