Journal of Pharmacokinetics and Pharmacodynamics

, Volume 42, Issue 6, pp 639–657 | Cite as

Application of a Bayesian approach to physiological modelling of mavoglurant population pharmacokinetics

  • Thierry Wendling
  • Swati Dumitras
  • Kayode Ogungbenro
  • Leon AaronsEmail author
Original Paper


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.


Mavoglurant Population pharmacokinetics Physiologically-based pharmacokinetic models Bayesian analysis Drug–drug interactions Paediatrics 



The authors would like to thank Nikolaos Tsamandouras and Andres Olivares-Morales (Manchester Pharmacy School, The University of Manchester, Manchester, United-Kingdom) for fruitful discussions.

Compliance with ethical standards

Conflict of interest

Thierry Wending is an employee of Novartis Pharma AG and a Ph.D. student at the University of Manchester.

Supplementary material

10928_2015_9430_MOESM1_ESM.docx (954 kb)
Supplementary material 1 (DOCX 954 kb)


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Thierry Wendling
    • 1
    • 2
  • Swati Dumitras
    • 2
  • Kayode Ogungbenro
    • 1
  • Leon Aarons
    • 1
    Email author
  1. 1.Manchester Pharmacy SchoolThe University of ManchesterManchesterUK
  2. 2.Drug Metabolism and PharmacokineticsNovartis Institutes for Biomedical ResearchBaselSwitzerland

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