Viscous behaviour of pharmaceutical creams: characterisation by neural network and polynomial modelling

Autori: M. Gasperlin, L. Tusar,J. Smid-Korbar, J. Kristl
Presentato al: Southern Europe Conference on Rheology
Anno: 1999
Volume: 2
Issue: Unico
Casa Editrice: SIR-Cuen Napoli
Lingua: English


Abstract
Viscosity is undoubtedly one of the most important rheological parameters characterising pharmaceutical semisolid systems like creams, ointments or gels. These systems are very heterogeneous with exhibited complex flow behaviour. Because of the simultaneously presence of viscous and elastic characteristics, as a reflection of their internal structure, they represent the most complicated systems for rheological evaluation. Pharmaceutical creams are semisolid emulsion systems, composed of surfactant, lipophilic in hydrophilic phase. In these polydisperse systems a surfactant or its blends interact with themselves and/or with hydrophilic or lipophilic phase, to form a gel network. Such internal structure decisively influences on appearance, physical stability and drug transport of the dosage form (1,2).
The neural networks still represent a rather new method in the area of modelling. They can be used for the empirical modelling, grouping and recognition. In the field of pharmacy the application of artificial neural network methodology has recently gained the importance (3,4,5). The potential applications are dosage form design and analysis, biopharmacy, drug design, epidemiology and clinical pharmacy (6).
The purpose of this study was to find out the dependence of a rheological parameter, complex dynamic viscosity on the composition of the studied pharmaceutical creams. The error back propagation neural network and polynomial models was uses to define it.


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