key: cord-1000848-3b9u9xpx authors: Cui, Cheng; Zhang, Miao; Yao, Xueting; Tu, Siqi; Hou, Zhe; Jie En, Valerie Sia; Xiang, Xiaoqiang; Lin, Jing; Cai, Ting; Shen, Ning; Song, Chunli; Qiao, Jie; Zhang, Shun; Li, Haiyan; Liu, Dong-yang title: Dose selection of chloroquine phosphate for treatment of COVID-19 based on a physiologically based pharmacokinetic model date: 2020-04-20 journal: Acta Pharm Sin B DOI: 10.1016/j.apsb.2020.04.007 sha: fb6a00358b7d8a197b422a60a06cdb2022e28f31 doc_id: 1000848 cord_uid: 3b9u9xpx 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 finally 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 4–5250 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. 60 61 Coronavirus disease 2019 (COVID-2019) which was declared a global pandemic by World Health Organization (WHO) 1 , has been spreading rapidly across the world, affecting more than 200 countries and claiming more than 700,000 confirmed cases. Approximately 20% of the patients with COVID-19 experienced fatal complications, including tissue failure, septic shock, pulmonary edema, severe pneumonia, acute respiratory distress syndrome (ARDS), and mortality rate among this population was estimated to be 50% 2 . Chloroquine (CQ) was first shown to effectively suppress Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in in vitro assay 3 , and has been subsequently suggested to be efficacious in slowing the deterioration of pneumonia, improving lung imaging results, decreasing viral load, and thus shorten disease duration 4, 5 . CQ phosphate has been used for the treatment of malaria and autoimmune diseases for more than 70 years. According to the prescribing information, the dosage on the first day is not to exceed 1500 mg CQ phosphate, followed by daily maintenance dose of not exceeding 1000 mg CQ phosphate. Although CQ has acceptable safety profile, there are some potential safety concerns with prolonged usage, including QT prolongation, ventricular tachycardia, and retinopathy 6e9 . Studies revealed that CQ also had potential broad-spectrum antiviral activities by increasing endosomal pH being required for virus/cell fusion to accumulate in the cell, and interfering with the glycosylation of cellular receptors of SARS-CoV 10, 11 . It was reported that the angiotensin-converting enzyme 2 (ACE2) receptor, which SARS-CoV-2 employs for the entry into the cell, is highly expressed in lung, gastrointestinal tract, kidney, and heart, etc., which allows SARS-CoV-2 to easily enter these organs 12 . CQ was reported to be highly and slowly accumulated in these organs 13 . Therefore, the distribution of CQ in these organs could be highly relevant to its potential effectiveness against SARS-CoV-2 and adverse events. Following the currently recommended dosing regimen for treatment of malaria or rheumatoid arthritis, it is likely that drug concentration at the site of action is exceedingly higher than the efficacious concentration (EC 50 ) needed to suppress the SARS-CoV-2 in vitro. Meanwhile, higher tissue accumulation of CQ may lead to adverse events. Therefore, dose of CQ should be optimized by considering exposureeefficacy and exposureesafety relationships of CQ. Among the infected patients, there are approximately 30% elderly, 30% with other complications such as hypertension and diabetes, and as well as pregnant women and children (approximately 2%) 2, 14, 15 . Dose selection and optimization in each special population often presents as a challenge for health care professional in the clinical setting. Therefore, there is an urgent need to develop an individualized dosing strategy for each vulnerable population for the safe and effective use of CQ phosphate against SARS-CoV-2. Physiologically-based pharmacokinetic (PBPK) model is an important mathematical tool that incorporates pharmacokinetic properties of drug and physiology, and allows the simulation of pharmacokinetic profiles of drug in plasma as well as other organs and tissues, including the site of action. It can also be used to predict drug PK in different patient populations under different treatment regimens. The initial CQ PBPK model was developed by Certara UK (Simcyp Division) in collaboration with the Bill & Melinda Gates Foundation (Seattle, WA, USA) and Medicines for Malaria Venture, and is freely available within a Global Health PBPK model repository (https://members.simcyp.com/account/ globalHealthRepository/). In addition, there is another report for Zika virus infection during pregnancy, where the PBPK model of chloroquine was established and validated by clinical blood and plasma timeeconcentration profiles 16 . Neither of the above two models reported the model construction or predictions in tissues. As the distribution of CQ in tissues could be highly relevant to its potential effectiveness against SARS-CoV-2 and adverse events, our study aims to develop a PBPK model of CQ to understand the drug exposure in various tissues under different treatment regimens of CQ phosphate, and use the model to predict the drug concentration at the site of action as well as in the tissues of interest where toxicity is of concern, and to subsequently support dose selection in different patient populations infected with SARS-CoV-2. We also reported the pharmacokinetic data of Chinese patients with COVID-19 for the first time to validate the PBPK model. The physicochemical characteristics and pharmacokinetic parameters of chloroquine were collected in Pubmed and Embase database through literature research. Among these parameters, pK a , LogP, and B/P ratio were generated from in vitro experimental data 17 . The fractional contribution of renal elimination and 2 Cheng Cui et al . 