DDSolver: An Add-In Program for Modeling and Comparison of Drug Dissolution Profiles
DDSolver: An Add-In Program for Modeling and Comparison of Drug Dissolution Profiles
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DOI：
10.1208/s12248-010-9185-1
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发表时间：
2010-09-01
期刊：
影响因子：
4.5
通讯作者：
Xie, Shaofei
中科院分区：
文献类型：
--
作者：
Zhang, Yong;Huo, Meirong;Xie, Shaofei
近年来，人们发展了几种数学模型来分析药物溶出度数据，并提出了许多不同的数学方法来评估两种药物溶出度曲线之间的相似性。然而，到目前为止，还没有关于简化溶出度曲线建模和比较所涉及的计算的计算机程序的报道。本文的目的是：(1)描述一个名为DDSolver的软件程序的开发，以便于评估药物溶出度数据之间的相似性；(2)利用非线性优化方法建立用于拟合溶出度数据的模型库；以及(3)简要回顾用于比较药物溶出度曲线的现有方法。DDSolver是一个免费提供的程序，它能够执行大多数现有的药物释放数据比较技术，包括探索性数据分析、单变量ANOVA、比率检验程序、差异系数f(1)、相似系数f(2)、Rescigno指数、差异法的90%可信区间(CI)、多元统计距离法、模型依赖法、Bootstrap f(2)法以及Chow和Ki的时间序列方法。程序的样品运行表明，结果令人满意，DDSolver可作为溶出数据分析的有用工具。
In recent years, several mathematical models have been developed for analysis of drug dissolution data, and many different mathematical approaches have been proposed to assess the similarity between two drug dissolution profiles. However, until now, no computer program has been reported for simplifying the calculations involved in the modeling and comparison of dissolution profiles. The purposes of this article are: (1) to describe the development of a software program, called DDSolver, for facilitating the assessment of similarity between drug dissolution data; (2) to establish a model library for fitting dissolution data using a nonlinear optimization method; and (3) to provide a brief review of available approaches for comparing drug dissolution profiles. DDSolver is a freely available program which is capable of performing most existing techniques for comparing drug release data, including exploratory data analysis, univariate ANOVA, ratio test procedures, the difference factor f(1), the similarity factor f(2), the Rescigno indices, the 90% confidence interval (CI) of difference method, the multivariate statistical distance method, the model-dependent method, the bootstrap f(2) method, and Chow and Ki's time series method. Sample runs of the program demonstrated that the results were satisfactory, and DDSolver could be served as a useful tool for dissolution data analysis.