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Parasite-host dynamics throughout antimalarial drug development stages complicate the translation of parasite clearance

Burgert, L. and Zaloumis, S. and Dini, S. and Marquart, L. and Cao, P. and Cherkaoui, M. and Gobeau, N. and McCarthy, J. and Simpson, J. A. and Möhrle, J. J. and Penny, M. A.. (2021) Parasite-host dynamics throughout antimalarial drug development stages complicate the translation of parasite clearance. Antimicrobial agents and chemotherapy, 65 (4). e01539-20.

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Abstract

Ensuring continued success against malaria depends on a pipeline of new antimalarials. Antimalarial drug development utilizes pre-clinical murine and experimental human malaria infection studies to evaluate drug efficacy. A sequential approach is typically adapted, with results from each stage, informing the design of the next stage of development. The validity of this approach depends on confidence that results from murine malarial studies predict the outcome of clinical trials in humans. Parasite clearance rates following treatment are key parameters of drug efficacy. To investigate the validity of forward predictions, we developed a suite of mathematical models to capture parasite growth and drug clearance along the drug development pathway and estimated parasite clearance rates. When comparing the three infection experiments, we identified different relationships of parasite clearance with dose, and different maximum parasite clearance rates: in P. berghei-NMRI mouse infections we estimated a maximum parasite clearance rate of 0.2 [1/h]; in P. falciparum-SCID mouse infections 0.05 [1/h]; while in human volunteer infection studies with P. falciparum, we found a maximum parasite clearance rate of 0.12 [1/h] and 0.18 [1/h] after treatment with OZ439 and MMV048, respectively. Sensitivity analysis revealed that host-parasite driven processes account for up to 25% of variance in parasite clearance for medium-high doses of antimalarials. Although there are limitations in translating parasite clearance rates across these experiments, they provide insight into characterising key parameters of drug action and dose response, and assist in decision-making regarding dosage for further drug development.
Faculties and Departments:09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH)
09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Disease Modelling > Disease Modelling and Intervention Dynamics (Penny)
UniBasel Contributors:Burgert, Lydia and Penny, Melissa
Item Type:Article, refereed
Article Subtype:Research Article
ISSN:0066-4804
Note:Publication type according to Uni Basel Research Database: Journal article
Language:English
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Last Modified:19 Dec 2022 12:53
Deposited On:19 Dec 2022 12:53

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