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.

中文翻译：

---

使用基于生理学的药代动力学模型预测抗疟药物青蒿琥酯及其活性代谢物双氢青蒿素的分布

事实证明，基于青蒿素的联合疗法 (ACTs) 可有效帮助对抗全球疟疾流行。为了最佳地应用这些药物，需要有关其组织特异性处置的信息，预测这些药代动力学特征的一种方法是基于生理的药代动力学 (PBPK) 建模。在这项研究中，开发了全身 PBPK 模型来模拟青蒿琥酯 (AS) 及其活性代谢物双氢青蒿素 (DHA) 的时间依赖性组织浓度。该模型是为大鼠和人类开发的，并结合了母体化合物和主要代谢物的药物代谢。模型校准使用贝叶斯框架中的文献数据进行，模型验证使用单独的数据集进行评估。结果表明模型预测与验证数据之间具有良好的一致性，证明了模型在预测 AS 和 DHA 的血液、血浆和组织药代动力学方面的能力。预计这种工具将有助于表征这些化学品的处置，并最终通过定量评估对疗效和毒性评估至关重要的组织特异性药物水平来改进给药方案。