This Article Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Reprints and Permissions Copyright Information Books from ASM Press MicrobeWorld Google Scholar Articles by Kocken, C. H.M. Articles by Thomas, A. W. PubMed PubMed Citation Articles by Kocken, C. H.M. Articles by Thomas, A. W.

 Previous Article  |  Next Article 

Antimicrob. Agents Chemother. doi:10.1128/AAC.00576-08
Copyright (c) 2008, American Society for Microbiology and/or the Listed Authors/Institutions. All Rights Reserved.

A statistical model to evaluate in vivo activity of anti-malarial drugs in a Plasmodium cynomolgi-macaque model for Plasmodium vivax malaria

Biomedical Primate Research Centre, Dept. of Parasitology, PO Box 3306, 2280 GH Rijswijk, The Netherlands; Dynamique des Interactions Membranaires Normale et Pathologiques, CNRS UMR 5235, cc107, Université Montpellier II, Place Eugene Bataillon, 34095 Montpellier, France

^* To whom correspondence should be addressed. Email: vial{at}univ-montp2.fr. thomas{at}bprc.nl.

	Abstract

Preclinical animal models informing anti-malarial drug development are scarce. We have used asexual erythrocytic Plasmodium cynomolgi infections of rhesus macaques to model P. vivax during preclinical development of compounds targeting parasite phospholipid synthesis. Using this malaria model we accumulated data confirming highly reproducible infection patterns, with self-curing parasite peaks reproducibly preceding recrudescence peaks. We applied non-linear mixed effect (NLME) models, estimating treatment effects in three drug studies: G25 (injected) and bisthiazolium prodrugs TE4gt and TE3 (oral). All compounds fully cured P. cynomolgi-infected macaques, with significant effects on parasitemia height and time of peak. Although all three TE3 doses tested were fully curative, NLME models discriminated dose-dependent differential pharmacological anti-malarial activity. By applying NLME modelling treatment effects are readily quantified. Such drug development studies are more informative and contribute to reduction and refinement in animal experimentation.