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.
Keywords: Combination therapy; Mathematical modeling; Multi-drug resistant bacteria; Pharmacodynamics.