Qin Yan, Jiao Zheng, Ye Yan-Rong, Wang Zi, Zou Ye, Shen Yun, Lv Qian-Zhou
Department of Pharmacy, Zhongshan Hospital, Fudan University, Shanghai, China.
Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Eur J Pharmacol. 2025 Sep 5;1002:177777. doi: 10.1016/j.ejphar.2025.177777. Epub 2025 May 28.
In critically ill patients, determining the appropriate dose of linezolid requires pharmacokinetic data on the drug and an understanding of covariate effects on its disposition. However, previous studies has reported that the established population pharmacokinetic models demonstrate an unsatisfactory predictability when applied to external clinical settings. The aim of this study was to establish and evaluate a population pharmacokinetic and pharmacodynamic model for linezolid in critically ill patients.
A total of 319 linezolid concentrations and 927 platelet counts were collected from 202 Chinese patients administered linezolid. Linezolid concentrations were quantified using a validated liquid chromatography-tandem mass spectrometry method. A population pharmacokinetic and pharmacodynamic model was developed through nonlinear mixed-effects modeling. The established model was evaluated using bootstrap method, goodness-of-fit plots and visual predictive check. Based on the established model and identified covariates, an optimal dosing regimen was developed.
A one-compartment model with first-order absorption and elimination was developed to characterize the pharmacokinetics of linezolid. Creatinine clearance (CLcr) and Severe liver impairment (Child-Pugh C) were identified as the most significant covariates influencing clearance (CL). The typical values of CL and volume of distribution (Vd) in the final model were 2.03 L/h and 38.5 L, respectively. Both CLcr and fibrinogen levels demonstrated significant effects on baseline platelet count, while the area under the concentrations-time curve of linezolid exhibited a significant impact on mean transit time. Simulations based on the established population pharmacokinetic and pharmacodynamic model suggested that a reduced dose of linezolid 400 mg or 300 mg administered every 12 h could achieve the pharmacodynamic target while reducing thrombocytopenia risks in patients with CLcr <60 mL/min or severe liver impairment. Furthermore, the median time to thrombocytopenia onset was 12 days for patients with baseline platelet >200 × 10/L and 8 days for those with baseline platelet between 100 × 10/L and 200 × 10/L when receiving the standard dose of 1200 mg/day.
Critically ill patients, especially those with severe renal impairment or severe liver impairment, may necessitate a reduced linezolid dose to prevent overexposure. The established population pharmacokinetic and pharmacodynamic model could support individualized dosing optimization of linezolid in criticslly ill patients.
在重症患者中，确定利奈唑胺的合适剂量需要该药物的药代动力学数据以及对协变量对其处置影响的了解。然而，先前的研究报告称，已建立的群体药代动力学模型应用于外部临床环境时预测性不尽人意。本研究的目的是建立并评估重症患者中利奈唑胺的群体药代动力学和药效学模型。
从202例接受利奈唑胺治疗的中国患者中收集了总共319个利奈唑胺血药浓度和927次血小板计数。利奈唑胺浓度采用经过验证的液相色谱 - 串联质谱法进行定量。通过非线性混合效应建模建立群体药代动力学和药效学模型。使用自助法、拟合优度图和可视化预测检查对建立的模型进行评估。基于建立的模型和确定的协变量，制定了最佳给药方案。
建立了一个具有一级吸收和消除的单室模型来描述利奈唑胺的药代动力学特征。肌酐清除率（CLcr）和严重肝功能损害（Child - Pugh C级）被确定为影响清除率（CL）的最显著协变量。最终模型中CL和分布容积（Vd）的典型值分别为2.03 L/h和38.5 L。CLcr和纤维蛋白原水平均对基线血小板计数有显著影响，而利奈唑胺浓度 - 时间曲线下面积对平均通过时间有显著影响。基于建立的群体药代动力学和药效学模型进行的模拟表明，对于CLcr<60 mL/min或严重肝功能损害的患者，每12小时给予400 mg或300 mg的利奈唑胺减量方案可实现药效学目标，同时降低血小板减少的风险。此外，接受1200 mg/天标准剂量时，基线血小板>200×10⁹/L的患者血小板减少症发作的中位时间为12天，基线血小板在100×10⁹/L至200×10⁹/L之间的患者为8天。
重症患者，尤其是严重肾功能损害或严重肝功能损害的患者，可能需要减少利奈唑胺剂量以防止药物暴露过量。建立的群体药代动力学和药效学模型可为重症患者利奈唑胺的个体化给药优化提供支持。
