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Dose selection of chloroquine phosphate for treatment of COVID-19 based on a physiologically based pharmacokinetic model.

ABSTRACT: Chloroquine (CQ) phosphate has been suggested to be clinically effective in the treatment of coronavirus disease 2019 (COVID-19). To develop a physiologically-based pharmacokinetic (PBPK) model for predicting tissue distribution of CQ and apply it to optimize dosage regimens, a PBPK model, with parameterization of drug distribution extrapolated from animal data, was developed to predict human tissue distribution of CQ. The physiological characteristics of time-dependent accumulation was mimicked through an active transport mechanism. Several dosing regimens were proposed based on PBPK simulation combined with known clinical exposure-response relationships. The model was also validated by clinical data from Chinese patients with COVID-19. The novel PBPK model allows in-depth description of the pharmacokinetics of CQ in several key organs (lung, heart, liver, and kidney), and was applied to design dosing strategies in patients with acute COVID-19 (Day 1: 750 mg BID, Days 2-5: 500 mg BID, CQ phosphate), patients with moderate COVID-19 (Day 1: 750 mg and 500 mg, Days 2-3: 500 mg BID, Days 4-5: 250 mg BID, CQ phosphate), and other vulnerable populations (e.g., renal and hepatic impairment and elderly patients, Days 1-5: 250 mg BID, CQ phosphate). A PBPK model of CQ was successfully developed to optimize dosage regimens for patients with COVID-19.

SUBMITTER: Cui C

PROVIDER: S-EPMC7252145 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Dose selection of chloroquine phosphate for treatment of COVID-19 based on a physiologically based pharmacokinetic model.

Cui Cheng C Zhang Miao M Yao Xueting X Tu Siqi S Hou Zhe Z Jie En Valerie Sia VS Xiang Xiaoqiang X Lin Jing J Cai Ting T Shen Ning N Song Chunli C Qiao Jie J Zhang Shun S Li Haiyan H Liu Dongyang D

Acta pharmaceutica Sinica. B 20200420 7

Chloroquine (CQ) phosphate has been suggested to be clinically effective in the treatment of coronavirus disease 2019 (COVID-19). To develop a physiologically-based pharmacokinetic (PBPK) model for predicting tissue distribution of CQ and apply it to optimize dosage regimens, a PBPK model, with parameterization of drug distribution extrapolated from animal data, was developed to predict human tissue distribution of CQ. The physiological characteristics of time-dependent accumulation was mimicked ...[more]

PMID: 32834950

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Project description:Patients with coronavirus disease 2019 (COVID-19) with cardiovascular diseases who are at higher risk of progressing to critical illness should be treated with nirmatrelvir/ritonavir (Paxlovid). Ritonavir, the booster in nirmatrelvir/ritonavir, modulates multiple drug metabolizing enzymes and transporters, complicating its use in real-world clinics. We aimed to apply physiologically-based pharmacokinetic (PBPK) modeling to simulate the complex drug-drug interactions (DDIs) of ritonavir with two anticoagulants, rivaroxaban and racemic warfarin, to address this important clinical conundrum. Simulations were implemented within Simcyp Simulator. Compound and population models were adopted from Simcyp and our previous studies. Upon verification and validation of the PBPK model of ritonavir, prospective DDI simulations with the anticoagulants were performed in both the general population (20-65 years) and geriatric subjects (65-85 years) with or without moderate renal impairment. Elevated rivaroxaban concentrations were simulated with nirmatrelvir/ritonavir treatment, where the impact was more profound among geriatric subjects with renal impairment. The overexposure of rivaroxaban was restored to normal range on day 4 post-discontinuation of nirmatrelvir/ritonavir, corroborating with the recovery of enzyme activity. A lower 10 mg daily dose of rivaroxaban could effectively maintain acceptable systemic exposure of rivaroxaban during nirmatrelvir/ritonavir treatment. Treatment of ritonavir marginally declined simulated S-warfarin concentrations, but substantially elevated that of R-warfarin, resulting in a decrease in the international normalized ratio (INR). As INR only recovered 2 weeks post-nirmatrelvir/ritonavir treatment, a longer surveillance INR for warfarin becomes important. Our PBPK-guided simulations evaluated clinically important yet untested DDIs and supports clinical studies to ensure proper anticoagulation management of patients with COVID-19 with chronic coagulative abnormalities when initiating nirmatrelvir/ritonavir therapy.

