ABSTRACT
The purpose of this study was to develop a simple and unique method of data reduction for pharmaceutical semisolids. Application and accuracy of different regression models for rate-controlled rotating cylinder and T-shaped spindle data was compared in a conventional analysis of variance. Methods employed to determine area under the flow curve (AUC) parameters included integration of fitting function, planimetration, and calculation of trapezoids. Complex rheological behavior such as structure breakdown at low rates of shear (D) and deflocculation of particle aggregates at high values for D is not sufficiently described by conventional fitting functions. Iterating the nonlinear power law function τ = τ0 + k2 · Dn0, however, gives the best fit of data for pharmaceutical samples, estimating a yield value, τ0.1 calculated for D = 0.1 s-1 following double logarithmic transformation. Alternatively, rheological AUC parameters are determined for D: 0 ≤ D ≤ 98 s-1. Validating models, maximum deviation for different methods of determination is smaller than Srel of 5 consecutive planimetration experiments. In case of sufficient fit of experimental data, integration of a nonlinear power law function is acceptable. Convenient fitting parameters τ and n0 can be substituted by area parameters such as AT, Arel, or R for all liquids, and hydrophilic and lipophilic gels, as well as o/w and w/o emulsions being investigated. The new AUC method offers robust data reduction and universal pharmaceutical application for different Newtonian and (pseudo)plastic materials. The approach is, however, limited to instrumental conditions and the range of D.