Predicting the Disposition of the Antimalarial Drug Artesunate and Its Active Metabolite Dihydroartemisinin Using Physiologically Based Pharmacokinetic Modeling

Abstract

Artemisinin-based combination therapies (ACTs) have proven to be effective in helping to combat the global malaria epidemic. To optimally apply these drugs, information about their tissue-specific disposition is required, and one approach to predict these pharmacokinetic characteristics is physiologically based pharmacokinetic (PBPK) modeling. In this study, a whole-body PBPK model was developed to simulate the time-dependent tissue concentrations of artesunate (AS) and its active metabolite, dihydroartemisinin (DHA). The model was developed for both rats and humans and incorporated drug metabolism of the parent compound and major metabolite. Model calibration was conducted using data from the literature in a Bayesian framework, and model verification was assessed using separate sets of data. Results showed good agreement between model predictions and the validation data, demonstrating the capability of the model in predicting the blood, plasma, and tissue pharmacokinetics of AS and DHA. It is expected that such a tool will be useful in characterizing the disposition of these chemicals and ultimately improve dosing regimens by enabling a quantitative assessment of the tissue-specific drug levels critical in the evaluation of efficacy and toxicity.

Keywords: PBPK; antimalarial agents; artemisinin; malaria; modeling.

FIG 1

Schematic detailing the generic whole-body structure of the PBPK model.

FIG 2

Diagram of the metabolic pathways of AS and DHA listed with the corresponding hypothesized tissue site of metabolism, where VB, MU, L, G, and K represent venous blood, muscle, liver, gut, and kidney tissues, respectively. Biologically active compounds are encircled by a solid line, while biologically inactive compounds are encircled with a dotted line.

FIG 3

Model-predicted pharmacokinetics for unchanged AS (A) and unchanged DHA (B) in rat plasma following i.v. administration of AS at 10 mg/kg. Simulations are coplotted with data taken from the literature (8) for the purposes of model validation. Error bars were digitized from the sourced data set.

FIG 4

Model-predicted pharmacokinetics of TR concentrations in blood (A), plasma (B), brain (C), heart (D), liver (E), and kidney tissues (F) in rats following an intravenous dose of DHA at 3 mg/kg. Simulations are coplotted with data from the literature (13) for the purposes of model validation. Error bars for blood and plasma were digitized from the sourced dataset.

FIG 5

Model-predicted plasma pharmacokinetics of unchanged AS (A) and unchanged DHA (B) in patients with uncomplicated Plasmodium falciparum malaria following i.v. administration of AS at 2.4 mg/kg. Simulations are coplotted with data extracted from the literature (9) for model validation. Error bars were calculated from digitized points extracted from the sourced data set.

FIG 6

Simulations of the plasma pharmacokinetics of DHA in humans following a repeated dosing schedule of i.v. AS at 2 mg/kg (A), 4 mg/kg (B), and 8 mg/kg (C) once every 24 h for the span of 72 h. Model predictions are coplotted with data pulled from the literature (12) for the purposes of model validation. Error bars were calculated from digitized points extracted from the sourced dataset.