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Updated: Aug 4, 2025

Author Spotlight: Identifying Compensatory Pathways in Malaria Parasites Containing Hypomorphic Allele of Essential Protein Kinases
Published on: November 22, 2024
Integrating Pharmacokinetic-Pharmacodynamic Modeling and Physiologically Based Pharmacokinetic Modeling to Optimize
Devasha Redhi1, Mwila Mulubwa2, Liezl Gibhard2
1South African Medical Research Council Drug Discovery and Development Research Unit, Department of Chemistry and Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.
Abstract:
The translation of a preclinical antimalarial drug development candidate to the clinical phases should be supported by rational human dose selection. A model-informed strategy based on preclinical data, which incorporates pharmacokinetic-pharmacodynamic (PK-PD) properties with physiologically based pharmacokinetic (PBPK) modeling, is proposed to optimally predict an efficacious human dose and dosage regimen for the treatment of Plasmodium falciparum malaria. The viability of this approach was explored using chloroquine, which has an extensive clinical history for malaria treatment. First, the PK-PD parameters and the PK-PD driver of efficacy for chloroquine were determined through a dose fractionation study in the P. falciparum-infected humanized mouse model. A PBPK model for chloroquine was then developed for predicting the drug's PK profiles in a human population, from which the human PK parameters were determined. Lastly, the PK-PD parameters estimated in the P. falciparum-infected mouse model and the human PK parameters derived from the PBPK model were integrated to simulate the human dose-response relationships against P. falciparum, which subsequently allowed the determination of an optimized treatment. The predicted efficacious human dose and dosage regimen for chloroquine were comparable to those recommended clinically for the treatment of uncomplicated, drug-sensitive malaria, which provided supportive evidence for the proposed model-based approach to antimalarial human dose predictions.
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