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The Pharmaco – Population and Evolutionary Dynamics of Multi-drug Therapy: Experiments with S. aureus and E. coli and Computer Simulations

机译:多药疗法的药理学种群和进化动力学:金黄色葡萄球菌和大肠杆菌的实验以及计算机模拟

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摘要

There are both pharmacodynamic and evolutionary reasons to use multiple rather than single antibiotics to treat bacterial infections; in combination antibiotics can be more effective in killing target bacteria as well as in preventing the emergence of resistance. Nevertheless, with few exceptions like tuberculosis, combination therapy is rarely used for bacterial infections. One reason for this is a relative dearth of the pharmaco-, population- and evolutionary dynamic information needed for the rational design of multi-drug treatment protocols. Here, we use in vitro pharmacodynamic experiments, mathematical models and computer simulations to explore the relative efficacies of different two-drug regimens in clearing bacterial infections and the conditions under which multi-drug therapy will prevent the ascent of resistance. We estimate the parameters and explore the fit of Hill functions to compare the pharmacodynamics of antibiotics of four different classes individually and in pairs during cidal experiments with pathogenic strains of Staphylococcus aureus and Escherichia coli. We also consider the relative efficacy of these antibiotics and antibiotic pairs in reducing the level of phenotypically resistant but genetically susceptible, persister, subpopulations. Our results provide compelling support for the proposition that the nature and form of the interactions between drugs of different classes, synergy, antagonism, suppression and additivity, has to be determined empirically and cannot be inferred from what is known about the pharmacodynamics or mode of action of these drugs individually. Monte Carlo simulations of within-host treatment incorporating these pharmacodynamic results and clinically relevant refuge subpopulations of bacteria indicate that: (i) the form of drug-drug interactions can profoundly affect the rate at which infections are cleared, (ii) two-drug therapy can prevent treatment failure even when bacteria resistant to single drugs are present at the onset of therapy, and (iii) this evolutionary virtue of two-drug therapy is manifest even when the antibiotics suppress each other's activity.
机译:使用多种而不是单一的抗生素治疗细菌感染有药理和进化方面的原因。组合使用抗生素可以更有效地杀死目标细菌以及预防耐药性的出现。然而,除了结核病外,很少有联合疗法用于细菌感染。原因之一是合理设计多种药物治疗方案所需的药代,种群和进化动态信息相对较少。在这里,我们使用体外药效学实验,数学模型和计算机模拟来探索不同两种药物疗法在清除细菌感染中的相对功效,以及在多种药物疗法可预防耐药性上升的条件下。我们估计参数并探索希尔功能的适合性,以比较金黄色葡萄球菌和大肠杆菌的致病菌株在灭杀实验中分别对和成对地比较四种不同类别的抗生素的药效学。我们还考虑了这些抗生素和抗生素对在降低表型耐药性但遗传易感性,持久性亚群水平方面的相对功效。我们的结果为以下命题提供了令人信服的支持:不同种类的药物之间的相互作用,协同作用,拮抗作用,抑制作用和可加性之间相互作用的性质和形式必须凭经验确定,并且不能从有关药效学或作用方式的知识中得出这些药物单独使用。结合这些药效学结果和细菌的临床相关避难所亚群的宿主内治疗的蒙特卡洛模拟表明:(i)药物-药物相互作用的形式可以深刻影响感染清除的速度,(ii)两种药物治疗即使在治疗开始时对单药具有耐药性的细菌,也可以预防治疗失败,并且(iii)即使在抗生素相互抑制活性的情况下,两药疗法的这种进化优势也很明显。

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