Nikolaou Michael, Schilling Amy N, Vo Giao, Chang Kai-Tai, Tam Vincent H
Department of Chemical & Biomolecular Engineering, University of Houston, Houston, TX 77204-4004, USA.
Ann Biomed Eng. 2007 Aug;35(8):1458-70. doi: 10.1007/s10439-007-9306-x. Epub 2007 Apr 13.
We present the development and first experimental validation of a mathematical modeling framework for predicting the eventual response of heterogeneous (distributed-resistance) microbial populations to antimicrobial agents at time-periodic (hence pharmacokinetically realistic) concentrations. Our mathematical model predictions are validated in a hollow-fiber in vitro experimental infection model. They are in agreement with the threshold levofloxacin exposure necessary to suppress resistance development of Pseudomonas aeruginosa in a murine thigh infection model. Predictions made by the proposed mathematical modeling framework can offer guidance for targeted testing of promising regimens. This can aid the development and clinical use of antimicrobial agents that combat microbial resistance.
我们展示了一个数学建模框架的开发及其首次实验验证,该框架用于预测异质(分布抗性)微生物群体在时间周期性(因此在药代动力学上符合实际)浓度下对抗菌剂的最终反应。我们的数学模型预测在中空纤维体外实验感染模型中得到了验证。它们与抑制小鼠大腿感染模型中铜绿假单胞菌耐药性发展所需的左氧氟沙星暴露阈值一致。所提出的数学建模框架所做的预测可为有前景的治疗方案的靶向测试提供指导。这有助于对抗微生物耐药性的抗菌剂的开发和临床应用。