Staatz Christine E, Tett Susan E
School of Pharmacy, University of Queensland, Brisbane, Queensland 4072, Australia.
Eur J Clin Pharmacol. 2002 Dec;58(9):597-605. doi: 10.1007/s00228-002-0517-7. Epub 2002 Nov 15.
To compare the population modelling programs NONMEM and P-PHARM during investigation of the pharmacokinetics of tacrolimus in paediatric liver-transplant recipients.
Population pharmacokinetic analysis was performed using NONMEM and P-PHARM on retrospective data from 35 paediatric liver-transplant patients receiving tacrolimus therapy. The same data were presented to both programs. Maximum likelihood estimates were sought for apparent clearance (CL/F) and apparent volume of distribution (V/F). Covariates screened for influence on these parameters were weight, age, gender, post-operative day, days of tacrolimus therapy, transplant type, biliary reconstructive procedure, liver function tests, creatinine clearance, haematocrit, corticosteroid dose, and potential interacting drugs.
A satisfactory model was developed in both programs with a single categorical covariate--transplant type--providing stable parameter estimates and small, normally distributed (weighted) residuals. In NONMEM, the continuous covariates--age and liver function tests--improved modelling further. Mean parameter estimates were CL/F (whole liver) = 16.3 l/h, CL/F (cut-down liver) = 8.5 l/h and V/F = 565 l in NONMEM, and CL/F = 8.3 l/h and V/F = 155 l in P-PHARM. Individual Bayesian parameter estimates were CL/F (whole liver) = 17.9 +/- 8.8 l/h, CL/F (cut-down liver) = 11.6 +/- 8.8 l/h and V/F = 712 +/- 792 l in NONMEM, and CL/F (whole liver) = 12.8 +/- 3.5 l/h, CL/F (cut-down liver) = 8.2 +/- 3.4 l/h and V/F = 221 +/- 164 l in P-PHARM. Marked interindividual kinetic variability (38-108%) and residual random error (approximately 3 ng/ml) were observed. P-PHARM was more user friendly and readily provided informative graphical presentation of results. NONMEM allowed a wider choice of errors for statistical modelling and coped better with complex covariate data sets.
Results from parametric modelling programs can vary due to different algorithms employed to estimate parameters, alternative methods of covariate analysis and variations and limitations in the software itself.
在研究儿童肝移植受者他克莫司的药代动力学过程中，比较群体建模程序NONMEM和P-PHARM。
使用NONMEM和P-PHARM对35例接受他克莫司治疗的儿童肝移植患者的回顾性数据进行群体药代动力学分析。将相同的数据提供给这两个程序。寻求表观清除率（CL/F）和表观分布容积（V/F）的最大似然估计值。筛选对这些参数有影响的协变量包括体重、年龄、性别、术后天数、他克莫司治疗天数、移植类型、胆道重建手术、肝功能检查、肌酐清除率、血细胞比容、皮质类固醇剂量以及潜在的相互作用药物。
在两个程序中均建立了一个令人满意的模型，单一分类协变量——移植类型——提供了稳定的参数估计值以及小的、呈正态分布（加权）的残差。在NONMEM中，连续协变量——年龄和肝功能检查——进一步改善了建模。NONMEM中平均参数估计值为CL/F（全肝）=16.3 l/h，CL/F（减体积肝）=8.5 l/h，V/F = 565 l；P-PHARM中CL/F = 8.3 l/h，V/F = 155 l。NONMEM中个体贝叶斯参数估计值为CL/F（全肝）=17.9±8.8 l/h，CL/F（减体积肝）=11.6±8.8 l/h，V/F = 712±792 l；P-PHARM中CL/F（全肝）=12.8±3.5 l/h，CL/F（减体积肝）=8.2±3.4 l/h，V/F = 221±164 l。观察到明显的个体间动力学变异性（38 - 108%）和残余随机误差（约3 ng/ml）。P-PHARM更便于用户使用，并能轻松提供信息丰富的结果图形展示。NONMEM在统计建模时允许更广泛的误差选择，并且能更好地处理复杂的协变量数据集。
由于用于估计参数的算法不同、协变量分析的替代方法以及软件本身的差异和局限性，参数建模程序的结果可能会有所不同。
