Dunne A
J Pharm Pharmacol. 1986 Feb;38(2):97-101. doi: 10.1111/j.2042-7158.1986.tb04519.x.
Non-linear least-squares regression is commonly used for pharmacokinetic parameter estimation. Initial parameter estimates are required as a prelude to non-linear least-squares and the quality of the final parameter estimates may depend on these initial values. Polyexponential curve stripping is frequently used for the provision of initial estimates. It is demonstrated that under certain conditions conventional curve stripping yields biased estimates. A new iterative curve stripping technique is developed and is shown to be free of such bias. The two methods are compared using both simulated and real pharmacokinetic data.
非线性最小二乘法回归常用于药代动力学参数估计。作为非线性最小二乘法的前奏,需要初始参数估计值,最终参数估计值的质量可能取决于这些初始值。多指数曲线剥离常用于提供初始估计值。结果表明,在某些条件下,传统的曲线剥离会产生有偏差的估计值。本文开发了一种新的迭代曲线剥离技术,该技术不存在此类偏差。使用模拟和实际药代动力学数据对这两种方法进行了比较。