EVALUATION OF METHODS FOR ESTIMATING POPULATION PHARMACOKINETIC PARAMETERS .1. MICHAELIS-MENTEN MODEL - ROUTINE CLINICAL PHARMACOKINETIC DATA
EVALUATION OF METHODS FOR ESTIMATING POPULATION PHARMACOKINETIC PARAMETERS .1. MICHAELIS-MENTEN MODEL - ROUTINE CLINICAL PHARMACOKINETIC DATA
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DOI：
10.1007/bf01060053
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发表时间：
1980-01-01
期刊：
影响因子：
--
通讯作者：
BEAL, SL
中科院分区：
文献类型：
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作者：
SHEINER, LB;BEAL, SL
个体药代动力学参数量化个体的药代动力学，而群体药代动力学参数量化群体平均动力学、个体间变异性和剩余个体内变异性加上测量误差。个体药代动力学是通过将个体数据拟合到药代动力学模型来估计的。群体药代动力学参数的估计是通过将所有个体的数据拟合在一起，就像没有个体动力学差异一样（初始池数据法），或者单独拟合每个个体的数据，然后将个体参数估计值结合起来（两阶段法）。第三种方法，NONMEM[非线性混合效应模型]，在这两种方法之间走中间路线，避免了它们各自的缺点。采用每种方法分析49例患者在常规治疗过程中获得的124个稳态苯妥英浓度-剂量对数据集。由此得出的种群参数估计值差异很大（例如，种群平均Km估计值为1.57、5.36和4.44 .mu）。g/ml（分别采用朴素池数据、2期和NONMEM方法）。对模拟数据进行了分析，以研究差异。模拟表明，混合数据方法不能估计变量，并且产生不精确的平均动力学估计。两阶段方法可以很好地估计平均动力学，但对个体间变异性的估计有偏差和不精确。NONMEM产生所有参数的准确和精确的估计，并为它们提供合理的置信区间。这一表现正是从理论考虑所期望的，并为使用NONMEM从常规型患者数据估计人群药代动力学提供了经验支持。
Individual pharmacokinetic parameters quantify the pharmacokinetics of an individual, while population pharmacokinetic parameters quantify population mean kinetics, interindividual variability and residual intraindividual variability plus measurement error. Individual pharmacokinetics are estimated by fitting individual data to a pharmacokinetic model. Population pharmacokinetic parameters are estimated by fitting all individual''s data together as though there were no individual kinetic differences (the naive pooled data approach) or by fitting each individual''s data separately, and then combining the individual parameter estimates (the 2-stage approach). A 3rd approach, NONMEM [nonlinear mixed effect model], takes a middle course between these, and avoids shortcomings of each of them. A data set consisting of 124 steady-state phenytoin concentration-dosage pairs from 49 patients, obtained in the routine course of their therapy, was analyzed by each method. The resulting population parameter estimates differ considerably (e.g., population mean Km is estimated as 1.57, 5.36 and 4.44 .mu.g/ml by the naive pooled data, 2-stage and NONMEM approaches, respectively). Simulations of the data were analyzed to investigate the differences. The simulations indicate that the pooled data approach fails to estimate variabilities and produces imprecise estimates of mean kinetics. The 2-stage approach produces good estimates of mean kinetics, but biased and imprecise estimates of interindividual variability. NONMEM produces accurate and precise estimates of all parameters, and reasonable confidence intervals for them. This performance is exactly what is expected from theoretical considerations and provides empirical support for the use of NONMEM when estimating population pharmacokinetics from routine type patient data.