PubMed:32285930 JSONTXT

{"target":"https://pubannotation.org/docs/sourcedb/PubMed/sourceid/32285930","sourcedb":"PubMed","sourceid":"32285930","source_url":"https://www.ncbi.nlm.nih.gov/pubmed/32285930","text":"Optimizing hydroxychloroquine dosing for patients with COVID-19: An integrative modeling approach for effective drug repurposing.\nHydroxychloroquine (HCQ) is a promising candidate for Coronavirus Disease of 2019 (COVID-19) treatment. The optimal dosing of HCQ is unknown. Our goal was to integrate historic and emerging pharmacological and toxicity data to understand safe and efficacious HCQ dosing strategies for COVID-19 treatment. The data sources included were 1) longitudinal clinical, pharmacokinetic, and virologic data from patients with severe acute respiratory syndrome-2 (SARS-CoV-2) infection who received HCQ with or without azithromycin (n=116), 2) in vitro viral replication data and SARS-CoV-2 viral load inhibition by HCQ, 3) a population pharmacokinetic model of HCQ and 4) a model relating chloroquine pharmacokinetics to QTc prolongation. A mechanistic PK/virologic/QTc model for HCQ was developed and externally validated to predict SARS-CoV-2 rate of viral decline and QTc prolongation. SARS-CoV-2 viral decline was associated with HCQ pharmacokinetics (p\u003c0.001). The extrapolated patient EC50 was 4.7 µM, comparable to the reported in vitro EC50 's. HCQ doses \u003e 400 mg BID for ≥5 days were predicted to rapidly decrease viral loads, reduce the proportion of patients with detectable SARS-CoV-2 infection, and shorten treatment courses, compared to lower dose (≤400 mg daily) regimens. However, HCQ doses \u003e600 mg BID were also predicted to prolong QTc intervals. This prolongation may have clinical implications warranting further safety assessment. Due to COVID-19's variable natural history, lower dose HCQ regimens may be indistinguishable from controls. Evaluation of higher HCQ doses is needed to ensure adequate safety and 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