Jawień Wojciech
Faculty of Pharmacy, Jagiellonian University in Kraków, ul. Medyczna 9, 30-688, Kraków, Poland,
J Pharmacokinet Pharmacodyn. 2014 Dec;41(6):655-73. doi: 10.1007/s10928-014-9392-y. Epub 2014 Oct 15.
An effective method of construction of a linear estimator of AUC in the finite interval, optimal in the minimax sense, is developed and demonstrated for five PK models. The models may be given as an explicit C(t) relationship or defined by differential equations. For high variability and rich sampling the optimal method is only moderately advantageous over optimal trapezoid or standard numerical approaches (Gauss-Legendre or Clenshaw-Curtis quadratures). The difference between the optimal estimator and other methods becomes more pronounced with a decrease in sample size or decrease in the variability. The described estimation method may appear useful in development of limited-sampling strategies for AUC determination, as an alternative to the widely used regression-based approach. It is indicated that many alternative approaches are also possible.
针对五个药代动力学（PK）模型，开发并展示了一种在有限区间内构建AUC线性估计量的有效方法，该方法在极小极大意义上是最优的。这些模型可以表示为明确的C(t)关系，也可以由微分方程定义。对于高变异性和丰富采样情况，最优方法仅比最优梯形法或标准数值方法（高斯 - 勒让德或克伦肖 - 柯蒂斯求积法）略具优势。随着样本量的减少或变异性的降低，最优估计量与其他方法之间的差异会更加明显。所描述的估计方法可能在开发用于AUC测定的有限采样策略中有用，可作为广泛使用的基于回归方法的替代方法。结果表明，许多其他方法也是可行的。
