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.