Population Pharmacokinetic and Pharmacodynamic Modeling of Artemisinin Resistance in Southeast Asia

Abstract

Abstract.Orally administered artemisinin-based combination therapy is the first-line treatment against uncomplicated P. falciparum malaria worldwide. However, the increasing prevalence of artemisinin resistance is threatening efforts to treat and eliminate malaria in Southeast Asia. This study aimed to characterize the exposure-response relationship of artesunate in patients with artemisinin sensitive and resistant malaria infections. Patients were recruited in Pailin, Cambodia (n = 39), and Wang Pha, Thailand (n = 40), and received either 2 mg/kg/day of artesunate mono-therapy for 7 consecutive days or 4 mg/kg/day of artesunate monotherapy for 3 consecutive days followed by mefloquine 15 and 10 mg/kg for 2 consecutive days. Plasma concentrations of artesunate and its active metabolite, dihydroartemisinin, and microscopy-based parasite densities were measured and evaluated using nonlinear mixed-effects modeling. All treatments were well tolerated with minor and transient adverse reactions. Patients in Cambodia had substantially slower parasite clearance compared to patients in Thailand. The pharmacokinetic properties of artesunate and dihydroartemisinin were well described by transit-compartment absorption followed by one-compartment disposition models. Parasite density was a significant covariate, and higher parasite densities were associated with increased absorption. Dihydroartemisinin-dependent parasite killing was described by a delayed sigmoidal Emax model, and a mixture function was implemented to differentiate between sensitive and resistant infections. This predicted that 84% and 16% of infections in Cambodia and Thailand, respectively, were artemisinin resistant. The final model was used to develop a simple diagnostic nomogram to identify patients with artemisinin-resistant infections. The nomogram showed > 80% specificity and sensitivity, and outperformed the current practice of day 3 positivity testing.

Population pharmacokinetic and pharmacodynamic properties of artesunate in patients with artemisinin sensitive and resistant infections in Southern Myanmar

“…Data from the current analysis were used as external validation for a recently developed nomogram from a study in Thailand and Cambodia [ 4 , 36 ]. Applying the baseline-adapted nomogram to identify patients with resistant parasite infections, resulted in 90.1% overall sensitivity and 92.1% overall accuracy compared to 55.1 and 75.2%, respectively, using the traditional day-3 positivity test.…”

“…The final population pharmacokinetic model of ARS-DHA was similar to that recently developed on data from a study conducted in Thailand and Cambodia [ 36 ]. The absorption of ARS was described using a transit compartment absorption model followed by a single distribution compartment for both ARS and DHA.…”

“…It was not surprising that body weight had a significant impact on pharmacokinetic parameters, considering that most physiological parameters scale by body weight. In addition, the malaria disease effect on absorption parameters (MTT and F) described in the previous study from Thailand and Cambodia [ 36 ] was implemented a priori. The current study featured plasma concentration data from the first administered dose only and the effect of declining parasite densities (i.e.…”

“…A simple diagnostic method to detect resistant malaria infections was recently developed, based on data from Thailand and Cambodia [ 36 ]. This new diagnostic method demonstrated to be a promising alternative to the current practice of day-3 positivity test as a proxy of having a drug resistant malaria infection [ 36 ]. The developed nomogram used baseline parasite counts to select the time point post-treatment to assess the parasite count.…”

Investigating the Efficacy of Triple Artemisinin-Based Combination Therapies for Treating Plasmodium falciparum Malaria Patients Using Mathematical Modeling

“…Determining dosing regimens that are robust to a wide range of scenarios helps rationalize the logistical and financial challenges of phase 2 and 3 clinical trials. Further improvements in the model can be made to increase its fidelity to the underlying biology, for instance, by consideration of the artemisinins PK (e.g., bioavailability) dependence on parasite density ( 20 ) and different bioavailabilities of MQ at different administered days ( 21 ). The PD model can also be improved by incorporating more complexities underlying drug action, such as the dependence of killing effect on the timespan that parasites are exposed to drugs ( 22 – 25 ), immunity-mediated parasite killing ( 26 , 27 ), and red blood cell (RBC) depletion/production ( 28 , 29 ).…”