Nielsen Elisabet I, Viberg Anders, Löwdin Elisabeth, Cars Otto, Karlsson Mats O, Sandström Marie
Division of Pharmacokinetics and Drug Therapy, Uppsala University, Box 591, SE-751 24 Uppsala, Sweden.
Antimicrob Agents Chemother. 2007 Jan;51(1):128-36. doi: 10.1128/AAC.00604-06. Epub 2006 Oct 23.
Dosing of antibacterial agents is generally based on point estimates of the effect, even though bacteria exposed to antibiotics show complex kinetic behaviors. The use of the whole time course of the observed effects would be more advantageous. The aim of the present study was to develop a semimechanistic pharmacokinetic (PK)/pharmacodynamic (PD) model characterizing the events seen in a bacterial system when it is exposed to antibacterial agents with different mechanisms of action. Time-kill curve experiments were performed with a strain of Streptococcus pyogenes exposed to a wide range of concentrations of the following antibiotics: benzylpenicillin, cefuroxime, erythromycin, moxifloxacin, and vancomycin. Bacterial counts were monitored with frequent sampling during the experiment. A simultaneous fit of all data was accomplished. The degradation of the drugs was monitored and corrected for in the model, and a link model was used to account for an effect delay. In the final PK/PD model, the total bacterial population was divided into two subpopulations: one growing drug-susceptible population and one resting insusceptible population. The drug effect was included as an increase of the killing rate of bacteria in the susceptible state, according to a maximum-effect (E(max)) model. An internal model validation showed that the model was robust and had good predictability. In conclusion, for all drugs, the final PK/PD model successfully described bacterial growth and killing kinetics when the bacteria were exposed to different antibiotic concentrations. The semimechanistic model that was developed might, after further refinement, serve as a tool for the development of optimal dosing strategies for antibacterial agents.
抗菌药物的给药通常基于效应的点估计，尽管暴露于抗生素的细菌表现出复杂的动力学行为。使用观察到的效应的整个时间过程会更具优势。本研究的目的是建立一个半机制药代动力学（PK）/药效动力学（PD）模型，以表征细菌系统在暴露于具有不同作用机制的抗菌药物时所观察到的事件。用一株化脓性链球菌进行了时间-杀菌曲线实验，该菌株暴露于以下抗生素的广泛浓度范围：苄青霉素、头孢呋辛、红霉素、莫西沙星和万古霉素。在实验过程中通过频繁采样监测细菌计数。完成了所有数据的同时拟合。在模型中监测并校正了药物的降解，并使用链接模型来解释效应延迟。在最终的PK/PD模型中，总细菌群体被分为两个亚群体：一个生长中的药物敏感群体和一个静止的不敏感群体。根据最大效应（E(max)）模型，将药物效应作为易感状态下细菌杀灭率的增加纳入模型。内部模型验证表明该模型稳健且具有良好的预测性。总之，对于所有药物，最终的PK/PD模型成功地描述了细菌在暴露于不同抗生素浓度时的生长和杀灭动力学。所建立的半机制模型经过进一步完善后，可能会成为开发抗菌药物最佳给药策略的工具。
