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Statistical model to evaluate in vivo activities of antimalarial drugs in a Plasmodium cynomolgi-macaque model for Plasmodium vivax malaria.


ABSTRACT: Preclinical animal models informing antimalarial drug development are scarce. We have used asexual erythrocytic Plasmodium cynomolgi infections of rhesus macaques to model Plasmodium 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 nonlinear mixed-effect (NLME) models, estimating treatment effects in three drug studies: G25 (injected) and the 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 antimalarial activity. By applying NLME modeling treatment effects are readily quantified. Such drug development studies are more informative and contribute to reduction and refinement in animal experimentation.

SUBMITTER: Kocken CH 

PROVIDER: S-EPMC2630605 | biostudies-literature | 2009 Feb

REPOSITORIES: biostudies-literature

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Statistical model to evaluate in vivo activities of antimalarial drugs in a Plasmodium cynomolgi-macaque model for Plasmodium vivax malaria.

Kocken Clemens H M CH   Remarque Edmond J EJ   Dubbeld Martin A MA   Wein Sharon S   van der Wel Annemarie A   Verburgh R Joyce RJ   Vial Henri J HJ   Thomas Alan W AW  

Antimicrobial agents and chemotherapy 20081117 2


Preclinical animal models informing antimalarial drug development are scarce. We have used asexual erythrocytic Plasmodium cynomolgi infections of rhesus macaques to model Plasmodium 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 nonlinear mixed-effect (NLME) models, es  ...[more]

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