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Physiologically Based Pharmacokinetic Modelling to Predict Single- and Multiple-Dose Human Pharmacokinetics of Bitopertin

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Abstract

Background

Bitopertin (RG1678) is a glycine reuptake inhibitor currently in phase 3 trials for treatment of schizophrenia. This paper describes the use of physiologically based pharmacokinetic (PBPK) modelling and preclinical data to gain insights into and predict bitopertin clinical pharmacokinetics.

Methods

Simulations of pharmacokinetics were initiated early in the drug discovery stage by integrating physicochemical properties and in vitro measurements into a PBPK rat model. Comparison of pharmacokinetics predicted by PBPK modelling with those measured after intravenous and oral dosing in rats and monkeys showed a good match and thus increased confidence that a similar approach could be applied for human prediction. After comparison of predicted plasma concentrations with those measured after single oral doses in the first clinical study, the human model was refined and then applied to simulate multiple-dose pharmacokinetics.

Results

Clinical plasma concentrations measured were in good agreement with PBPK predictions. Predicted area under the plasma concentration–time curve (AUC) was within twofold of the observed mean values for all dose levels. Maximum plasma concentration (C max) at higher doses was well predicted but approximately twofold below observed values at the lower doses. A slightly less than dose-proportional increase in both AUC and C max was observed, and model simulations indicated that when the dose exceeded 50 mg, solubility limited the fraction of dose absorbed. Refinement of the absorption model with additional solubility and permeability measurements further improved the match of simulations to observed single-dose data. Simulated multiple-dose pharmacokinetics with the refined model were in good agreement with observed data.

Conclusions

Clinical pharmacokinetics of bitopertin can be well simulated with a mechanistic PBPK model. This model supports further clinical development and provides a valuable repository for pharmacokinetic knowledge gained about the molecule.

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Acknowledgments

This study was funded by F. Hoffmann-La Roche. All authors were employees of F. Hoffmann-La Roche when this work was carried out. They have no other conflicts of interest to declare.

Author contribution

Participated in research design: Parrott, Hainzl, Martin-Facklam, Boutouyrie, Alberati. Conducted experiments: Hainzl, Alberati, Martin-Facklam, Boutouyrie, Hofmann, Robson. Performed data analysis: Parrott, Hofmann. Wrote or contributed to writing the manuscript: Parrott, Martin-Facklam. Reviewed manuscript drafts and approved final version for submission: Parrott, Hainzl, Alberati, Hoffmann, Robson, Boutouyrie, and Martin-Facklam.

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Authors and Affiliations

  1. Non-Clinical Safety, Pharmaceuticals Division, F. Hoffmann-La Roche Ltd., Bau 70/130, Grenzacherstrasse, Basel, Switzerland

    Neil Parrott & Dominik Hainzl

  2. Discovery Neuroscience, Pharmaceuticals Division, F. Hoffmann-La Roche Ltd., Basel, Switzerland

    Daniela Alberati

  3. Clinical Pharmacology, Pharmaceuticals Division, F. Hoffmann-La Roche Ltd., Basel, Switzerland

    Carsten Hofmann & Meret Martin-Facklam

  4. Christchurch Clinical Studies Trust, Christchurch, New Zealand

    Richard Robson

  5. Clinical Pharmacology, Shire AG, Eysins, Switzerland

    Bruno Boutouyrie

Authors
  1. Neil Parrott
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  2. Dominik Hainzl
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  4. Carsten Hofmann
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  7. Meret Martin-Facklam
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Correspondence to Neil Parrott.

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Parrott, N., Hainzl, D., Alberati, D. et al. Physiologically Based Pharmacokinetic Modelling to Predict Single- and Multiple-Dose Human Pharmacokinetics of Bitopertin. Clin Pharmacokinet 52, 673–683 (2013). https://doi.org/10.1007/s40262-013-0061-x

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