Abstract: Journal of Pharmacokinetics and Pharmacodynamics https://doi.org/10.1007/s10928-020-09689-x (0123456789().,-volV)(0123456789().,-volV) COMMENTARY Hydroxychloroquine and azithromycin as potential treatments for COVID-19; clinical status impacts the outcome Malek Okour1 • Mahmoud Al-Kofahi2 • Daren Austin3 Received: 27 April 2020 / Accepted: 4 May 2020 Ó Springer Science+Business Media, LLC, part of Springer Nature 2020 In March 2020, hydroxychloroquine (HCQ) and azithromycin were tested as potential treatments for COVID19 pandemic, in an open label non-randomized clinical trial [1]. Data were collected from 36 confirmed COVID-19 patients after receiving no treatment (n = 16) or 200 mg q8h of HCQ with (n = 6) or without (n = 14) azithromycin depending on clinical status. Collected data over six days included one HCQ concentration per patient; respiratory viral loads (PCR assay); azithromycin co-treatment; and clinical status among other variables. Using observed HCQ concentrations and basic pharmacokinetic equations, it was possible to calculate missing concentrations at all days for all patients (Supplementary Fig. S1). Daily viral load, presented as PCR threshold cycle (CT), was converted into a dichotomous variable (positivePCR or negative-PCR). A logistic regression evaluated whether HCQ concentrations, azithromycin co-treatment (yes/no), clinical status (asymptomatic, upper or lower respiratory tract infection [URTI or LRTI]), time (day 0–6), and other covariates (age, sex) were associated with response (positive-PCR outcome). Electronic supplementary material The online version of this article (doi:https://doi.org/10.1007/s10928-020-09689-x) contains supplementary material, which is available to authorized users. & Malek Okour malek.x.okour@gsk.com Mahmoud Al-Kofahi malkofah@umn.edu Daren Austin daren.j.austin@gsk.com 1 GlaxoSmithKline, Collegeville, PA, USA 2 College of Pharmacy, University of Minnesota, Minneapolis, MN, USA 3 GlaxoSmithKline, London, UK Model evaluation and selection was performed based on statistical significance (p-value B 0.05) and diagnostic plots (Supplementary Figs. S2, S3). The final model contained HCQ log-concentrations (ng/ml), azithromycin cotreatment, clinical status, and day as statistically significant covariates (Figs. 1 and S4). Results showed that the odds of positive-PCR decrease by 53% for each unit increase in HCQ log-concentration. Similarly, the odds decrease by 61%, and by 12% for each day increase, and for azithromycin co-treatment, respectively. Whereas the odds of positive-PCR increase by 99.4 folds and 212 folds for having URTI and LRTI versus being asymptomatic subject. Using the model, minimum HCQ concentrations to achieve [ 50% probability of negative-PCR on day 3 were calculated, with or without azithromycin, for the clinical statuses. A minimum HCQ concentration (ng/ml) of 8103 (without azithromycin) and 282 (with azithromycin) are needed in subjects with LRTI. A minimum HCQ concentration (ng/ml) of 2441 (without azithromycin) and 83.9 (with azithromycin) are needed in subjects with URTI. Asymptomatic patients require minimal HCQ concentrations (\ 2 ng/ml) regardless of azithromycin co-treatment. Next, HCQ population PK model [2] was used to simulate dosing regimens needed to achieve targeted HCQ concentrations. Simulations showed that when HCQ is coadministered with azithromycin, a loading dose is critical in rapid achievement of targeted concentrations. The suggested..