Literature DB >> 33643034

Development of a Physiologically Based Pharmacokinetic Model for Hydroxychloroquine and Its Application in Dose Optimization in Specific COVID-19 Patients.

Miao Zhang1,2, Xueting Yao1, Zhe Hou1, Xuan Guo1, Siqi Tu1, Zihan Lei1, Zhiheng Yu1, Xuanlin Liu1, Cheng Cui1, Xijing Chen2, Ning Shen3, Chunli Song4, Jie Qiao5, Xiaoqiang Xiang6, Haiyan Li1,7, Dongyang Liu1.   

Abstract

In Feb 2020, we developed a physiologically-based pharmacokinetic (PBPK) model of hydroxychloroquine (HCQ) and integrated in vitro anti-viral effect to support dosing design of HCQ in the treatment of COVID-19 patients in China. This, along with emerging research and clinical findings, supported broader uptake of HCQ as a potential treatment for COVID-19 globally at the beginning of the pandemics. Therefore, many COVID-19 patients have been or will be exposed to HCQ, including specific populations with underlying intrinsic and/or extrinsic characteristics that may affect the disposition and drug actions of HCQ. It is critical to update our PBPK model of HCQ with adequate drug absorption and disposition mechanisms to support optimal dosing of HCQ in these specific populations. We conducted relevant in vitro and in vivo experiments to support HCQ PBPK model update. Different aspects of this model are validated using PK study from 11 published references. With parameterization informed by results from monkeys, a permeability-limited lung model is employed to describe HCQ distribution in the lung tissues. The updated model is applied to optimize HCQ dosing regimens for specific populations, including those taking concomitant medications. In order to meet predefined HCQ exposure target, HCQ dose may need to be reduced in young children, elderly subjects with organ impairment and/or coadministration with a strong CYP2C8/CYP2D6/CYP3A4 inhibitor, and be increased in pregnant women. The updated HCQ PBPK model informed by new metabolism and distribution data can be used to effectively support dosing recommendations for clinical trials in specific COVID-19 patients and treatment of patients with malaria or autoimmune diseases.
Copyright © 2021 Zhang, Yao, Hou, Guo, Tu, Lei, Yu, Liu, Cui, Chen, Shen, Song, Qiao, Xiang, Li and Liu.

Entities:  

Keywords:  dosing recommendation; drug-drug interaction; hydroxychloroquine; physiologically-based pharmacokinetic; specific populations

Year:  2021        PMID: 33643034      PMCID: PMC7907647          DOI: 10.3389/fphar.2020.585021

Source DB:  PubMed          Journal:  Front Pharmacol        ISSN: 1663-9812            Impact factor:   5.810


  42 in total

1.  Simultaneous quantitation of hydroxychloroquine and its metabolites in mouse blood and tissues using LC-ESI-MS/MS: An application for pharmacokinetic studies.

Authors:  Yashpal S Chhonker; Richard L Sleightholm; Jing Li; David Oupický; Daryl J Murry
Journal:  J Chromatogr B Analyt Technol Biomed Life Sci       Date:  2017-11-23       Impact factor: 3.205

2.  Hydroxychloroquine: A Physiologically-Based Pharmacokinetic Model in the Context of Cancer-Related Autophagy Modulation.

Authors:  Keagan P Collins; Kristen M Jackson; Daniel L Gustafson
Journal:  J Pharmacol Exp Ther       Date:  2018-02-08       Impact factor: 4.030

3.  Digoxin-hydroxychloroquine interaction?

Authors:  I Leden
Journal:  Acta Med Scand       Date:  1982

4.  Hydroxychloroquine in systemic lupus erythematosus: results of a French multicentre controlled trial (PLUS Study).

Authors:  Nathalie Costedoat-Chalumeau; Lionel Galicier; Olivier Aumaître; Camille Francès; Véronique Le Guern; Frédéric Lioté; Amar Smail; Nicolas Limal; Laurent Perard; Hélène Desmurs-Clavel; Du Le Thi Huong Boutin; Bouchra Asli; Jean-Emmanuel Kahn; Jacques Pourrat; Laurent Sailler; Félix Ackermann; Thomas Papo; Karim Sacré; Olivier Fain; Jerome Stirnemann; Patrice Cacoub; Moez Jallouli; Gaelle Leroux; Judith Cohen-Bittan; Marie-Laure Tanguy; Jean-Sébastien Hulot; Philippe Lechat; Lucile Musset; Zahir Amoura; Jean-Charles Piette
Journal:  Ann Rheum Dis       Date:  2012-11-10       Impact factor: 19.103

5.  A physiologically based pharmacokinetic modeling approach to predict disease-drug interactions: suppression of CYP3A by IL-6.

Authors:  K K Machavaram; L M Almond; A Rostami-Hodjegan; I Gardner; M Jamei; S Tay; S Wong; A Joshi; J R Kenny
Journal:  Clin Pharmacol Ther       Date:  2013-04-10       Impact factor: 6.875

6.  Mechanism of action of hydroxychloroquine as an antirheumatic drug.

Authors:  R I Fox
Journal:  Semin Arthritis Rheum       Date:  1993-10       Impact factor: 5.532

7.  Steady-state pharmacokinetics of hydroxychloroquine in rheumatoid arthritis patients.

Authors:  D R Miller; S K Khalil; G A Nygard
Journal:  DICP       Date:  1991-12

8.  Does In Vitro Potency Predict Clinically Efficacious Concentrations?

Authors:  Rasmus Jansson-Löfmark; Stephan Hjorth; Johan Gabrielsson
Journal:  Clin Pharmacol Ther       Date:  2020-05-10       Impact factor: 6.875

9.  Pharmacokinetics of Hydroxychloroquine in Pregnancies with Rheumatic Diseases.

Authors:  Stephen J Balevic; Thomas P Green; Megan E B Clowse; Amanda M Eudy; Laura E Schanberg; Michael Cohen-Wolkowiez
Journal:  Clin Pharmacokinet       Date:  2019-04       Impact factor: 5.577

10.  Observational Study of Hydroxychloroquine in Hospitalized Patients with Covid-19.

Authors:  Joshua Geleris; Yifei Sun; Jonathan Platt; Jason Zucker; Matthew Baldwin; George Hripcsak; Angelena Labella; Daniel K Manson; Christine Kubin; R Graham Barr; Magdalena E Sobieszczyk; Neil W Schluger
Journal:  N Engl J Med       Date:  2020-05-07       Impact factor: 91.245

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  1 in total

Review 1.  Developing New Treatments for COVID-19 through Dual-Action Antiviral/Anti-Inflammatory Small Molecules and Physiologically Based Pharmacokinetic Modeling.

Authors:  Panagiotis Zagaliotis; Anthi Petrou; George A Mystridis; Athina Geronikaki; Ioannis S Vizirianakis; Thomas J Walsh
Journal:  Int J Mol Sci       Date:  2022-07-20       Impact factor: 6.208

  1 in total

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