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Therefore, it is necessary to investigate an easy-to-use program for fitting release data with more ready-to-use dissolution models.Īnother important area in dissolution data analysis is assessment of the similarity between dissolution profiles. This may make it difficult for new users to implement the procedure.
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However, these programs require the user to define the equation manually and to provide an initial value for each parameter.
#Ja rule 336 zip software
Alternatively, the nonlinear fitting of dissolution data can be performed using other professional statistical software packages such as MicroMath Scientist ( 2), GraphPad Prism ( 3), SigmaPlot ( 4), or SYSTAT ( 5). However, until now, only one special program has been reported for fitting dissolution data, and only five release models have been implemented, and these could be applied only over a limited range ( 1). Because there is no available computer program for fitting drug release data using these specific nonlinear equations, it is desirable to develop a nonlinear fitting program for solving these problems in a convenient way. Therefore, quantitative evaluation of drug dissolution characteristics is of great interest to pharmaceutical scientists.Ī wide variety of mathematical models have been developed to fit the drug release data, most of which are presented as nonlinear equations. It can be used not only as a primary tool to monitor the consistency and stability of drug products but also as a relatively rapid and inexpensive technique to predict in vivo absorption of a drug formulation. In vitro dissolution testing plays an important role in drug formulation development and quality control. Sample runs of the program demonstrated that the results were satisfactory, and DDSolver could be served as a useful tool for dissolution data analysis.
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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. 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. However, until now, no computer program has been reported for simplifying the calculations involved in the modeling and comparison of dissolution profiles. 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.