Physiologically‐Based Pharmacokinetic Modeling for Optimal Dosage Prediction of Quinine Coadministered With Ritonavir‐Boosted Lopinavir

Saeheng, Teerachat; Na‐Bangchang, Kesara; Siccardi, Marco; Rajoli, Rajith K. R.; Karbwang, Juntra

doi:10.1002/cpt.1721

Cited by 24 publications

(28 citation statements)

References 46 publications

(62 reference statements)

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“…Systemic exposures of quinine and its metabolite 3‐hydroxyquinine are decreased when coadministered with nevirapine 182 and ritonavir‐boosted lopinavir in healthy subjects 183 . Recently, PBPK modeling has been applied to predict optimal dosage regimens of quinine when coadministered with lopinavir/ritonavir in malaria and HIV coinfected patients with renal failure, hepatic insufficiency, or CYP3A4 polymorphism 184 …”

Section: Antimalarial Dose Optimization In Special Conditionsmentioning

confidence: 99%

The Role of Clinical Pharmacology in Chemotherapy of Multidrug‐Resistant Plasmodium falciparum

Karbwang

Na‐Bangchang

2020

The Journal of Clinical Pharma

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Malaria remains one of the major global public health problems due to the emergence and spread of multidrug‐resistant Plasmodium falciparum. In recent years, clinical pharmacology has significantly contributed to the optimal dosing regimens of antimalarial drugs. The application of pharmacometric modeling and simulation has assisted in the accurate characterization of pharmacokinetic‐pharmacodynamic relationships and the optimization of the dosage regimens of existing antimalarial drugs, including new antimalarial candidates for multidrug‐resistant P falciparum in different populations.

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Section: Antimalarial Dose Optimization In Special Conditionsmentioning

confidence: 99%

The Role of Clinical Pharmacology in Chemotherapy of Multidrug‐Resistant Plasmodium falciparum

Karbwang

Na‐Bangchang

2020

The Journal of Clinical Pharma

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“…were constructed based on the previously published information [11,12] using Simbiology ® (version 5.8.2), the product of MATLAB ® (version 2019a) (MathWorks, Natick, MA, USA).…”

Section: Model Constructionmentioning

confidence: 99%

“…The physicochemical and biochemical properties (model parameters) of each drug, including human physiological parameters, were obtained from the published articles are available in the supplementary material of this article [9,11,[13][14][15][16][17][18][19][20][21][22][23][24][25] (Additional file 1).…”

Section: Model Constructionmentioning

confidence: 99%

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Physiologically-based Pharmacokinetic (PBPK) Modeling for Prediction of the Optimal Dose Regimens of Quinine and Phenobarbital Co-administration in Adult Patients with Cerebral Malaria and Seizures

Saeheng

Karbwang

Rajoli

et al. 2020

Preprint

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Background: Cerebral malaria is a fatal disease. Patients with cerebral malaria are at risk of seizure development, therefore, the co-administration of antimalarial and antiepileptic drugs are needed. Quinine and phenobarbital are standard drugs for the treatment of cerebral malaria with seizures. However, there is no information on the optimal dosage regimens of both drugs when used concomitantly.T he study applied physiologically-based pharmacokinetic (PBPK) modeling for prediction of the optimal dose regimens of quinine and phenobarbital when co-administered in patients with cerebral malaria and concurrent seizures who carry wild type and polymorphic cytochrome P450 (CYP450) 2C9/2C19. Methods: The whole-body PBPK models for quinine and phenobarbital were constructed based on the previously published information using Simbiology®. One hundred virtual population were simulated. Four published articles were used for model verification. Sensitivity analysis was carried out to determine the effect of the changes in model parameters on AUC0–72h. Simulation of optimal dose regimens was based on standard drug-drug interactions (DDIs), and actual clinical use study approaches. Results: Dose adjustment of the standard regimen of phenobarbital is not required when co-administered with quinine. The proposed optimal dose regimen for quinine, when co-administered with phenobarbital for patients with a single or continuous seizure in all malaria-endemic areas regardless of CYP2C9/CYP2C19 genotypes, is a loading dose of 1,500 mg IV infusion over 8 hours, followed by 1,200 mg infusion over 8 hours given three times daily, or multiple doses of 1,400 mg IV infusion over 8 hours, given three times daily. In areas with quinine resistance, the dose regimen should be increased as a loading dose of 2,000 mg IV infusion over 8 hours, followed by 1,750 mg infusion over 8 hours given three times daily.Conclusion: The developed PBPK models are reliable, and successfully predicted the optimal doses regimens of quinine-phenobarbital co-administration with no requirement of CYP2C9/CYP2C19 genotyping.

