Sheiner L B, Beal S L
J Pharmacokinet Biopharm. 1981 Oct;9(5):635-51. doi: 10.1007/BF01061030.
Individual pharmacokinetic parameters quantify the pharmacokinetics of an individual, while population pharmacokinetic parameters quantify population mean-kinetics, interindividual variability, and residual variability, including intraindividual variability and measurement error. Individual pharmacokinetics are estimated by fitting individual data to a pharmacokinetic model. Population pharmacokinetic parameters have been estimated either by fitting all individuals' data together as though there were no individual kinetic difference, the naive pooled data (NPD) approach, or by fitting each individuals' data separately and then combining the individual parameter estimates, the two stage (TS) approach. A third approach, NONMEM, takes a middle course between these. This study provides further evidence of NONMEM's validity by comparing, using simulation, the three approaches on three types of data sets corresponding to three typical types of pharmacokinetic studies. The estimates of population parameters provided by the NPD method are poorer than those provided by either of the other methods. The estimates provided by the TS method are adequate for mean values and for residual variability, but not for interindividual kinetic variability. NONMEM's estimates are as good as those of the TS method for mean parameters and for residual variability, and considerably better for interindividual variability. The latter estimates are still not acceptable in an absolute sense. This is probably due, not to an intrinsic fault of the method (as it is in the case of the TS approach), but to an insufficient number of individuals being studied.
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则量化群体的平均动力学、个体间变异性和残余变异性，包括个体内变异性和测量误差。个体药代动力学通过将个体数据拟合到药代动力学模型来估计。群体药代动力学参数的估计方法有两种：一种是将所有个体的数据一起拟合，就好像不存在个体动力学差异一样，即单纯合并数据（NPD）法；另一种是分别拟合每个个体的数据，然后合并个体参数估计值，即两阶段（TS）法。第三种方法NONMEM则介于这两者之间。本研究通过模拟比较三种方法在对应于三种典型药代动力学研究类型的三种数据集上的表现，进一步证明了NONMEM的有效性。NPD方法提供的群体参数估计值比其他两种方法中的任何一种都要差。TS方法提供的估计值对于平均值和残余变异性是足够的，但对于个体间动力学变异性则不够。NONMEM对于平均参数和残余变异性的估计与TS方法一样好，对于个体间变异性的估计则明显更好。从绝对意义上讲，后者的估计值仍然不可接受。这可能不是由于该方法本身的缺陷（如TS方法那样），而是由于所研究的个体数量不足。
