Model informed dosing of Hydroxycholoroquine in COVID-19 patients:
Learnings from the recent experience, remaining uncertainties and Gaps
Abstract
Aims In the absence of a commonly agreed dosing protocol based on
pharmacokinetic considerations, the dose and treatment duration for
hydroxychloroquine (HCQ) COVID-19 disease currently vary across national
guidelines and clinical study protocols. We have used a model-based
approach to explore the relative impact of alternative dosing regimens
proposed in different dosing protocols for hydroxychloroquine in
COVID-19. Methods We compared different PK exposures using Monte Carlo
simulations based on a previously published population pharmacokinetic
model in patients with rheumatoid arthritis, externally validated using
both independent data in lupus erythematous patients and recent data in
French COVID-19 patients. Clinical efficacy and safety information from
COVID-19 patients treated with HCQ were used to contextualize and assess
the actual clinical value of the model predictions. Results Literature
and observed clinical data confirm the variability in clinical responses
in COVID-19 when treated with the same fixed doses. Confounding factors
were identified that should be taken into account for dose
recommendation. For 80% of patients, doses higher than 800mg day on D1
followed by 600mg daily on following days might not be needed for being
cured. Limited adverse drug reactions have been reported so far for this
dosing regimen, most often confounded by co-medications, comorbidities
or underlying COVID-19 disease effects. Conclusion Our results were
clear indicating the unmet need for characterization of target PK
exposures to inform HCQ dosing optimization in COVID-19. Dosing
optimization for HCQ in COVID-19 is still an unmet need. Efforts in this
sense are a prerequisite for best the benefit/risk balance.