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

9 December 2009; accepted 8 March 2010; published online 6 April 2010 | Yong Zhang, Meirong Huo, Jianping Zhou, Aifeng Zou, Weize Li, Chengli Yao, Shaofei Xie
The article introduces DDSolver, a freely available add-in program for Microsoft Excel designed to facilitate the modeling and comparison of drug dissolution data. The program aims to simplify the calculations involved in assessing the similarity between drug dissolution profiles, which is a critical aspect of drug formulation development and quality control. DDSolver supports various statistical methods for comparing dissolution profiles, including exploratory data analysis, univariate ANOVA, ratio test procedures, difference factor f1, similarity factor f2, Rescigno indices, 90% confidence interval (CI) of difference method, multivariate statistical distance method, model-dependent method, bootstrap f2 method, and Chow and Ki’s time series method. The program uses nonlinear least-squares curve-fitting techniques and the Nelder-Mead simplex algorithm for parameter estimation. It also provides user-defined functions for characterizing drug release curves and assessing the similarity between dissolution profiles. Sample runs demonstrate the program's reliability and ease of use, making it a valuable tool for pharmaceutical scientists.The article introduces DDSolver, a freely available add-in program for Microsoft Excel designed to facilitate the modeling and comparison of drug dissolution data. The program aims to simplify the calculations involved in assessing the similarity between drug dissolution profiles, which is a critical aspect of drug formulation development and quality control. DDSolver supports various statistical methods for comparing dissolution profiles, including exploratory data analysis, univariate ANOVA, ratio test procedures, difference factor f1, similarity factor f2, Rescigno indices, 90% confidence interval (CI) of difference method, multivariate statistical distance method, model-dependent method, bootstrap f2 method, and Chow and Ki’s time series method. The program uses nonlinear least-squares curve-fitting techniques and the Nelder-Mead simplex algorithm for parameter estimation. It also provides user-defined functions for characterizing drug release curves and assessing the similarity between dissolution profiles. Sample runs demonstrate the program's reliability and ease of use, making it a valuable tool for pharmaceutical scientists.
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