The objective of this article is to optimize the similarity factor within immediate release (IR) and modified release (MR) of in vitro drug release profiles. The least square method is used to minimize the difference between empirical and regression curve fitting data of in vitro IR/MR drug release profiles. An estimation of percentage drug release at intermediate timepoints has been done to improve the similarity factor $f_{2}$ using linear curve fit method. In this study linear regression model is used to analyze the similarity factor $f_{2}$ for Nitrofurantoin MR Capsules, Venlafaxine HCl MR Tablets and Lurasidone IR Tablets in order to exhibit the significance as well as similarity owing to the consideration of extra intervening timepoints. This linear regression model may help pharmaceutical industries to examine the inside comparison of IR/MR in vitro drug release profile with few modifications in timepoint selection to improve similarity factor $f_{2}$ .

中文翻译：

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使用线性回归模型优化用于药物早期制剂开发的体外药物释放曲线的相似因子

本文的目的是优化体外药物释放曲线的速释 (IR) 和缓释 (MR) 内的相似因子。最小二乘法用于最小化体外 IR/MR 药物释放曲线的经验曲线拟合数据和回归曲线拟合数据之间的差异。已完成对中间时间点药物释放百分比的估计，以使用线性曲线拟合方法改进相似因子 $f_{2}$。在本研究中，线性回归模型用于分析呋喃妥因 MR 胶囊、盐酸文拉法辛 MR 片和鲁拉西酮 IR 片的相似因子 $f_{2}$ 以展示由于考虑额外干预时间点的显着性和相似性.