Time-kill experiments can discern the pharmacodynamics of infectious bacteria exposed to antibiotics in vitro, and thus help guide the design of effective therapies for challenging clinical infections. This task is resource-limited, therefore typically bypassed in favor of empirical shortcuts. The resource limitation could be addressed by continuously assessing the size of a bacterial population under antibiotic exposure using optical density measurements. However, such measurements count both live and dead cells and are therefore unsuitable for declining populations of live cells. To fill this void, we develop here a model-based method that infers the count of live cells in a bacterial population exposed to antibiotics from continuous optical-density measurements of both live and dead cells combined. The method makes no assumptions about the underlying mechanisms that confer resistance and is widely applicable. Use of the method is demonstrated by an experimental study on Acinetobacter baumannii exposed to levofloxacin.

Time-kill 实验可以辨别在体外暴露于抗生素的感染性细菌的药效学，从而有助于指导针对具有挑战性的临床感染的有效疗法的设计。此任务是资源有限的，因此通常绕过以支持经验捷径。资源限制可以通过使用光密度测量持续评估抗生素暴露下细菌种群的大小来解决。然而，这种测量同时计算活细胞和死细胞，因此不适用于减少的活细胞群。为了填补这一空白，我们在这里开发了一种基于模型的方法，该方法通过对活细胞和死细胞的连续光密度测量来推断暴露于抗生素的细菌群中活细胞的数量。该方法对赋予抵抗力的潜在机制没有任何假设，并且可以广泛适用。实验研究证明了该方法的使用鲍曼不动杆菌暴露于左氧氟沙星。