Population Pharmacokinetics and Pharmacodynamics of Artemether and Lumefantrine during Combination Treatment in Children with Uncomplicated Falciparum Malaria in Tanzania

Abstract

The combination of artemether (ARM) and lumefantrine is currently the first-line treatment of uncomplicated falciparum malaria in mainland Tanzania. While the exposure to lumefantrine has been associated with the probability of adequate clinical and parasitological cure, increasing exposure to artemether and the active metabolite dihydroartemisinin (DHA) has been shown to decrease the parasite clearance time. The aim of this analysis was to describe the pharmacokinetics and pharmacodynamics of artemether, dihydroartemisinin, and lumefantrine in African children with uncomplicated malaria. In addition to drug concentrations and parasitemias from 50 Tanzanian children with falciparum malaria, peripheral parasite densities from 11 asymptomatic children were included in the model of the parasite dynamics. The population pharmacokinetics and pharmacodynamics of artemether, dihydroartemisinin, and lumefantrine were modeled in NONMEM. The distribution of artemether was described by a two-compartment model with a rapid absorption and elimination through metabolism to dihydroartemisinin. Dihydroartemisinin concentrations were adequately illustrated by a one-compartment model. The pharmacokinetics of artemether was time dependent, with typical oral clearance increasing from 2.6 liters/h/kg on day 1 to 10 liters/h/kg on day 3. The pharmacokinetics of lumefantrine was sufficiently described by a one-compartment model with an absorption lag time. The typical value of oral clearance was estimated to 77 ml/h/kg. The proposed semimechanistic model of parasite dynamics, while a rough approximation of the complex interplay between malaria parasite and the human host, adequately described the early effect of ARM and DHA concentrations on the parasite density in malaria patients. However, the poor precision in some parameters illustrates the need for further data to support and refine this model.Artemisinin-based combination therapy is generally accepted as treatment of choice for acute uncomplicated Plasmodium falciparum malaria (31). A fixed-dose combination containing artemether (ARM) and lumefantrine (LUM) is currently the first-line treatment of uncomplicated falciparum malaria in mainland Tanzania. The rationale behind combining ARM with LUM is to make use of the disparate pharmacokinetic profiles of the two drugs and thereby improve treatment efficacy and delay development of drug resistance. While ARM and its primary active metabolite dihydroartemisinin (DHA) are rapidly eliminated, LUM is slowly cleared from the body.

Making the Most of Clinical Data: Reviewing the Role of Pharmacokinetic-Pharmacodynamic Models of Anti-malarial Drugs

“…2c, where k pq denotes the transition rate constant for movement from compartment p to q. Variations of this five-compartment model have also been published (10,21), and of note, both papers model the relationship between artemisinin (10) (and artemether/dihydroartemisinin (21)) concentration and killing differently to (17), thereby avoiding the issue just discussed.…”

“…An additional lag time parameter was included to allow patients to be infected at different times prior to treatment. Hietala et al introduced parasites into P 1 four life cycles prior to treatment (21).…”

“…Continuous-time within-host pharmacokinetic-pharmacodynamic models: a Total parasite burden models (5,7,13,15,18,19,20); b Stage-specific models (11). Note, k death was assumed to be determined by the killing action of the anti-malarial and host immunity; c Stage-specific models (10,17,21). Note: Gordi et al had only three compartments for the parasite life cycle and the drug only had action (k drug (t)) against two of these compartments the stage-specific killing effect of drug (defined as function S a (t) above).…”

“…Some of these mechanistic PK-PD models have been fitted formally to patient parasite-time profiles to obtain parameter estimates (10,11,14,16,17,21,22), whereas others have simply selected parameter values that generate parasitetime profiles that accord well with the profiles from clinical studies (5)(6)(7)9,12,13,15,(18)(19)(20). Both of these approaches are dependent on empirical data defining the dynamics of the parasite burden.…”

“…These models can be incorporated in population-level analyses to predict the selection and spread of drug resistance (8). A variety of within-host PK-PD models have been described for falciparum malaria, and there is a wide variation in the number of biological parameters describing the parasite life cycle and PD effect of the anti-malarial treatment (5)(6)(7)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22). The accuracy of these models in predicting the change in parasite burden following treatment depends on many factors.…”