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 CYP2C8 and CYP3A4 were derived from public results 18, 19 . The permeability coefficient of chloroquine in human lung adenocarcinoma-3 (Calu-3, parameter relevant for predicting lung drug concentrations) cells was predicted by the QSAR model built in Simcyp software (Version 18, Certara, UK). All clinical pharmacokinetic data of chloroquine were collected from Pubmed and Embase databases. The key words used for the search were "Clinical Pharmacokinetic and Chloroquine". The publications from January 1, 1940 to February 29, 2020 were reviewed. At similar dose levels and comparable patient population, the blood drug concentration of chloroquine is significantly higher or lower than the observed values of similar studies by five-fold or more will be excluded. When pharmacokinetic parameters were not available, the data were obtained from the concentrationetime profile figures in the publications by Plot Digitizer (GetData, Version 2.26), and were applied in Phoenix (Verison 8.6, Certara, UK) to calculate the corresponding main PK parameters (predicted area under curve, AUC and maximum drug concentration, C max ). A first-order absorption model with the input of f a and k a (fraction absorbed and first-order absorption constant, respectively) was used to describe the drug absorption process; a full-PBPK model was used to describe the drug distribution characteristics; the enzyme kinetic data and renal clearance data were used to describe the elimination characteristics; a model of permeability-rate limited mechanism was used to predict the pharmacokinetics of chloroquine in lung 20 , heart, liver, and kidney tissues, and the perfusion-limited model was assumed in other organs/tissues. Intracellular CQ accumulation 21 was characterized by the inclusion of efflux and uptake mechanism in each permeability-rate limited tissue compartments, with passive diffusion clearance (CL pd ) optimized based on the ratio of time varying tissue-to-plasma concentration ratio (K p ) and the ratio of the elimination half-life of chloroquine in tissues to that of plasma (R t ) in rat. The Simcyp Simulator trial design was set to match population demographics (including ethnicity, age, and sex), as well as the dosing and blood collection time points of each literature report. Each simulation includes 10 trials with 10 subjects in each trial. Simulated AUC and C max were compared with clinical observations to assess the predictive performance of the PBPK model. Evaluation criteria are: 1) the observed value is within the 90% confidence interval of the predicted value; 2) the ratio of simulated AUC and C max values are within 2-fold namely, 0.5 ratio 2.0 of the observed values. The use of a tighter boundary (within 25%) was also examined. Two methods were applied to support the use of PBPK model for predicting tissue drug concentrations: 1) the ratio of time dependent tissue-to-plasma concentration ratio (K p ) of CQ in rats 22 and predicted K p in human; and 2) the ratio of the elimination half-life of CQ in tissues to that of plasma (R t ) observed in rats 22 and predicted R t in human by PBPK model. Evaluation criteria are: 1) overlapping of the prediction profiles in human and observation profiles in rats and comparison of the variability of K p in rats and the predicted variability of human K p ; 2) The variation range of the calculated R t value should be within 2-fold, namely, 0.5 R t 2.0. According to the preliminary clinical data from novel COVID-19 patients (n Z 120) 5 , the average time for a nucleic acid swab test to turn negative was 4.4 days under the dosing schedule of 500 mg BID for 7 days. Assuming this dose regimen is effective, we chose to predict the trough concentration in lung tissue on the fifth day (at post-dose 120 h) as an indicator of the minimum efficacious concentration, and the predicted lung tissue AUC 0e120 h as the minimum efficacious exposure level. In addition, safety limits and warning limits were set based on the doseesafety relationship of CQ in the rheumatoid arthritis patients 23 . At the same time, we arbitrarily referred to the mean value of in vitro activity concentration of half maximal effective concentration (EC 50 ) from two studies 3, 24 . According to the approved dosage in product label, the standard antimalarial treatments (Regimen A), the highest dose that demonstrates symptom improvement in the treatment of rheumatoid arthritis (Regimen B) and the apparent effective clinical treatment (Regimen C) were selected as reference regimens. Using PBPK model, we simulated PK profiles of CQ under these reference