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应用生理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处置。

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

机构信息

School of Biomedical Engineering, Colorado State University, Fort Collins, Colorado, USA.

School of Biomedical Engineering, Colorado State University, Fort Collins, Colorado, USA

出版信息

Antimicrob Agents Chemother. 2021 Feb 17;65(3). doi: 10.1128/AAC.02280-20.

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.

摘要

青蒿素类复方疗法(ACTs)已被证明能有效帮助抗击全球疟疾疫情。为了最佳应用这些药物,需要了解有关其组织特异性分布的信息,而预测这些药代动力学特征的一种方法是基于生理学的药代动力学(PBPK)建模。在这项研究中,开发了一个全身 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。该模型针对大鼠和人类进行了开发,并纳入了母体化合物和主要代谢物的药物代谢。使用贝叶斯框架中的文献数据进行模型校准,并使用单独的数据评估模型验证。结果表明,模型预测与验证数据之间具有良好的一致性,表明该模型能够预测 AS 和 DHA 的血液、血浆和组织药代动力学。预计这种工具将有助于描述这些化学物质的处置情况,并通过定量评估评估疗效和毒性的关键组织特异性药物水平,最终改善给药方案。

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