📖 ABSTRACT/OVERVIEW
The emergence of partial artemisinin resistance in sub-Saharan Africa threatens the efficacy of artemisinin-based combination therapies, which form the cornerstone of Nigeria's national malaria treatment policy. Pharmacokinetic-pharmacodynamic mathematical modelling integrating clinical patient data with parasite dynamics provides a rigorous quantitative framework for predicting resistance emergence and optimising dosing regimens to delay it. This study developed and validated an integrated PK-PD model of antimalarial drug resistance development incorporating clinical pharmacokinetic data from a cohort of 220 uncomplicated malaria patients treated with artemether-lumefantrine across three hospitals in Kano and Jigawa States. Population PK modelling was performed using NONMEM with non-linear mixed-effects methodology. Parasite dynamics were modelled by a within-host mathematical model incorporating Kelch13 mutation fitness costs, replication rate, and drug-induced killing kinetics. Stochastic simulation was used to predict resistance emergence probabilities under alternative dosing regimens and patient adherence scenarios. Population PK analysis identified significant body weight, age, and CYP3A4 genotype as covariates explaining pharmacokinetic variability in the North West Nigerian study population. The integrated PK-PD model accurately reproduced observed day-3 parasite clearance rates. Simulation predicted a 34% higher resistance emergence risk under current 3-day dosing in patients with sub-therapeutic artemether exposure due to pharmacokinetic variability. Extended 4-day dosing in underweight patients and CYP3A4 ultrarapid metabolisers was predicted to reduce resistance emergence probability by 28%. The study provides original quantitative evidence to inform national artemether-lumefantrine dosing guideline revision for high-risk pharmacokinetic subgroups. Keywords: pharmacokinetic-pharmacodynamic modelling, artemether-lumefantrine, antimalarial resistance, population PK, Nigeria.
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