regimens and overlaid predictions of the above efficacious and safety concentrations. These simulations guided us to propose three dosage regimens individualized for the following patients with COVID-19: acute patients (Regimen D), moderate patients (Regimen E) and special populations (Regimen F). The simulated populations include Chinese healthy volunteers, children (0e17 years old), pregnant women (in second trimester), elderly (65e98 years old) and patients with hepatic and renal impairment. Unless otherwise stated, default models within Sim-CYP population library were used. Ratio of male to female subjects was set to 1:1 for all simulations. An open-label, single-center study (Ethical review approval number: PJ-NBEY-KY-2020-063-01) was conducted to assess the safety, efficacy, and pharmacokinetics of CQ in patients with COVID-19. A total of eight patients weighing more than 60 kg were orally given 500 mg CQ phosphate BID for 7 days (same with Regimen C). Plasma samples on Day 1, Day 3, Day 5, Day 7 and Day 14 were collected prior to dose administration. The plasma concentrations of CQ were determined using a validated high-performance liquid chromatographyetandem mass spectrometry (HPLCeMS/MS) method (see details in Supporting Information). The study was approved by the Ethics Committee of Ningbo Hwamei Hospital, University of Chinese Academy of Sciences (Ningbo, China), and was performed in accordance with the Declaration of Helsinki. All subjects signed the Informed Consent Form (ICF) before the study. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 A PBPK model of CQ incorporating in-depth tissue compartments was developed and validated using CQ PK data from both human (blood and plasma) and rat (plasma and tissues). With this model, we can propose an appropriate dose optimization strategy to treat COVID-19 in acute patients, moderate patients, and special vulnerable populations who may need lower doses. The overall model-informed dosing strategy is shown in Fig. 1 . The final model parameters and sources are shown in Table 1 . A total of 28 articles related to human pharmacokinetics of chloroquine were collected based on the search criteria. There were four articles that were excluded according to the exclusion criteria, and a total of 39 CQ concentrationetime profiles from different populations following administration of CQ phosphate were included (the retrieval method is shown in Supporting Information Fig. S1 . Of these studies, one was used to build the model 25 , and the remaining 38 profiles were used to verify the model. The population characteristics of all drug concentrationetime curves and the design of dosing regimens are shown in Supporting Information Table S1 . The 38 concentrationetime profiles from different clinical studies were compared with the predicted blood or plasma concentrations to verify the predictability of the PBPK model. The results show that 94% (31/33) of the observed AUC values were adequately described by PBPK simulations within 0.5e2.0-fold, and 45% (15/33) of observed AUC values were described by PBPK simulations within 0.8e1.25-fold. Regarding C max , 97% (32/33) observed C max values were described by PBPK simulations within 0.5e2.0-fold, and 18% (6/33) observed C max values were described by PBPK simulations within 0.8e1.25-fold. Verification results are shown in Fig. 2 , which includes data used for model building. Fig. 3 shows that the overall trends of change on the PBPK simulated ratios (K p ) of tissue drug concentrations to plasma drug concentrations over 0e144 h after a single dose of CQ were similar to that observed in rats 22 . The ratio (R t ) of elimination half-life of chloroquine in tissues to elimination half-life in plasma is between 0.5 and 2.0 as listed in Table 2 22 . These evidences helped to increase the confidence in the PBPK simulated CQ exposures in lung, heart, liver and kidney. There are total of six regimens of CQ phosphate investigated in this study (Table 3) . PBPK model was used to simulate regimens AeE in healthy Chinese subjects. Simulation of Regimen F was tested in Chinese healthy volunteers, Geriatric Northern European Caucasians (NEC), cirrhosis (mild, moderate and severe), renal glomerular filtration rate (GFR, 30e60 mL/min/1.73 cm 2 and less than 30 mL/min/1.73 cm 2 ), pregnancy (in second trimester) and pediatric populations default in Simcyp (Version18.0). The basis for dose selection is described as follows. Regimen C has been clinically used as an apparent efficacious dose 5 . The PBPK model predicted trough concentration in the lung tissue under Regimen C on Day 5 is 60.6 mg/mL, and the predicted total exposure for five consecutive days (AUC 0e120 h ) is 3020 h mg/mL. These two values are defined as the minimum effective concentration and the minimum effective exposure, respectively. Based on Frisk-Holmberg et al. 23 , the peak serum concentration with almost no adverse reactions was 400 ng/mL, so it was used as a safety limit. The warning limit was set at a maximum serum concentration of 800 ng/mL, at which adverse effects were observed in approximately 80% subjects. Assuming plasma concentrations are equivalent to serum concentrations, we used PBPK model to simulate plasma and lung tissue concentrations of CQ under six different regimens (Table 3) . Simulated drug concentrationetime curves in plasma, blood, and lung tissue are shown in Fig. 4 . The simulation results show that the predicted population mean C max of the conventional clinical treatment Regimens A and B were below 400 ng/mL, which was consistent with clinical evidence. Regimen C mimics clinical study in which apparent Figure 1 Overall research strategy. