Background Artemisinins are the most effective anti-malarial drugs for uncomplicated and severe Plasmodium falciparum malaria. However, widespread artemisinin resistance in the Greater Mekong Region of Southeast Asia is threatening the possibility to control and eliminate malaria. This work aimed to evaluate the pharmacokinetic and pharmacodynamic properties of artesunate and its active metabolite, dihydroartemisinin, in patients with sensitive and resistant falciparum infections in Southern Myanmar. In addition, a simple nomogram previously developed to identify artemisinin resistant malaria infections was evaluated. Methods Fifty-three (n = 53) patients were recruited and received daily oral artesunate monotherapy (4 mg/kg) for 7 days. Frequent artesunate and dihydroartemisinin plasma concentration measurements and parasite microscopy counts were obtained and evaluated using nonlinear mixed-effects modelling. Results The absorption of artesunate was best characterized by a transit-compartment (n = 3) model, followed by one-compartment disposition models for artesunate and dihydroartemisinin. The drug-dependent parasite killing effect of dihydroartemisinin was described using an Emax function, with a mixture model discriminating between artemisinin sensitive and resistant parasites. Overall, 56% of the studied population was predicted to have resistant malaria infections. Application of the proposed nomogram to identify artemisinin-resistant malaria infections demonstrated an overall sensitivity of 90% compared to 55% with the traditional day-3 positivity test. Conclusion The pharmacokinetic-pharmacodynamic properties of artesunate and dihydroartemisinin were well-characterized with a mixture model to differentiate between drug sensitive and resistant infections in these patients. More than half of all patients recruited in this study had artemisinin-resistant infections. The relatively high sensitivity of the proposed nomogram highlights its potential clinical usefulness.
【저자키워드】 pharmacokinetics, Artemisinin, malaria, resistance, Pharmacodynamics, Parasite clearance, Nonlinear mixed-effects modelling,