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Please use this identifier to cite or link to this item: http://hdl.handle.net/1993/8115

Title: Study of polymer hydration and drug release: texture analysis and model evaluation
Authors: Li, Hongtao
Supervisor: Gu, Xiaochen (Pharmacy)
Examining Committee: Collins, David (Pharmacy) Parkinson, Fiona (Pharmacology and Therapeutics) Simons, Keith (Pharmacy) Wu, Shirley X.Y.(University of Toronto)
Graduation Date: October 2012
Keywords: API
Active pharmaceutical ingredient
HPMC
Hydroxypropyl methylcellulose
PEO
Polyethylene oxide
Issue Date: 23-Jul-2012
Abstract: Hydrophilic polymers in a swellable matrix tablet hydrate quickly to form a hydrogel layer on the exterior of the dosage once in contact with water or biologic fluid. The resultant hydrogel serves as a barrier to regulate water permeation into the matrix and drug diffusion from the preparation. It is therefore important to understand how the polymer is hydrated and what mechanism exists between hydrogel formation and drug dissolution from a swellable matrix tablet. In this thesis, a TA texture analyzer was utilized to monitor and characterize matrix swelling properties during dissolution process. Multiple regression models were employed to analyze the quantitative relationship between drug dissolution or hydrogel thickness and major formulation factors (polymer ratio, drug solubility). Modified release matrix tablets were prepared using four APIs with a range of aqueous solubility, i.e., acetaminophen (ACE), chlorpheniramine (CHL), ibuprofen (IBU), and pseudoephedrine hydrochloride (PSE). Two hydrophilic polymers, polyethylene oxide (PEO) and hydroxypropyl methylcellulose (HPMC) were selected and tested as primary matrix polymers for the formulations. It was found from the experiments that multiple regression model was capable of estimating drug dissolution for both PEO and HPMC matrix preparations. Based on major formulation factors the regression models provide satisfactory prediction of drug release, which could further aid in formulation development and optimization.
URI: http://hdl.handle.net/1993/8115
Appears in Collection(s):FGS - Electronic Theses & Dissertations (Public)

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