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 efficacious of COVID-19 patients was observed 5 . Under this regimen, the model simulated population mean C max of plasma exceeded 400 ng/mL, but was below 800 ng/mL. Regimen D was designed for treating patients with acute COVID-19. Under this regimen, the model-simulated population mean trough concentration in lung tissue could reach 60.6 mg/mL in 3e5 days. Regimen E was designed for treating moderate COVID-19 infected patients, and model simulated mean trough concentration in lung tissue can reach 60.6 mg/mL in 5e7 days. The total exposures (AUC 0e120 h ) for 5 consecutive days of both Regimens D and E (3650 and 3220 h mg/mL, respectively) are greater than 3020 h mg/mL. If we assume Regimen E represents a minimum effective dose (250 mg BID for 5 days, CQ phosphate), the unbound lung tissue concentration would reach the mean Whole organ passive diffusion clearance between intra-and extra-cellular water (L/h) 0.1 Optimized based on K p and R t in rat and V ss Z 137.7 (L/kg) Passive diffusion clearance for heart CL heart (uL/min) 0.1 Uptake clearance for heart CL heart (uL/min) 11000 Efflux clearance for heart CL heart (uL/min) 9 Passive diffusion clearance for heart CL liver (uL/min) 0.1 Uptake clearance for liver CL liver (uL/min) 59000 Efflux clearance for liver CL liver (uL/min) 9 Passive diffusion clearance for heart CL kidney (uL/min) 0.1 Uptake clearance for kidney CL kidney (uL/min) 34000 Efflux clearance for kidney CL kidney (uL/min) 10 Abbreviations: P, octanolewater partition coefficient; PBPK, physiologically-based pharmacokinetic; V ss , volume of distribution at steady-state; K p , partition coefficient; HLM, human liver microsome. a Rodgers and Rowland prediction method was used. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 EC 50 level at 24 h after the first administration of CQ and continued to increase for 10 days. When the simulated concentrationetime profile is extended to 28 days, the results shows that the elimination of the drug in the body was slow and drug accumulation in the tissues was high. For example, in Regimen C, plasma concentration on Day 28 reached 60.4 ng/ mL, whereas predicted lung tissue concentration was 124 mg/mL. High concentrations of CQ were also observed in the heart, liver and kidney (Fig. 5) . Regimen F was a reduced-dose regimen intended for other vulnerable populations with COVID-19. In these populations, exposure may be increased due to reduced drug elimination. Model simulated results show that CQ exposure in the elderly (65e98 years), and patients with hepatic and renal impairment were higher than in normal adults, but the exposure in pregnant women was lower. Despite the differences in exposures, the unbound lung tissue concentration could all reach the mean EC 50 level within 24 h after dosing, as shown in Fig. 6 . The results showing that children of different age groups could achieve similar plasma and blood exposure to adults by adjusting the dose regimen are shown in Fig. 7 . A total of 25 plasma samples were collected and analyzed successfully from eight patients with moderate COVID-19. After multiple oral doses (500 mg BID, CQ phosphate) for 7 days, the mean concentrations were 169. 4 Fig. 8 , and the results show that the predicted mean 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 concentration was within 2-fold of the observed mean concentration, indicating that the pathological state might have little influence on the pharmacokinetic characteristics of drug in plasma. At present, in many clinical studies (ChiCTR2000029939, ChiCTR2000029935, ChiCTR2000029899, etc.) conducted in China, there are no standard recommended dosing regimens of chloroquine phosphate (see Supporting Information Table S2 ). After preliminary clinical research and exploration, National Health Commission of the People's Republic of China proposed that the recommended dose of chloroquine phosphate for the treatment of COVID-19 was 500 mg BID for adults (18e65 years), and continuous administration should not exceed 7 days. In clinical setting, the dose is often being adjusted case-by-case based on the experience of the clinicians, and the selection of optimal dosing regimen would require a well-designed clinical trial with prolonged time period for safety monitoring with large sample size. With the current urgent need of the treatment to help patients with COVID-19, it is not feasible to conduct such conventional clinical trials to optimize dose selection for chloroquine. Therefore, we borrowed the principles of the US FDA's Animal Rule 26 and used PBPK modeling as a tool to