Mathematical Modeling of Drug Release Profiles for Modified Hydrophobic HPMC Based Gels

Hydroxypropyl methylcellulose (HPMC) is now available in modified hydrophobic forms (Sangelose). In this paper, the effect of viscosity grade and HPMC concentration on in vitro release kinetics of a topically applied drug were studied using gel formulations of a nonsteroidal anti-inflammatory drug (NSAID), diclofenac potassium (DP), with different viscosity grades of the polymer (60L, 60 M, 90 M for hydrophobic HPMC and 50 cPs for conventional hydrophilic HPMC) in different proportions. It was found that hydrophobic HPMC-based gels having a higher viscosity and lower polymer concentration release a notably higher amount of drug compared with hydrophilic HPMC-based gels containing a higher concentration of polymer but with lower viscosity. For gels, the suitability of different common empirical (zero-order, first-order, and Higuchi), and semi-empirical (Ritger-Peppas and Peppas-Sahlin) models, 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 was used. Further, instead of the widely used transformed linear fit method, direct fitting was used in the paper to avoid any form of truncation and transformation errors. The results revealed that the log-logistic distribution, amongst all the models investigated, was the best fit for hydrophobic formulations. For hydrophilic ones, the semi-empirical models and Weibull distribution worked best, although log-logistic also showed a close fit. The shape parameter for the log-logistic and Weibull distribution conveys vital information about the rate of release and helps improve understanding of drug release profiles.