1 Background

SARS Coronavirus disease 2019 is the most severe pandemic since almost a century with more than 1,000,000 infections and 60000 deaths all over the world within less than 6 months [1], creating an unprecedented urgent need for an effective and safe drug to stop its spread and protect population less skilled to manage the crisis.
Standard drugs and vaccines development approaches are lengthy and expensive: they require years/decades of research and development: they are therefore not the optimal response for the current outbreak in view of the rapid spread of the disease. It is therefore commonly agreed that there is a more pressing refinement need for alternative solutions, including drug repurposing and modelling and simulations.
Drug repurposing consists in this context on using of already marketed drugs or therapeutics under development for other indications based on their potential pharmacological interest or the available non-clinical or clinical data with SARS coronavirus. It can be combined to alternative evidence generation approaches including modelling and simulation to address some important questions such as determining the acceptable dose for the different drugs to be either tested in clinical trials or implemented in compassionate/off-label use during the outbreak.
Hydroxychloroquine (HCQ), a 4-aminoquinolein drug approved and used since decades for treatment of malaria [2], rheumatoid arthritis [3] and cutaneous lupus erythematosus (CLE) [4] is being considered as a potential therapeutic option in COVID-19. Recentin vitro studies demonstrated the antiviral activity of chloroquine (CQ) and HCQ on SARS-CoV-2 (see e.g. [5], [6] and references therein) with results showing higher potency (lower in vitro EC50) for HCQ as compared to CQ, so that lower doses (than in approved indications) could be used in COVID19.
HCQ has been used in clinical trials for COVID-19 treatment with different outcomes/results [7-10], it is currently investigated in a series of additional ongoing/planned clinical trials [11] and is included in some national guidelines for management of COVID-19. However, in the absence of a clear dosing protocol based on drug exposure in plasma/blood and at the site of infection, dosage and duration of treatment currently vary across national and clinical study protocols. Inappropriate dosing regimen can lead to an increase risk of either therapeutic failure or adverse events such as cardiotoxicity (QT prolongation) and retinopathies.
Modelling and simulation have the potential to optimize the dose based on the pharmacokinetics (PK) behavior of the drug, provided that exposure-response is understood and target concentrations are characterized for both efficacy and safety. It is therefore considered timely to explore how the evidence gathered with the clinical use of HCQ could feed the understanding of its PK and PD and inform the dosing in COVID-19 patients. In March 2020, a physiologically based pharmacokinetic (PBPK) model was published by Yao et al to simulate/predict the HCQ concentrations in blood, plasma and lung fluid of Chinese patients [5]. Based on the PBPK model results, the authors recommend an oral loading dose of 400 mg twice daily of hydroxychloroquine sulfate, followed by a maintenance dose of 200 mg given twice daily for 4 days However, no pharmacokinetic data in COVID-19 patients were available to clinically validate the model. A different and much higher dosing regimen (at least 800 mg daily over 10 days) has recently been recommended by Garcia-Cremades et al. based on PK/PD simulation of HCQ effects on SARS COV-2 viral load the one hand, and on QT prolonging effects of chloroquine (CQ) (a similar drug), on the other hand. [12]
The first aim of this work is to assess and compare different dosing regimens using Monte Carlo simulations based on a previously published population pharmacokinetic (popPK) models in patients with rheumatoid arthritis (RA) [3], externally validated using both independent data in patients with cutaneous lupus erythematosus (CLE) [ref : Morita] and recent data in COVID-19 patients [4]. Moreover clinical efficacy and safety information from COVID-19 patients treated with HCQ at Saint-Pierre hospital (Brussels/Belgium) and as included in the recently published studies are used to assess the clinical value of the model predictions.
This work also aims to present and discuss the strength of evidence and the uncertainties for a model informed approach based on the currently available data as well as the current gaps in information for HCQ dose optimization in COVID-19.