Literature DB >> 27395799

A comparison of two semi-mechanistic models for prolactin release and prediction of receptor occupancy following administration of dopamine D2 receptor antagonists in rats.

Amit Taneja1, An Vermeulen2, Dymphy R H Huntjens2, Meindert Danhof3, Elizabeth C M De Lange3, Johannes H Proost4.   

Abstract

We compared the model performance of two semi-mechanistic pharmacokinetic-pharmacodynamic models, the precursor pool model and the agonist-antagonist interaction model, to describe prolactin response following the administration of the dopamine D2 receptor antagonists risperidone, paliperidone or remoxipride in rats. The time course of pituitary dopamine D2 receptor occupancy was also predicted. Male Wistar rats received a single dose (risperidone, paliperidone, remoxipride) or two consecutive doses (remoxipride). Population modeling was applied to fit the pool and interaction models to the prolactin data. The pool model was modified to predict the time course of pituitary D2 receptor occupancy. Unbound plasma concentrations of the D2 receptor antagonists were considered the drivers of the prolactin response. Both models were used to predict prolactin release following multiple doses of paliperidone. Both models described the data well and model performance was comparable. Estimated unbound EC50 for risperidone and paliperidone was 35.1nM (relative standard error 51%) and for remoxipride it was 94.8nM (31%). KI values for these compounds were 11.1nM (21%) and 113nM (27%), respectively. Estimated pituitary D2 receptor occupancies for risperidone and remoxipride were comparable to literature findings. The interaction model better predicted prolactin profiles following multiple paliperidone doses, while the pool model predicted tolerance better. The performance of both models in describing the prolactin profiles was comparable. The pool model could additionally describe the time course of pituitary D2 receptor occupancy. Prolactin response following multiple paliperidone doses was better predicted by the interaction model.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Agonist-antagonist interaction model; Dopamine D(2) receptor antagonists; Paliperidone (PubChem CID: 115237); Precursor pool model; Prolactin; Receptor occupancy; Remoxipride (PubChem CID: 54477); Risperidone (PubChem CID: 5073)

Mesh:

Substances:

Year:  2016        PMID: 27395799     DOI: 10.1016/j.ejphar.2016.07.005

Source DB:  PubMed          Journal:  Eur J Pharmacol        ISSN: 0014-2999            Impact factor:   4.432


  5 in total

1.  Revealing the Neuroendocrine Response After Remoxipride Treatment Using Multi-Biomarker Discovery and Quantifying It by PK/PD Modeling.

Authors:  Willem J van den Brink; Yin C Wong; Berfin Gülave; Piet H van der Graaf; Elizatbeth C M de Lange
Journal:  AAPS J       Date:  2016-10-26       Impact factor: 4.009

Review 2.  Schizophrenia: synthetic strategies and recent advances in drug design.

Authors:  Maria Azmanova; Anaïs Pitto-Barry; Nicolas P E Barry
Journal:  Medchemcomm       Date:  2018-03-16       Impact factor: 3.597

3.  Modeling of prolactin response following dopamine D2 receptor antagonists in rats: can it be translated to clinical dosing?

Authors:  Amit Taneja; An Vermeulen; Dymphy R H Huntjens; Meindert Danhof; Elizabeth C M De Lange; Johannes H Proost
Journal:  Pharmacol Res Perspect       Date:  2017-12

4.  Fingerprints of CNS drug effects: a plasma neuroendocrine reflection of D2 receptor activation using multi-biomarker pharmacokinetic/pharmacodynamic modelling.

Authors:  Willem J van den Brink; Dirk-Jan van den Berg; Floor E M Bonsel; Robin Hartman; Yin-Cheong Wong; Piet H van der Graaf; Elizabeth C M de Lange
Journal:  Br J Pharmacol       Date:  2018-08-31       Impact factor: 8.739

5.  Summary data of potency and parameter information from semi-mechanistic PKPD modeling of prolactin release following administration of the dopamine D2 receptor antagonists risperidone, paliperidone and remoxipride in rats.

Authors:  Amit Taneja; An Vermeulen; Dymphy R H Huntjens; Meindert Danhof; Elizabeth C M De Lange; Johannes H Proost
Journal:  Data Brief       Date:  2016-08-06
  5 in total

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