Han Nayoung, Ha Soojung, Yun Hwi-yeol, Kim Myeong Gyu, Min Sang-Il, Ha Jongwon, Lee Jangik Ike, Oh Jung Mi, Kim In-Wha
Clinical Pharmacy and Research Institute of Pharmaceutical Sciences, Seoul National University, Seoul, Korea.
Basic Clin Pharmacol Toxicol. 2014 May;114(5):400-6. doi: 10.1111/bcpt.12176. Epub 2013 Dec 11.
As tacrolimus has a rather narrow therapeutic range and high individual variability in its pharmacokinetics, it is important to determine the cause of the variation in tacrolimus pharmacokinetics. The purpose of this study was to establish a population pharmacokinetic-pharmacogenetic model of tacrolimus and identify covariates that affect pharmacokinetic parameters to prevent fluctuations in the tacrolimus trough concentration during the early period after transplantation. Data from 1501 trough concentrations and 417 densely collected concentrations were compiled from 122 patients who were on post-operative days 10-20 and analysed with a nonlinear mixed-effect model. The first-order conditional estimation (FOCE) with interaction method was used to fit the model using the NONMEM program. Clinical/laboratory data were also collected for the same period, and CYP3A5 and ABCB1 genotypes were analysed for use in modelling from all included patients. An empirical Bayesian approach was used to estimate individual pharmacokinetic profiles. A one-compartment model with first absorption and elimination and lag time best described the data. The estimated population mean of clearance (CL/F), volume of distribution (V/F) and absorption rate (Ka ) were 21.9 L/hr, 205 L, and 3.43/hr, respectively, and the lag time was fixed at 0.25 hr. Clearance increased with days after transplantation and decreased with CYP3A5*3/3 about 18.4% compared with CYP3A51 carriers (p < 0.001). A population pharmacokinetic model was developed for tacrolimus in early post-kidney transplantation recipients to identify covariates that affect tacrolimus pharmacokinetics. Post-operative days and CYP3A5 genotype were confirmed as critical factors of tacrolimus pharmacokinetics.
由于他克莫司的治疗窗较窄，其药代动力学存在较高的个体差异，因此确定他克莫司药代动力学变异的原因很重要。本研究的目的是建立他克莫司的群体药代动力学-药物遗传学模型，并识别影响药代动力学参数的协变量，以防止移植后早期他克莫司谷浓度的波动。收集了122例术后10-20天患者的1501个谷浓度数据和417个密集采集浓度数据，并用非线性混合效应模型进行分析。采用带交互作用的一阶条件估计（FOCE）方法，使用NONMEM程序拟合模型。同期还收集了临床/实验室数据，并对所有纳入患者的CYP3A5和ABCB1基因型进行分析以用于建模。采用经验贝叶斯方法估计个体药代动力学特征。具有一级吸收、消除和滞后时间的单室模型最能描述数据。清除率（CL/F）、分布容积（V/F）和吸收速率（Ka）的估计群体均值分别为21.9 L/hr、205 L和3.43/hr，滞后时间固定为0.25小时。清除率随移植后天数增加而升高，与CYP3A51携带者相比，CYP3A53/*3携带者的清除率降低约18.4%（p<0.001）。建立了肾移植术后早期他克莫司的群体药代动力学模型，以识别影响他克莫司药代动力学的协变量。术后天数和CYP3A5基因型被确认为他克莫司药代动力学的关键因素。
