title: Application of a Bayesian approach to physiological modelling of mavoglurant population pharmacokinetics.
abstract: Mavoglurant (MVG) is an antagonist at the metabotropic glutamate receptor-5 currently under clinical development at Novartis Pharma AG for the treatment of central nervous system diseases. The aim of this study was to develop and optimise a population whole-body physiologically-based pharmacokinetic (WBPBPK) model for MVG, to predict the impact of drug-drug interaction (DDI) and age on its pharmacokinetics. In a first step, the model was fitted to intravenous (IV) data from a clinical study in adults using a Bayesian approach. In a second step, the optimised model was used together with a mechanistic absorption model for exploratory Monte Carlo simulations. The ability of the model to predict MVG pharmacokinetics when orally co-administered with ketoconazole in adults or administered alone in 3-11 year-old children was evaluated using data from three other clinical studies. The population model provided a good description of both the median trend and variability in MVG plasma pharmacokinetics following IV administration in adults. The Bayesian approach offered a continuous flow of information from pre-clinical to clinical studies. Prediction of the DDI with ketoconazole was consistent with the results of a non-compartmental analysis of the clinical data (threefold increase in systemic exposure). Scaling of the WBPBPK model allowed reasonable extrapolation of MVG pharmacokinetics from adults to children. The model can be used to predict plasma and brain (target site) concentration-time profiles following oral administration of various immediate-release formulations of MVG alone or when co-administered with other drugs, in adults as well as in children.
authors.affiliation: Manchester Pharmacy School, The University of Manchester, Manchester, UK.|Drug Metabolism and Pharmacokinetics, Novartis Institutes for Biomedical Research, Basel, Switzerland.
authors.forename: Thierry
authors.initials: T
authors.lastname: Wendling
authors.affiliation: Drug Metabolism and Pharmacokinetics, Novartis Institutes for Biomedical Research, Basel, Switzerland.
authors.forename: Swati
authors.initials: S
authors.lastname: Dumitras
authors.affiliation: Manchester Pharmacy School, The University of Manchester, Manchester, UK.
authors.forename: Kayode
authors.initials: K
authors.lastname: Ogungbenro
authors.affiliation: Manchester Pharmacy School, The University of Manchester, Manchester, UK. leon.aarons@manchester.ac.uk.
authors.forename: Leon
authors.initials: L
authors.lastname: Aarons
mesh_terms: D061605:Administration, Intravenous; D000284:Administration, Oral; D000328:Adult; D000367:Age Factors; D001499:Bayes Theorem; D001921:Brain / Q000378:metabolism; D002648:Child; D002675:Child, Preschool; D002986:Clinical Trials as Topic; D003198:Computer Simulation; D004334:Drug Administration Schedule; D004347:Drug Interactions; D018691:Excitatory Amino Acid Antagonists / Q000008:administration & dosage / Q000097:blood / Q000493:pharmacokinetics*; D005260:Female; D006801:Humans; D007211:Indoles / Q000008:administration & dosage / Q000097:blood / Q000493:pharmacokinetics*; D007654:Ketoconazole / Q000008:administration & dosage; D008297:Male; D008390:Markov Chains; D008954:Models, Biological; D015233:Models, Statistical; D009010:Monte Carlo Method; D014018:Tissue Distribution
chemical_list: D018691:Excitatory Amino Acid Antagonists; D007211:Indoles; C581397:mavoglurant; D007654:Ketoconazole
keywords: Bayesian analysis; Drug–drug interactions; Mavoglurant; Paediatrics; Physiologically-based pharmacokinetic models; Population pharmacokinetics