Background: The quantitative determination of the effects of antimicro- bials is essential for our understanding of pharmacodynamics and for their rational clinical application. However, common pharmacodynamic measures of antimicrobial efficacy, such as the MIC and the pharmacodynamic func- tion, fail to capture the observed dependence of efficacy on the bacterial population size - a phenomenon called inoculum effect. Objectives: We aimed to assess the relationship between bacterial inoculum size and pharmacodynamic parameters, and to determine the consequences of the inoculum effect on bacterial population dynamics under treatment with antimicrobials. Methods: We used the mathematical multi-hit model to quantify the effect of the inoculum on the pharmacodynamic parameters. The model describes antimicrobial action mechanistically, which allowed us to test various hypotheses concerning the mechanistic basis of the inoculum effect. Results: Our model showed that the inoculum effect can arise from the binding dynamics of antimicrobial molecules to bacterial targets alone and does not require enzymatic degradation of antimicrobials. With enzymatic degradation, however, the inoculum effect is more pronounced. We propose to include the inoculum effect when measuring antimicrobial efficacy, i.e. to extend the pharmacodynamic function with the inoculum effect. This extended pharmacodynamic function mimiced simple long-term population dynamics well. More complex scenarios were only captured with the mechanism-based multi-hit model. In simulations with competing antimicrobial-sensitive and -resistant bacteria, neglecting the inoculum effect lead to an overestimation of the competitive ability of the resistant strain. Conclusions: Our work emphasizes that the pharmacodynamic function - and in general any efficacy measure, e.g. the MIC - should include information about the inoculum size on which it is based, and ideally account for the inoculum effect.

中文翻译：

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从细菌种群建模的角度看药效接种物的作用

背景：定量确定抗菌药物的作用对于我们了解药效学及其合理的临床应用至关重要。但是，常用的抗微生物功效的药效学指标，如MIC和药效学功能，未能捕获观察到的功效对细菌种群大小的依赖性，这种现象称为接种效应。目的：我们旨在评估细菌接种量与药效学参数之间的关系，并确定接种物对抗生素治疗后细菌种群动态的影响。方法：我们使用数学的多重打击模型来量化接种物对药效学参数的影响。该模型以机械方式描述了抗菌作用，这使我们能够检验有关接种物作用机理的各种假设。结果：我们的模型表明，接种物的作用可能是由于抗菌剂分子与细菌靶标的结合动力学而产生的，不需要酶解抗菌剂。但是，随着酶的降解，接种物的作用更加明显。我们建议在测量抗菌功效时包括接种物作用，即通过接种物作用扩展药效学功能。这种扩展的药效学功能很好地模仿了简单的长期种群动态。仅使用基于机制的多次打击模型才能捕获更复杂的场景。在对竞争性抗菌敏感和耐药细菌的模拟中，忽视接种效应会导致高估抗性菌株的竞争能力。结论：我们的工作强调，药效学功能-通常包括MIC等任何功效指标，都应包括有关其所依据的接种量的信息，并在理想情况下应考虑接种物的作用。