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The AAPS Journal

, Volume 15, Issue 2, pp 533–541 | Cite as

Predictions of In Vivo Prolactin Levels from In Vitro K i Values of D2 Receptor Antagonists Using an Agonist–Antagonist Interaction Model

  • Klas J. Petersson
  • An M. Vermeulen
  • Lena E. Friberg
Research Article

Abstract

Prolactin elevation is a side effect of all currently available D2 receptor antagonists used in the treatment of schizophrenia. Prolactin elevation is the result of a direct antagonistic D2 effect blocking the tonic inhibition of prolactin release by dopamine. The aims of this work were to assess the correlation between in vitro estimates of D2 receptor affinity and pharmacokinetic–pharmacodynamic model-based estimates obtained from analysis of clinical data using an agonist–antagonist interaction (AAI) model and to assess the value of such a correlation in early prediction of full prolactin time profiles. A population model describing longitudinal prolactin data was fitted to clinical data from 16 clinical phases 1 and 3 trials including five different compounds. Pharmacokinetic data were modeled for each compound and the prolactin model was both fitted in per-compound fits as well as simultaneously to all prolactin data. Estimates of prolactin elevating potency were compared to corresponding in vitro values and their predictability was evaluated through model-based simulations. The model successfully described the prolactin time course for all compounds. Estimates derived from experimental preclinical data and the model fit of the clinical data were strongly correlated (p < 0.001), and simulations adequately predicted the prolactin elevation in five out of six compounds. The AAI model has the potential to be used in drug development to predict prolactin response for a given exposure of D2 antagonists using routinely produced preclinical data.

Key words

in vitroin vivo correlation pharmacodynamic scaling population modeling prolactin 

Notes

Acknowledgments

Klas Petersson would like to acknowledge Janssen Pharmaceutica N.V. for sponsorship of his PhD work. Part of the computations were performed on resources provided by SNIC through Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) under Project p2011063

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Copyright information

© American Association of Pharmaceutical Scientists 2013

Authors and Affiliations

  • Klas J. Petersson
    • 1
  • An M. Vermeulen
    • 2
  • Lena E. Friberg
    • 1
  1. 1.Department of Pharmaceutical BiosciencesUppsala UniversityUppsalaSweden
  2. 2.Division of Janssen PharmaceuticaJanssen Research & DevelopmentBeerseBelgium

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