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Statistical Modeling of Drug Release Profiles for HPMC Matrix Tablets

Wenzhao Yang, Statistician, The Dow Chemical Company
Jin Zhao, Scientist, The Dow Chemical Company
Jamie Curtis-Fisk, Scientist, The Dow Chemical Company
Karen Balwinski, Scientist, The Dow Chemical Company
True Rogers, Scientist, The Dow Chemical Company
Shrikant Khot, Scientist, The Dow Chemical Company


Matrix tablets containing hypromellose, also called hydroxypropyl methylcellulose (HPMC), are widely used in oral drug delivery to modulate drug release over time. Drug release is primarily influenced by the kinetics and extent of polymer swelling and erosion, and drug (or active pharmaceutical ingredient (API)) dissolution, diffusion, and/or erosion through the polymer matrix. Mathematical modeling of drug release profiles has been developed in the past to enable pharmaceutical scientists to design and optimize matrix tablet formulations. This research focuses on using statistical analyses to compare and assess the suitability of various models for METHOCEL™ Premium HPMC matrices. Linear mixed model (LMM) without mathematical models and two-stage model (TSM) with mathematical models were used to develop predictive models. Multiple regression methods (Stepwise Regression, Partial Least Square and Generalized models) in JMP were implemented to incorporate drug property factors for modeling drug release rate in TSM. The predictive model developed here provided mechanistic insight into kinetic release profile of HPMC matrices. This can be used to aid pharmaceutical scientists with efficient and streamlined formulation design and in vitro drug release experimentation to deliver desired modified-release performance.
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