combine the available cell-level and animal-level data and describe quantitatively the doseeexposureeresponse relationships of chloroquine. Modeling and simulation approach were employed to understand and translate the kinetics of CQ from the cell level to the body level, and were used to support the design of dosing regimens for different patient populations. PBPK model integrates a series of mathematical equations that describe human physiological and biochemical pathways, drug physicochemical properties and drug mechanistic pharmacokinetic data parameters to systematically study the body's effects on drugs 27 . The model-based selection of dosing regimens of CQ presented in our study was based on the following knowledge: in vitro antiviral potency 3 , historical knowledge of exposureeresponse relationship for safety 23 , apparent efficacy reported recently (e.g., under dosing Regimen C) 5 , and a PBPK model capable of predicting drug concentrations in plasma, blood, and tissues. The novelty of this study includes (i) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 mimicking the physiological characteristics of time-dependent accumulation through an active transport mechanism in the model, which reasonably captured high accumulation of chloroquine in the cells 21 for better prediction of the local PK characteristics of CQ in permeability-limited tissues, and (ii) supporting PBPK prediction of human tissue drug concentrations using animal data. The collection of the lung tissue sample presents a challenge in clinical operation. Considering that the accumulation of CQ in tissues was mainly due to passive diffusion and increased intracellular pH, we assumed that there is minimal inter-species difference. It is thus reasonable to use the rat K p and R t values to support the prediction of tissue concentrations using PBPK models. In the absence of clinical experimental data, this is a powerful alternative to predict the high K p ratios of human according to observed in rats. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 As ACE2 receptor is highly expressed in gastrointestinal tract, kidney, and heart, which allows SARS-CoV-2 virus to easily enter these organs 28 , accumulation of CQ in these organs could be highly relevant to its effectiveness. Meanwhile, significant drug accumulation in these organs may raise safety concerns. Considering it could passively enter tissue cells and was trapped in some organelles in the ionized form 21 , permeability-limited distribution model was applied in these tissues to characterize the timedependent cellular drug accumulation. The simulated results showed that chloroquine could retain in tissues for a long time after dosing stopped. In order to administer right dosing regimen to special populations, model simulations were performed to assess the relationship of drug exposure and safety. The liver metabolic enzyme activity and glomerular filtration rate of these special populations are altered 29e32 . However, as CQ was almost equally eliminated by CYP450-mediated metabolism and renal secretion 13 , dramatic change in either pathway theoretically might not lead to significant increase in CQ exposure, which was consistent with our simulation results. The results suggested that there is no drastic increase in exposure for the elderly, patients with renal or hepatic impaired functions, or pregnant women. In these subjects, dose adjustment can be used according to proposed regimens based on exposure-matching. Considering known safety and emerging information on efficacy, we proposed the use of Regimen F as starting regimen for treating COVID-19 in these special 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 populations. However, in other sensitive populations, such as children with different ages or the patients with both of impaired renal and hepatic functions, CQ exposure may increase dramatically, and CQ should be avoided or used very cautiously if it has to be used. For example, a regimen with a lower loading dose and less frequent dosing may be considered. The developed drug model and population models can be used to predict the exposure and design different dosage regimens. Linking the exposure with clinical effect, the dose of CQ in special population can be properly guided. Multiple assumptions were made in this study and several limitations warrant additional research to further enhance the predictability of the model. First, we assumed same underlying physiology between healthy subjects, patients with acute or moderate COVID-19 and virtual populations that better represent COVID-19 disease related pathophysiology may be needed. Sensitivity analysis was performed on the newly established model, such as the change of free fraction of CQ in lung tissue, pulmonary blood flow, pulmonary pH, and intrinsic clearance rate (CL int ) of lung tissue. The results showed that these physiological and pathological changes had little impact on the predictions. And this assumption was preliminarily validated by the clinical pharmacokinetic data from eight patients with COVID-19, and need further confirmation. Second, simulations were conducted in various