Lipophilic semisolid emulsion systems: viscoelastic behaviour and prediction of physical stability by neural network modelling

Abstract

The influence of different ratios of individual components (silicone surfactant, hydrophilic and lipophilic phase) on the viscoelastic behaviour of semisolid lipophilic emulsion systems was studied. The creams were prepared according to a preliminary experimental design (mixture design). The content of all three phases was varied: surfactant (1–5%), purified water (from 40 to 90%) and white petrolatum (5–59%). Oscillatory rheometry was used as the most appropriate experimental method for the evaluation of the emulsions. The rheological properties were influenced by the ratio of the components. For highly concentrated systems the predominant elastic response in the whole frequency range was measured. The cross-over point is characteristic for the concentrated systems. For the low concentrated systems, viscous behaviour is predominant. Rheometry has also been employed to follow and evaluate physical stability as one of the critical factors of emulsion systems. The dynamic rheological parameter, tan δ, has been chosen as the basis for developing mathematical models (linear, polynomial, neural) to forecast stability related to the content of the separate components in emulsion systems. After testing the linear models their non agreement to statistical criteria for a good model F reg, F lof, CC, DC, and RMS was found. The two-level neural network has been proven to be a statistically acceptable model, as were the polynomials of the second order. The two-level neural network model was also evaluated and the results have shown a great degree of reliability. The prediction of tan δ using a neural network model was found to be of great interest for the contemporary pharmaceutical formulation design because a lot of additional testing can be omitted.