A multistate tuberculosis pharmacometric model: a framework for studying anti-tubercular drug effects in vitro
A multistate tuberculosis pharmacometric model: a framework for studying anti-tubercular drug effects in vitro
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DOI：
10.1093/jac/dkv416
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发表时间：
2016-04-01
影响因子：
5.2
通讯作者：
Simonsson, Ulrika S. H.
中科院分区：
文献类型：
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作者：
Clewe, Oskar;Aulin, Linda;Simonsson, Ulrika S. H.
结核分枝杆菌在体外可以以不同的状态存在，表现为快速增殖、缓慢增殖和不增殖。描述结核分枝杆菌的自然生长特征可以为准确描述药物对不同细菌状态的影响提供一个框架。本研究中使用的结核分枝杆菌H37Rv的自然生长数据包括基于体外低氧系统的数据定义的存活率，以CFU-时间为基础。自然生长模型的外部验证是使用代表细菌将放射性标记的蛋氨酸掺入蛋白质的速率的数据进行的。用对数期(0.25-16 mg/L)和静止期(0.5-mg/L)的利福平时间-杀灭曲线，通过评估不同的线性和非线性暴露-反应关系来评估模型的药物效应描述能力。最终的药物计量学模型由一个代表快、慢和非繁殖细菌的三室微分方程组组成。模型预测与外部数据有很好的相关性(R(2)aEuroS=aEuroS0.98)。通过包括药物对不同细菌状态的影响，分别和同时描述了利福平对对数相和固定相培养的影响。在对数相和固定相系统中，在对数相和固定相系统中，对数(10)菌落单位在14天后和在0.5 mg/L浓度下的预测减少率分别为2.2和0.8。该模型预测了有和没有药物作用的不同细菌状态下细菌数量的变化，因此可以作为体外抗结核药物作用的研究框架。
Mycobacterium tuberculosis can exist in different states in vitro, which can be denoted as fast multiplying, slow multiplying and non-multiplying. Characterizing the natural growth of M. tuberculosis could provide a framework for accurate characterization of drug effects on the different bacterial states.The natural growth data of M. tuberculosis H37Rv used in this study consisted of viability defined as cfu versus time based on data from an in vitro hypoxia system. External validation of the natural growth model was conducted using data representing the rate of incorporation of radiolabelled methionine into proteins by the bacteria. Rifampicin time-kill curves from log-phase (0.25-16 mg/L) and stationary-phase (0.5-64 mg/L) cultures were used to assess the model's ability to describe drug effects by evaluating different linear and non-linear exposure-response relationships.The final pharmacometric model consisted of a three-compartment differential equation system representing fast-, slow- and non-multiplying bacteria. Model predictions correlated well with the external data (R(2)aEuroS=aEuroS0.98). The rifampicin effects on log-phase and stationary-phase cultures were separately and simultaneously described by including the drug effect on the different bacterial states. The predicted reduction in log(10) cfu after 14 days and at 0.5 mg/L was 2.2 and 0.8 in the log-phase and stationary-phase systems, respectively.The model provides predictions of the change in bacterial numbers for the different bacterial states with and without drug effect and could thus be used as a framework for studying anti-tubercular drug effects in vitro.