Laboratory of Drug Metabolism and Pharmacokinetics, Showa Pharmaceutical University, 3-3165, Machida, Tokyo, 194-8543, Japan.
Certara UK Limited, Sheffield, UK.
Eur J Clin Pharmacol. 2021 Aug;77(8):1157-1168. doi: 10.1007/s00228-021-03098-w. Epub 2021 Feb 1.
Variability in teicoplanin pharmacokinetics has been explained by multiple factors such as body weight, renal function, and serum albumin level. To improve mechanistic understanding of the causes of variability, a physiologically based pharmacokinetic (PBPK) model can be used as a systematic platform. In this study, a PBPK model of teicoplanin was developed to quantitatively assess the effects of physiological changes due to disease status using virtual populations.
Predictive performance of the models was evaluated by comparing simulated and observed concentration-time profiles of teicoplanin. Subsequently, sensitivity analyses were conducted to identify potential factors contributing to individual differences in teicoplanin PK.
The developed PBPK model generated concentration-time profiles that were comparable to clinical observations in healthy adults, including Caucasians and Japanese, and after single-dose and multiple-dose administration. The predicted PK parameters (i.e., C, AUC, clearance) were within a two-fold range of the observed data in patients with renal impairments as well as healthy adults. Changes in total and unbound teicoplanin concentrations at 72 h, after various dosing regimens (tested 4-14 mg/kg q12h for three doses as a loading dose and then 4-14 mg/kg daily as a maintenance dose), were sensitive to renal function and serum albumin concentrations.
The PBPK model of teicoplanin provides mechanistic insight into the factors altering its disposition and allows assessments of the theoretical and quantitative impact of individual changes in physiological parameters on its PK even when an actual assessment with adequate sample sizes of patients is challenging.
替考拉宁药代动力学的变异性可以用多种因素来解释，如体重、肾功能和血清白蛋白水平。为了提高对变异性原因的机制理解，可以使用基于生理学的药代动力学（PBPK）模型作为系统平台。本研究开发了替考拉宁的 PBPK 模型，以使用虚拟人群定量评估疾病状态下生理变化对其药代动力学的影响。
通过比较替考拉宁的模拟和观察浓度-时间曲线来评估模型的预测性能。随后，进行敏感性分析以确定可能导致替考拉宁 PK 个体差异的潜在因素。
所开发的 PBPK 模型生成的浓度-时间曲线与健康成年人（包括白种人和日本人）以及肾功能损害患者和健康成年人单次和多次给药后的临床观察结果相当。在肾功能损害患者和健康成年人中，预测的 PK 参数（即 C、AUC、清除率）与观察数据的比值在两倍范围内。在不同的给药方案（测试了 4-14 mg/kg q12h 作为负荷剂量给药三剂，然后 4-14 mg/kg 每日作为维持剂量）下，72 小时时总替考拉宁和游离替考拉宁浓度的变化对肾功能和血清白蛋白浓度敏感。
替考拉宁的 PBPK 模型提供了对改变其处置的因素的机制理解，并允许评估生理参数个体变化对其 PK 的理论和定量影响，即使在实际评估中对患者进行充分的样本量评估具有挑战性。
