Dose Optimization of Chloroquine by Pharmacokinetic Modeling During Pregnancy for the Treatment of Zika Virus Infection

Olusola Olafuyi, Raj K.s. Badhan

Research output: Contribution to journalArticlepeer-review

Abstract

The insidious nature of Zika virus (ZIKV) infections can have a devastating consequence for foetal development. Recent reports have highlighted that chloroquine (CQ) is capable of inhibiting ZIKV endocytosis in brain cells. We applied pharmacokinetic modelling to develop a predictive model for CQ exposure to identify an optimal maternal/foetal dosing regimen to prevent ZIKV endocytosis in brain cells. Model validation utilised 13 non-pregnancy and 3 pregnancy clinical studies and a therapeutic CQ plasma window of 0.3-2 μM was derived. Dosing regimens used in rheumatoid arthritis, systemic lupus erythematosus and malaria were assessed for their ability to target this window. Dosing regimen identified that weekly doses used in malaria were not sufficient to reach the lower therapeutic window, however daily doses of 150 mg achieved this therapeutic window. The impact of gestational age was further assessed and culminated in a final proposed regimen of 600 mg on day 1, 300 mg on day 2 and 3 and 150 mg thereafter until the end of trimester 2, which resulted in maintaining 65 % and 94 % of subjects with a trough plasma concentration above the lower therapeutic window on day 6 and at term, respectively.
Original languageEnglish
Pages (from-to)P661-673
JournalJournal of Pharmaceutical Sciences
Volume108
Issue number1
Early online date3 Nov 2018
DOIs
Publication statusPublished - 1 Jan 2019

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
  • Zika
  • malaria
  • pregnancy

Fingerprint

Dive into the research topics of 'Dose Optimization of Chloroquine by Pharmacokinetic Modeling During Pregnancy for the Treatment of Zika Virus Infection'. Together they form a unique fingerprint.

Cite this