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“…The whole PBPK models for LPV/r, and chloroquine were constructed based on the previously published articles (Saeheng, Na-Bangchang, Siccardi, Rajoli, & Karbwang, 2019;Siccardi, 2015) using Simbiology® (version 5.8.2), the product of MATLAB® (version 2019a) (MathWorks, Natick, MA, USA). The physicochemical, and biochemical properties (model parameters) of each drug were collected from the published articles (Table S1) (Ernest, Hall, & Jones, 2005;Koudriakova et al, 1998;Olafuyi & Badhan, 2019;Patel, Mandava, Gokulgandhi, Pal, & Mitra, 2014;Saeheng et al, 2019;Wagner et al, 2017;Xu, Vela, Shi, Marroum, & Gao, 2017;Zhang et al, 2012). Model assumptions included blood-flow limited model, immediate drug dissolution, absence of drug absorption in the stomach and large intestine, and absence of enterohepatic recirculation.…”

Section: Model Constructionmentioning

confidence: 99%

Dosage prediction of chloroquine and ritonavir-boosted lopinavir for COVID-19 treatment: A physiologically-based pharmacokinetic (PBPK) modelling

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Background and Purpose: The 2019 novel coronavirus (COVID-19) has been spread out since December 2019 from China to 29 countries. No effective treatment is currently available, although the combination regimen of the antiretroviral drugs-lopinavir/ritonavir (LPV/r), with other antiviral drugs have been using, but the evidences are limited. A recent in vitro study showed that chloroquine could inhibit COVID-19 to cells, and enhance antiviral efficacy. This study aimed to predict the optimal dose regimens of LPV/r, and chloroquine in combination as a potential treatment of COVID-19 infection, using the physiologically-based pharmacokinetic (PBPK) modelling. Experimental approach: The whole PBPK models were constructed. The predicted plasma drug concentrations were compared with the published clinical data. The validated models were used to predict optimal dosage regimens of LPV/r, and chloroquine co-administration. The optimal dose regimen was determined based on the efficacy, and toxicity reported in the published data. Key Results: The average errors of the predicted values were within 30% of the observed data. The proposed optimal dosage regimen is the once-daily dose of 800/200 mg LPV/r co-administered with chloroquine at a loading dose of 1,000 mg, followed by twice-daily dose of 500 mg for 8 doses on the second day, and the twice-daily dose of 400 mg for 18 doses. Conclusion and Implications: PBPK modelling successfully predicted pharmacokinetic profiles within an acceptable range of errors. The study provides a focus for clinical studies to confirm the efficacy of the proposed dosage regimen as a novel treatment for COVID-19 infection.

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Physiologically‐Based Pharmacokinetic Modeling for Optimal Dosage Prediction of Quinine Coadministered With Ritonavir‐Boosted Lopinavir

Cited by 24 publications

References 46 publications

The Role of Clinical Pharmacology in Chemotherapy of Multidrug‐Resistant Plasmodium falciparum

The Role of Clinical Pharmacology in Chemotherapy of Multidrug‐Resistant Plasmodium falciparum

Physiologically-based Pharmacokinetic (PBPK) Modeling for Prediction of the Optimal Dose Regimens of Quinine and Phenobarbital Co-administration in Adult Patients with Cerebral Malaria and Seizures

Dosage prediction of chloroquine and ritonavir-boosted lopinavir for COVID-19 treatment: A physiologically-based pharmacokinetic (PBPK) modelling

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