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Development and Evaluation of a Physiologically Based Pharmacokinetic Model for Predicting Haloperidol Exposure in Healthy and Disease Populations

The physiologically based pharmacokinetic (PBPK) approach can be used to develop mathematical models for predicting the absorption, distribution, metabolism, and elimination (ADME) of administered drugs in virtual human populations. Haloperidol is a typical antipsychotic drug with a narrow therapeut...

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Autores principales: Alasmari, Mohammed S., Alasmari, Fawaz, Alasmari, Abdullah F., Alshamsan, Aws, Alsanea, Sary, Rasool, Muhammad F., Alqahtani, Faleh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9506126/
https://www.ncbi.nlm.nih.gov/pubmed/36145543
http://dx.doi.org/10.3390/pharmaceutics14091795
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author Alasmari, Mohammed S.
Alasmari, Fawaz
Alasmari, Abdullah F.
Alshamsan, Aws
Alsanea, Sary
Rasool, Muhammad F.
Alqahtani, Faleh
author_facet Alasmari, Mohammed S.
Alasmari, Fawaz
Alasmari, Abdullah F.
Alshamsan, Aws
Alsanea, Sary
Rasool, Muhammad F.
Alqahtani, Faleh
author_sort Alasmari, Mohammed S.
collection PubMed
description The physiologically based pharmacokinetic (PBPK) approach can be used to develop mathematical models for predicting the absorption, distribution, metabolism, and elimination (ADME) of administered drugs in virtual human populations. Haloperidol is a typical antipsychotic drug with a narrow therapeutic index and is commonly used in the management of several medical conditions, including psychotic disorders. Due to the large interindividual variability among patients taking haloperidol, it is very likely for them to experience either toxic or subtherapeutic effects. We intend to develop a haloperidol PBPK model for identifying the potential sources of pharmacokinetic (PK) variability after intravenous and oral administration by using the population-based simulator, PK-Sim. The model was initially developed and evaluated to predict the PK of haloperidol and its reduced metabolite in adult healthy population after intravenous and oral administration. After evaluating the developed PBPK model in healthy adults, it was used to predict haloperidol–rifampicin drug–drug interaction and was extended to tuberculosis patients. The model evaluation was performed using visual assessments, prediction error, and mean fold error of the ratio of the observed-to-predicted values of the PK parameters. The predicted PK values were in good agreement with the corresponding reported values. The effects of the pathophysiological changes and enzyme induction associated with tuberculosis and its treatment, respectively, on haloperidol PK, have been predicted precisely. For all clinical scenarios that were evaluated, the predicted values were within the acceptable two-fold error range.
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spelling pubmed-95061262022-09-24 Development and Evaluation of a Physiologically Based Pharmacokinetic Model for Predicting Haloperidol Exposure in Healthy and Disease Populations Alasmari, Mohammed S. Alasmari, Fawaz Alasmari, Abdullah F. Alshamsan, Aws Alsanea, Sary Rasool, Muhammad F. Alqahtani, Faleh Pharmaceutics Article The physiologically based pharmacokinetic (PBPK) approach can be used to develop mathematical models for predicting the absorption, distribution, metabolism, and elimination (ADME) of administered drugs in virtual human populations. Haloperidol is a typical antipsychotic drug with a narrow therapeutic index and is commonly used in the management of several medical conditions, including psychotic disorders. Due to the large interindividual variability among patients taking haloperidol, it is very likely for them to experience either toxic or subtherapeutic effects. We intend to develop a haloperidol PBPK model for identifying the potential sources of pharmacokinetic (PK) variability after intravenous and oral administration by using the population-based simulator, PK-Sim. The model was initially developed and evaluated to predict the PK of haloperidol and its reduced metabolite in adult healthy population after intravenous and oral administration. After evaluating the developed PBPK model in healthy adults, it was used to predict haloperidol–rifampicin drug–drug interaction and was extended to tuberculosis patients. The model evaluation was performed using visual assessments, prediction error, and mean fold error of the ratio of the observed-to-predicted values of the PK parameters. The predicted PK values were in good agreement with the corresponding reported values. The effects of the pathophysiological changes and enzyme induction associated with tuberculosis and its treatment, respectively, on haloperidol PK, have been predicted precisely. For all clinical scenarios that were evaluated, the predicted values were within the acceptable two-fold error range. MDPI 2022-08-26 /pmc/articles/PMC9506126/ /pubmed/36145543 http://dx.doi.org/10.3390/pharmaceutics14091795 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Alasmari, Mohammed S.
Alasmari, Fawaz
Alasmari, Abdullah F.
Alshamsan, Aws
Alsanea, Sary
Rasool, Muhammad F.
Alqahtani, Faleh
Development and Evaluation of a Physiologically Based Pharmacokinetic Model for Predicting Haloperidol Exposure in Healthy and Disease Populations
title Development and Evaluation of a Physiologically Based Pharmacokinetic Model for Predicting Haloperidol Exposure in Healthy and Disease Populations
title_full Development and Evaluation of a Physiologically Based Pharmacokinetic Model for Predicting Haloperidol Exposure in Healthy and Disease Populations
title_fullStr Development and Evaluation of a Physiologically Based Pharmacokinetic Model for Predicting Haloperidol Exposure in Healthy and Disease Populations
title_full_unstemmed Development and Evaluation of a Physiologically Based Pharmacokinetic Model for Predicting Haloperidol Exposure in Healthy and Disease Populations
title_short Development and Evaluation of a Physiologically Based Pharmacokinetic Model for Predicting Haloperidol Exposure in Healthy and Disease Populations
title_sort development and evaluation of a physiologically based pharmacokinetic model for predicting haloperidol exposure in healthy and disease populations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9506126/
https://www.ncbi.nlm.nih.gov/pubmed/36145543
http://dx.doi.org/10.3390/pharmaceutics14091795
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