Textural profiling and statistical optimization of crosslinked calcium-alginate-pectinate-cellulose acetophthalate gelisphere matrices

✍ Scribed by Viness Pillay; Michael P. Danckwerts

• Publisher: John Wiley and Sons
• Year: 2002
• Tongue: English
• Weight: 209 KB
• Volume: 91
• Category: Article
• ISSN: 0022-3549
• DOI: 10.1002/jps.10251

✦ Synopsis

A 2(5) factorial design was employed to statistically evaluate the textural properties of a crosslinked calcium-alginate-pectinate-cellulose acetophthalate gelisphere system. In accordance with the factorial matrix, gelispheres were formulated by titrating a combination polymeric solution comprised of sodium alginate, pectin and/or cellulose acetophthalate into an inducer solution (crosslinking agent) consisting of calcium and/or acetate ions. A Texture Analyzer was used to profile the gelisphere matrices for their resilience in the unhydrated and hydrated states, the fracture energy involved in matrix rupture, and the matrix hardness achieved with different levels of crosslinking. Significantly different textural properties were found among the crosslinked formulations. In particular, the unhydrated matrix resilience was selected as a parameter for optimization of the gelisphere formulation because of its large impact on drug release modulation, matrix integrity, and sensitivity to the crosslinking process. Resilience increased with increasing polymer concentration, irrespective of the polymer combination. Furthermore, resilience was not significantly influenced by the concentration of the crosslinking agents, but rather by the application of a higher polymer concentration in the crosslinking reaction; again irrespective of the polymer combination. In addition to the use of a factorial design, artificial neural modeling was employed to predict the textural properties based on the factorial matrix as a statistically suitable data source. Neural networks appeared to be a strong competitor of factorial regression for the prediction of textural data.