卷积法在体内外相关性研究中的应用

本文介绍了体内外相关性和卷积法/反卷积法的概念及原理, 阐述了采用卷积法使用Excel根据制剂的药代动力学数据计算其在体内释放行为的策略及方法, 并用于体内外相关性研究。该法用数学软件对药代动力学数据进行拟合以弥补缺失的数据点, 在假设输入函数基本符合威布尔规律的前提下, 在Excel中根据卷积法原理以试错法的方式确定拟合度最佳的输入函数(威布尔函数)参数, 最后以拟合度最佳的输入函数作为制剂的体内释放行为与体外释放数据进行相关性研究。在实例中不仅详细说明了该法的应用, 并且通过与隔室模型法和反卷积法的比较证明此方法简单有效, 可以作为体内外相关性研究的有力工具。

Application of numerical convolution in in vivo / in vitro correlation research

This paper introduced the conception and principle of in vivo / in vitro correlation (IVIVC) and convolution / deconvolution methods, and elucidated in details the convolution strategy and method for calculating the in vivo absorption performance of the pharmaceutics according to the their pharmacokinetic data in Excel, then put the results forward to IVIVC research.  Firstly, the pharmacokinetic data ware fitted by mathematical software to make up the lost points.  Secondly, the parameters of the optimal fitted input function were defined by trail-and-error method according to the convolution principle in Excel under the hypothesis that all the input functions fit the Weibull functions.  Finally, the IVIVC between in vivo input function and the in vitro dissolution was studied.  In the examples, not only the application of this method was demonstrated in details but also its simplicity and effectiveness were proved by comparing with the compartment model method and deconvolution method.  It showed to be a powerful tool for IVIVC research.