Abstract
Different concentrations of hydrophobically modified hydroxypropyl methylcellulose (HPMC, 60 M Grade) and conventional hydrophilic hydroxypropyl methylcellulose (50 cPs) were used to prepare four topical hydrogel formulations using a model non steroidal anti‐inflammatory drug (NSAID) diclofenac potassium (DP). For all the formulations, suitability of different common empirical (zero‐order, first‐order, and Higuchi), semi‐empirical (Ritger‐Peppas and Peppas‐Sahlin), and some new statistical (logistic, log‐logistic, Weibull, Gumbel, and generalized extreme value distribution) models to describe the drug release profile were tested through non‐linear least‐square curve fitting. A general purpose mathematical analysis tool MATLAB is used for the purpose. Further, instead of the widely used transformed linear fit method, direct fitting was used in the paper to avoid any sort of truncation and transformation errors. The results revealed that the log‐logistic distribution, among all the models that were investigated, was the best fit for hydrophobic formulations. For hydrophilic cases, the semi‐empirical models and Weibull distribution worked best, although log‐logistic also showed a close fit.
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