The repurposing of ivermectin for malaria: a prospective pharmacokinetics-based virtual clinical trials assessment of dosing regimen options

Raj Badhan, Zaril Zakaria, Olusola Olafuyi

Research output: Contribution to journalArticle

Abstract

Ivermectin has demonstrated many successes in the treatment of a range of nematode infections. Considering the increase in malaria resistance attention has turned towards ivermectin as a candidate for repurposing for malaria. This study developed and validated an ivermectin physiologically-based pharmacokinetic model in healthy adults (20-50 years) and paediatric (3-5 years/15-25 kg) subjects and in a representative adult malaria population group (Thailand). Dosing optimisation demonstrated a twice daily for 3- or 5-day regimens would provide a time above the LC50 of more than 7 days for adult and paediatric. Furthermore, to address the occurrence of CYP450-induction often encountered with antiretroviral agents, simulated drug-drug interaction studies with efavirenz highlighted that a 1 mg/kg once daily dose for five days would counteract the increased ivermectin hepatic clearance and enable a time above LC50 of 138.8 hours in adults and 141.2 hours in paediatric subjects. It was also demonstrated that dosage regimen design would require consideration of the age-weight geographical relationship of the subjects, with a dosage regimen for a representative Thailand population group requiring at least a single daily dose for 5 days to maintain ivermectin plasma concentrations and a time above LC50 similar to that in healthy adults.
Original languageEnglish
Pages (from-to)2236-2250
JournalJournal of Pharmaceutical Sciences
Volume107
Issue number8
Early online date5 Apr 2018
DOIs
Publication statusPublished - 1 Aug 2018

Bibliographical note

© 2018, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

Keywords

  • Physiologically-based pharmacokinetics
  • pharmacokinetics
  • drug resistance
  • Onychomycosis
  • n-silico modelling

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