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Predicting Hydroxychloroquine Clearance in Healthy and Diseased Populations Using a Physiologically Based Pharmacokinetic Approach

Hydroxychloroquine (HCQ), a congener of chloroquine, is widely used in prophylaxis and the treatment of malaria, and also as a cure for rheumatoid arthritis, systemic lupus erythematosus, and various other diseases. Physiologically based pharmacokinetic modeling (PBPK) has attracted great interest i...

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Autores principales: Alqahtani, Faleh, Asiri, Ali Mohammed, Zamir, Ammara, Rasool, Muhammad Fawad, Alali, Amer S., Alsanea, Sary, Walbi, Ismail A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10140819/
https://www.ncbi.nlm.nih.gov/pubmed/37111735
http://dx.doi.org/10.3390/pharmaceutics15041250
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author Alqahtani, Faleh
Asiri, Ali Mohammed
Zamir, Ammara
Rasool, Muhammad Fawad
Alali, Amer S.
Alsanea, Sary
Walbi, Ismail A.
author_facet Alqahtani, Faleh
Asiri, Ali Mohammed
Zamir, Ammara
Rasool, Muhammad Fawad
Alali, Amer S.
Alsanea, Sary
Walbi, Ismail A.
author_sort Alqahtani, Faleh
collection PubMed
description Hydroxychloroquine (HCQ), a congener of chloroquine, is widely used in prophylaxis and the treatment of malaria, and also as a cure for rheumatoid arthritis, systemic lupus erythematosus, and various other diseases. Physiologically based pharmacokinetic modeling (PBPK) has attracted great interest in the past few years in predicting drug pharmacokinetics (PK). This study focuses on predicting the PK of HCQ in the healthy population and extrapolating it to the diseased populations, i.e., liver cirrhosis and chronic kidney disease (CKD), utilizing a systematically built whole-body PBPK model. The time vs. concentration profiles and drug-related parameters were obtained from the literature after a laborious search and in turn were integrated into PK-Sim software for designing healthy intravenous, oral, and diseased models. The model’s evaluation was performed using observed-to-predicted ratios (Robs/Rpre) and visual predictive checks within a 2-fold error range. The healthy model was then extrapolated to liver cirrhosis and CKD populations after incorporating various disease-specific pathophysiological changes. Box–whisker plots showed an increase in AUC(0-t) in liver cirrhosis, whereas a decrease in AUC(0-t) was seen in the CKD population. These model predictions may assist clinicians in adjusting the administered HCQ doses in patients with different degrees of hepatic and renal impairment.
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spelling pubmed-101408192023-04-29 Predicting Hydroxychloroquine Clearance in Healthy and Diseased Populations Using a Physiologically Based Pharmacokinetic Approach Alqahtani, Faleh Asiri, Ali Mohammed Zamir, Ammara Rasool, Muhammad Fawad Alali, Amer S. Alsanea, Sary Walbi, Ismail A. Pharmaceutics Article Hydroxychloroquine (HCQ), a congener of chloroquine, is widely used in prophylaxis and the treatment of malaria, and also as a cure for rheumatoid arthritis, systemic lupus erythematosus, and various other diseases. Physiologically based pharmacokinetic modeling (PBPK) has attracted great interest in the past few years in predicting drug pharmacokinetics (PK). This study focuses on predicting the PK of HCQ in the healthy population and extrapolating it to the diseased populations, i.e., liver cirrhosis and chronic kidney disease (CKD), utilizing a systematically built whole-body PBPK model. The time vs. concentration profiles and drug-related parameters were obtained from the literature after a laborious search and in turn were integrated into PK-Sim software for designing healthy intravenous, oral, and diseased models. The model’s evaluation was performed using observed-to-predicted ratios (Robs/Rpre) and visual predictive checks within a 2-fold error range. The healthy model was then extrapolated to liver cirrhosis and CKD populations after incorporating various disease-specific pathophysiological changes. Box–whisker plots showed an increase in AUC(0-t) in liver cirrhosis, whereas a decrease in AUC(0-t) was seen in the CKD population. These model predictions may assist clinicians in adjusting the administered HCQ doses in patients with different degrees of hepatic and renal impairment. MDPI 2023-04-15 /pmc/articles/PMC10140819/ /pubmed/37111735 http://dx.doi.org/10.3390/pharmaceutics15041250 Text en © 2023 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
Alqahtani, Faleh
Asiri, Ali Mohammed
Zamir, Ammara
Rasool, Muhammad Fawad
Alali, Amer S.
Alsanea, Sary
Walbi, Ismail A.
Predicting Hydroxychloroquine Clearance in Healthy and Diseased Populations Using a Physiologically Based Pharmacokinetic Approach
title Predicting Hydroxychloroquine Clearance in Healthy and Diseased Populations Using a Physiologically Based Pharmacokinetic Approach
title_full Predicting Hydroxychloroquine Clearance in Healthy and Diseased Populations Using a Physiologically Based Pharmacokinetic Approach
title_fullStr Predicting Hydroxychloroquine Clearance in Healthy and Diseased Populations Using a Physiologically Based Pharmacokinetic Approach
title_full_unstemmed Predicting Hydroxychloroquine Clearance in Healthy and Diseased Populations Using a Physiologically Based Pharmacokinetic Approach
title_short Predicting Hydroxychloroquine Clearance in Healthy and Diseased Populations Using a Physiologically Based Pharmacokinetic Approach
title_sort predicting hydroxychloroquine clearance in healthy and diseased populations using a physiologically based pharmacokinetic approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10140819/
https://www.ncbi.nlm.nih.gov/pubmed/37111735
http://dx.doi.org/10.3390/pharmaceutics15041250
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