D'Argenio D Z
J Pharmacokinet Biopharm. 1981 Dec;9(6):739-56. doi: 10.1007/BF01070904.
A sequential estimation procedure is presented which uses optimal sampling times to estimate the parameters of a model from data obtained from a group of subjects. This optimal sampling sequential estimation procedure utilizes parameter estimates from previous subjects in the group to determine the optimal sampling times for the next subject. Parameter estimates obtained from the optimal sampling procedure are compared to those obtained from a conventional sampling scheme by using Monte Carlo simulations which include noise terms for both assay error and intersubject variability. The results of these numerical experiments, for the two examples considered here, show that the parameter estimates obtained from data collected at optimal sampling times have significantly less variability than those generated using the conventional sampling procedure. We conclude that optimal sampling and preexperiment simulation may be useful tools for designing informative pharmacokinetic experiments.
本文提出了一种序贯估计程序，该程序使用最优采样时间从一组受试者获得的数据中估计模型参数。这种最优采样序贯估计程序利用组中先前受试者的参数估计来确定下一个受试者的最优采样时间。通过蒙特卡罗模拟将从最优采样程序获得的参数估计与从传统采样方案获得的参数估计进行比较，蒙特卡罗模拟包括分析误差和受试者间变异性的噪声项。对于这里考虑的两个例子，这些数值实验的结果表明，在最优采样时间收集的数据所获得的参数估计的变异性明显小于使用传统采样程序产生的变异性。我们得出结论，最优采样和实验前模拟可能是设计信息丰富的药代动力学实验的有用工具。