virtual populations that have been developed based on Caucasian data. The comparability of CQ pharmacokinetics in vulnerable populations may require further validation. Third, we focused on liver, lung, heart, and kidney when parameterizing permeability-limited drug distribution. Future research is needed to characterize drug distribution to other organs such as the eyes. CQ is known to cause retinopathy, understanding tissue distribution in this organ is important. In addition, several assumptions were made when parameterizing permeability-limited CQ distribution, including the use of apparent active transport mechanism to capture time-dependent drug accumulation, and the use of animal data to support prediction of tissue concentrations in humans. We proposed a model-informed dose selection strategy under emergency situation. First, we established and validated a novel PBPK model to predict concentrations in lung, heart, liver and kidney using permeability-limited model by mimicking the physiological characteristics of time-dependent accumulation through an active transport mechanism in the model. Second, we selected the simulated lung trough concentration on Day 5 and AUC 0e120 h in patients with a dose of 500 mg BID (CQ phosphate) as effective target and selected 800 ng/mL of plasma trough concentration as safety limit according to the clinical exposureeresponse relationship. Third, we optimized different dosing regimens for different type of patients using PBPK model. Fourth, pharmacokinetic data from Chinese patients with moderate COVID-19 was firstly reported and employed to validate the model. We hope our PBPK model could be applied for optimizing the use of CQ for treatment of COVID-19, and our dosing optimizing strategy could help accelerate safe and effective use of other anti-COVID-19 drugs . 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 World Health Organization declares global emergency: a review of the 2019 novel coronavirus (COVID-19) Novel Coronavirus Pneumonia Emergency Response Epidemiology Team. The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) in China Remdesivir and chloroquine effectively inhibit the recently emerged novel coronavirus (2019-nCoV) in vitro Chloroquine for the 2019 novel coronavirus SARS-CoV-2 Breakthrough Yang X. 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Focus on recent advancements The outbreak of COVID-19: an overview Novel corona virus disease (COVID-19) in pregnancy: what clinical recommendations to follow Dose optimization of chloroquine by pharmacokinetic modeling during pregnancy for the treatment of Zika virus infection An in vitro toolbox to accelerate anti-malarial drug discovery and development In vitro metabolism of chloroquine: identification of CYP2C8, CYP3A4, and CYP2D6 as the main isoforms catalyzing N-desethylchloroquine formation Cytochrome P450 2C8 and CYP3A4/5 are involved in chloroquine metabolism in human liver microsomes Development of a multicompartment permeabilitylimited lung PBPK model and its application in predicting pulmonary pharmacokinetics of antituberculosis drugs Therapy and pharmacological properties of hydroxychloroquine and chloroquine in treatment of systemic lupus erythematosus, rheumatoid arthritis and related diseases Kinetics of the distribution and elimination of chloroquine in the rat Chloroquine serum concentration and side effects: evidence for dose-dependent kinetics In vitro antiviral activity and projection of optimized dosing design of hydroxychloroquine for the treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Disposition of chloroquine in man after single intravenous and oral doses The animal rule: the role of clinical pharmacology in determining an effective dose in humans Physiologically based pharmacokinetic modeling: from regulatory science to regulatory policy SARS-CoV-2 cell entry depends on ACE2 and TMPRSS2 and is blocked by a clinically proven protease inhibitor Physiological changes in pregnancy Altered drug metabolism during pregnancy: hormonal regulation of drug-metabolizing enzymes Hepatic cytochrome P-4503A (CYP3A) activity in the elderly The ageing kidney Protein binding of chloroquine enantiomers and desethylchloroquine Characterization of chloroquine plasma protein binding in man Pharmacokinetics of chloroquine in Thais: plasma and red-cell concentrations following an intravenous infusion to healthy subjects and patients with Plasmodium vivax malaria Enantioselective analysis of chloroquine and desethylchloroquine after oral administration of racemic chloroquine The disposition of chloroquine in healthy Nigerians after single intravenous and oral doses We thank Drs Eleanor Howgate and Maurice Dickins for the development of the original chloroquine PBPK base model, and thank Lisa Almond, Alice Ke and Mian Zhang for providing the initial model and constructive discussions. We thank Dr Ping Zhao, Dr Gaohua Lu and Dr Hoi-Kei Lon for the scientific suggestion and proofreading. This work was supported by the "13th The authors declare no conflicts of interest. Supplementary data to this article can be found online at https:// doi.org/10.1016/j.apsb.2020.04.007.