caa a22 4500 605533806 CHVBK 20210128100839.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s10928-015-9430-4 doi (NATIONALLICENCE)springer-10.1007/s10928-015-9430-4 Application of a Bayesian approach to physiological modelling of mavoglurant population pharmacokinetics [Elektronische Daten] [Thierry Wendling, Swati Dumitras, Kayode Ogungbenro, Leon Aarons] 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 3-11year-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. Springer Science+Business Media New York, 2015 Mavoglurant nationallicence Population pharmacokinetics nationallicence Physiologically-based pharmacokinetic models nationallicence Bayesian analysis nationallicence Drug-drug interactions nationallicence Paediatrics nationallicence Wendling Thierry Manchester Pharmacy School, The University of Manchester, Manchester, UK aut Dumitras Swati Drug Metabolism and Pharmacokinetics, Novartis Institutes for Biomedical Research, Basel, Switzerland aut Ogungbenro Kayode Manchester Pharmacy School, The University of Manchester, Manchester, UK aut Aarons Leon Manchester Pharmacy School, The University of Manchester, Manchester, UK aut Journal of Pharmacokinetics and Pharmacodynamics Springer US; http://www.springer-ny.com 42/6(2015-12-01), 639-657 1567-567X 42:6<639 2015 42 10928 https://doi.org/10.1007/s10928-015-9430-4 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10928-015-9430-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Wendling Thierry Manchester Pharmacy School, The University of Manchester, Manchester, UK aut NATIONALLICENCE 700 1- Dumitras Swati Drug Metabolism and Pharmacokinetics, Novartis Institutes for Biomedical Research, Basel, Switzerland aut NATIONALLICENCE 700 1- Ogungbenro Kayode Manchester Pharmacy School, The University of Manchester, Manchester, UK aut NATIONALLICENCE 700 1- Aarons Leon Manchester Pharmacy School, The University of Manchester, Manchester, UK aut NATIONALLICENCE 773 0- Journal of Pharmacokinetics and Pharmacodynamics Springer US; http://www.springer-ny.com 42/6(2015-12-01), 639-657 1567-567X 42:6<639 2015 42 10928