Pharmacometrics Institute for Practical Education and Training (PIPET), College of Medicine, The Catholic University of Korea.
Department of Pharmacology, College of Medicine, The Catholic University of Korea.
Ther Drug Monit. 2022 Dec 1;44(6):729-737. doi: 10.1097/FTD.0000000000001006. Epub 2022 Jul 13.
Tacrolimus shows high variability in inter- and intraindividual pharmacokinetics (PK); therefore, it is important to develop an appropriate model for accurate therapeutic drug monitoring (TDM) procedures. This study aimed to develop a pharmacokinetic model for tacrolimus that can be used for TDM procedures in Korean adult transplant recipients by integrating published models with acquired real-world TDM data and evaluating clinically meaningful covariates.
Clinical data of 1829 trough blood samples from 269 subjects were merged with simulated data sets from published models and analyzed using a nonlinear mixed-effect model. The stochastic simulation and estimation (SSE) method was used to obtain the final parameter estimates.
The final estimated values for apparent clearance, the volume of distribution, and absorption rate were 21.2 L/h, 510 L, and 3.1/h, respectively. The number of postoperative days, age, body weight, and type of transplant organs were the major clinical factors affecting tacrolimus PK.
A tacrolimus PK model that can incorporate published PK models and newly collected data from the Korean population was developed using the SSE method. Despite the limitations in model development owing to the nature of TDM data, the SSE method was useful in retrieving complete information from the TDM data by integrating published PK models while maintaining the variability of the model.
他克莫司在个体间和个体内的药代动力学（PK）中表现出高度变异性；因此，开发一种合适的模型用于准确的治疗药物监测（TDM）程序非常重要。本研究旨在开发一种他克莫司的药代动力学模型，通过整合已发表的模型和获得的真实世界 TDM 数据，并评估有临床意义的协变量，将其用于韩国成年移植受者的 TDM 程序。
将 269 名受试者的 1829 个谷浓度血样的临床数据与已发表模型的模拟数据集合并，并使用非线性混合效应模型进行分析。使用随机模拟和估计（SSE）方法获得最终参数估计值。
最终估计的表观清除率、分布容积和吸收速率分别为 21.2 L/h、510 L 和 3.1/h。术后天数、年龄、体重和移植器官类型是影响他克莫司 PK 的主要临床因素。
使用 SSE 方法开发了一种可以整合已发表 PK 模型和新收集的韩国人群数据的他克莫司 PK 模型。尽管由于 TDM 数据的性质限制了模型的开发，但 SSE 方法通过整合已发表的 PK 模型从 TDM 数据中检索完整信息，同时保持模型的变异性，在模型开发中非常有用。
