This submission belongs to the 2025 PAGANZ symposium “Pharmacometric approaches in malaria research”
Abstract
The World Health Organization (WHO) estimated a total of 263 million cases of malaria worldwide, leading to 597,000 deaths, in 2023. Children under the age of five accounted for 74% of the total malaria-related deaths. Artemisinin-based combination therapy (ACT) is the recommended first-line therapy for uncomplicated falciparum malaria. The artemisinin-drug has a very potent and rapid parasite killing effect, resulting in a substantial reduction in the parasite biomass during the first three days of treatment. The long-lasting partner-drug is responsible for the elimination of residual parasites, in order to prevent recrudescent malaria infections.
Artemisinin-resistant falciparum malaria was first characterized in southeast Asia, and has spread widely throughout the region in the past 15 years. ACT partner drug resistance has now also emerged on the backbone of artemisinin-resistant infections, resulting in poor efficacy and treatment failures of certain ACTs in southeast Asia. Recently, artemisinin-resistance in P. falciparum emerged independently in several countries in sub-Saharan Africa. Widespread artemisinin-resistance and the development of multi-drug resistant malaria in Africa would have a devastating impact on our ability to treat and eliminate malaria. Furthermore, our research has shown that many of the antimalarial drugs were introduced at the wrong dose, particularly in young children and pregnant women. Improving existing treatments and ensuring optimal dosing of the new drugs is essential for success in the control and elimination of malaria.
The only way to determine accurately the correct dose regimens for novel and currently used antimalarial treatments is to establish a dose-response relationship through pharmacokinetic (PK) and pharmacodynamic (PD) modelling and simulation. Well-designed clinical trials, followed by accurate drug quantification and pharmacometric analysis, has the potential to identify particular groups of patients that are at risk of under- or over-dosing. Developed and validated models can then be used for in-silico dose-optimization and clinical trial design of prospective studies of optimized regimens. This talk will introduce malaria and the pharmacometric approaches used to tackle this important infectious disease.