Project description:BACKGROUND: Propofol is widely used for both short-term anesthesia and long-term sedation. It has unusual pharmacokinetics because of its high lipid solubility. The standard approach to describing the pharmacokinetics is by a multi-compartmental model. This paper presents the first detailed human physiologically based pharmacokinetic (PBPK) model for propofol. METHODS: PKQuest, a freely distributed software routine http://www.pkquest.com, was used for all the calculations. The "standard human" PBPK parameters developed in previous applications is used. It is assumed that the blood and tissue binding is determined by simple partition into the tissue lipid, which is characterized by two previously determined set of parameters: 1) the value of the propofol oil/water partition coefficient; 2) the lipid fraction in the blood and tissues. The model was fit to the individual experimental data of Schnider et. al., Anesthesiology, 1998; 88:1170 in which an initial bolus dose was followed 60 minutes later by a one hour constant infusion. RESULTS: The PBPK model provides a good description of the experimental data over a large range of input dosage, subject age and fat fraction. Only one adjustable parameter (the liver clearance) is required to describe the constant infusion phase for each individual subject. In order to fit the bolus injection phase, for 10 or the 24 subjects it was necessary to assume that a fraction of the bolus dose was sequestered and then slowly released from the lungs (characterized by two additional parameters). The average weighted residual error (WRE) of the PBPK model fit to the both the bolus and infusion phases was 15%; similar to the WRE for just the constant infusion phase obtained by Schnider et. al. using a 6-parameter NONMEM compartmental model. CONCLUSION: A PBPK model using standard human parameters and a simple description of tissue binding provides a good description of human propofol kinetics. The major advantage of a PBPK model is that it can be used to predict the changes in kinetics produced by variations in physiological parameters. As one example, the model simulation of the changes in pharmacokinetics for morbidly obese subjects is discussed.

Project description:Abstract Background ADG20 is a fully human IgG1 monoclonal antibody engineered to have potent and broad neutralization against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other SARS-like CoVs with pandemic potential and an extended half-life. ADG20 is administered intramuscularly (IM). A QSP/PBPK model was constructed to support dose selection for a Phase 2/3 trial of ambulatory patients with mild to moderate COVID-19 (STAMP: NCT04805671). Methods A QSP/PBPK model was used to simulate receptor occupancy (RO) and drug exposure in the upper airway (nasopharyngeal/oropharyngeal epithelial lining fluid [ELF] compartment). RO was linked to an existing viral dynamic model to enable the prediction of the natural time course of viral load and the effect of ADG20 on viral clearance and infectivity rate. RO was calculated using: 1) in vitro ADG20–SARS-CoV-2 binding kinetics (association rate constant (kon) of 1.52E+06 M-1•s1 and dissociation rate constant (koff) of 2.81E-04 s-1 from a Biacore assay; 2) time course of ADG20 concentrations in ELF; and 3) time course of viral load following ADG20 administration. Molar SARS-CoV-2 viral binding site capacity was calculated assuming 40 spike proteins per virion, 3 binding sites per spike, and an initial viral load of log 107 copies/mL for all patients. The QSP/PBPK model and a 2018 CDC reference body weight distribution (45–150 kg) were used to simulate 1000 concentration-time profiles for a range of candidate ADG20 regimens. ADG20 regimens were evaluated against 2 criteria: 1) ability to attain near complete ( >90%), and durable (28-day) SARS-CoV-2 RO in the ELF; and 2) ability to maintain ELF ADG20 concentrations relative to a concentration (0.5 mg/L) associated with 100% viral growth suppression in an in vitro post-infection assay. Results A single 300 mg IM ADG20 dose met the dose selection criteria in terms of RO (Figure A) and viral growth suppression (Figure B). Conclusion These data support the evaluation of an ADG20 300 mg IM dose for the treatment of mild to moderate COVID-19. ADG20 is forecasted to attain near complete ( >90%) SARS-CoV-2 RO in the ELF and maintain ELF ADG20 concentrations above that associated with 100% viral growth suppression in vitro. Figure. QSP/PBPK model forecast of ADG20 300 mg IM in adults (A) Predicted RO expressed as percent occupancy with the dotted line representing the threshold for 90% RO. (B) Predicted median concentration of ADG20 relative to a concentration (0.5 mg/L) associated with 100% viral growth suppression as indicated by the dotted line; the shaded area represents the 90% prediction interval. Disclosures Evan D. Tarbell, PhD, Adagio Therapeutics, Inc. (Independent Contractor) Scott A. Van Wart, PhD, Adagio Therapeutics, Inc. (Independent Contractor) Laura M. Walker, PhD, Adagio Therapeutics, Inc. (Other Financial or Material Support, Laura M. Walker is an inventor on a patent application submitted by Adagio Therapeutics, Inc., describing the engineered SARS-CoV-2 antibody.) Andrew Santulli, PhD, Adagio Therapeutics, Inc. (Independent Contractor) Lynn E. Connolly, MD, PhD, Adagio Therapeutics, Inc. (Employee) Donald E Mager, PharmD, PhD, Adagio Therapeutics, Inc. (Independent Contractor) Paul G. Ambrose, PharmD, Adagio Therapeutics, Inc. (Employee)

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Dose selection of chloroquine phosphate for treatment of COVID-19 based on a physiologically based pharmacokinetic model.

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Dose selection of chloroquine phosphate for treatment of COVID-19 based on a physiologically based pharmacokinetic model.

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