Andreu Franc, Colom Helena, Grinyó Josep M, Torras Joan, Cruzado Josep M, Lloberas Nuria
*Department of Pharmacy and Pharmaceutical Technology, School of Pharmacy, University of Barcelona; and †Nephrology Service and Laboratory of Experimental Nephrology, Hospital Universitari de Bellvitge, Barcelona, Spain.
Ther Drug Monit. 2015 Apr;37(2):246-55. doi: 10.1097/FTD.0000000000000134.
Tacrolimus pharmacokinetics (PK) presents a high variability that hampers its therapeutic use. The aims of this study are to: (1) develop a population pharmacokinetic (PPK) model for tacrolimus and to identify the factors that contribute to the variability of tacrolimus PK in renal transplant patients; and (2) to establish a new Bayesian estimator that can easily and routinely be applied in the hospital. A new PPK model may allow efficacy to be optimized, improve dose regimens, minimize side effects, and decrease the cost of extensive area under the curve (AUC) monitoring.
PPK analysis of the full PK profiles of 16 patients on 5 occasions was performed with NONMEM 7.2. Biochemical variables (hematocrit, hemoglobin, aspartate aminotransferase, and others) were analyzed.
A 2-open-compartment model with interoccasion variability best described the PK of tacrolimus. Three transit compartments provided the best description of the absorption process. The hematocrit, aspartate aminotransferase, and alanine aminotransferase were not significant in the covariate analysis. External validation with 91 patients proved the good predictability of the model with a bias and precision of 0.37 mcg/L (CI 95%, -0.11 to 1.20 mcg/L) and 0.38 mcg/L (CI 95%, 0.02 to 1.21 mcg/L), respectively. A limited sampling strategy using 1 sampling point at predose (trough concentrations) showed a good performance in AUC0-12h estimation with a correlation between AUCfull and AUCLSS, bias and imprecision of r = 0.75, 6.78% (range, -16.26% to 30.06%) and 1.42% (IC 95%, 0.14%-3.61%), respectively.
The PPK model developed provides reliable prior information for Bayesian adaptive control of dosage regimens of tacrolimus to achieve the desired AUC goals in stable renal transplant patients.
他克莫司的药代动力学（PK）存在高度变异性，这妨碍了其治疗应用。本研究的目的是：（1）建立他克莫司的群体药代动力学（PPK）模型，并确定导致肾移植患者他克莫司PK变异性的因素；（2）建立一种新的贝叶斯估计器，可在医院中轻松且常规地应用。新的PPK模型可能有助于优化疗效、改进给药方案、最小化副作用并降低曲线下面积（AUC）广泛监测的成本。
使用NONMEM 7.2对16例患者5次的完整PK谱进行PPK分析。分析了生化变量（血细胞比容、血红蛋白、天冬氨酸转氨酶等）。
具有给药间隔变异性的二室开放模型能最好地描述他克莫司的PK。三个转运室能最好地描述吸收过程。在协变量分析中，血细胞比容、天冬氨酸转氨酶和丙氨酸转氨酶无显著意义。对91例患者进行的外部验证证明该模型具有良好的预测性，偏差和精密度分别为0.37 mcg/L（95%CI，-0.11至1.20 mcg/L）和0.38 mcg/L（95%CI，0.02至1.21 mcg/L）。在给药前（谷浓度）使用1个采样点的有限采样策略在AUC0-12h估计中表现良好，AUC全值与AUC有限采样策略值之间的相关性、偏差和不精密度分别为r = 0.75、6.78%（范围，-16.26%至30.06%）和1.42%（95%IC，0.14%-3.61%）。
所建立的PPK模型为他克莫司给药方案的贝叶斯自适应控制提供了可靠的先验信息，以在稳定的肾移植患者中实现所需的AUC目标。
