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.
The artemisinin-based combination therapy artemether-lumefantrine is commonly used in pregnant malaria patients. However, the effect of pregnancy-related changes on exposure is unclear, and pregnancy has been associated with decreased efficacy in previous studies.
Although traditional approaches to biomarker discovery have elucidated key molecular markers that have improved drug selection (precision medicine), the discovery of biomarkers that inform optimal dose selection (precision dosing) continues to be a challenge in many therapeutic areas. Larger and more diverse study populations are necessary to discover additional biomarkers that provide the resolution needed for a more tailored dose. To generate and accommodate large datasets of drug response phenotypes, time‐ and cost‐efficient strategies are necessary. In particular, a multitude of technological advances that originated for purposes outside of biomedical research (electronic health records, direct‐to‐consumer genetic testing, social media, mobile devices, and machine learning) have made it easier to communicate, connect, and gather information from consumers. Although these technologies have been used with success in the health sciences for an array of purposes, these resources have not been fully capitalized on for precision dosing. This perspective will touch on how these innovations can be used as data sources, data collection tools, and data processing tools for drug‐response phenotypes with a unique focus on advancing biomarker‐driven precision dosing.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.