COUPLING THE IMAGE ANALYSIS AND THE ARTIFICIAL NEURAL NETWORKS TO PREDICT A MIXING TIME OF A PHARMACEUTICAL POWDER

In recent years, different laboratories were interested in predicting the mixing time of a pharmaceutical powder. In fact, a nonhomogeneous mixture may lead to under dose and/or overdose of the active ingredient in the drug product. Our study is aimed toward using a new and revolutionary approach in the field of the processes "The Artificial Neural Networks" (ANN) by using the Neural Networks Toolbox((TM)) derived from Matlab (R) software. The validation of the neural network was assumed by studying others mixing powders and then we compared the experimental results to the data obtained by the neural network calculations. Experimental results were obtained from a non-destructive method (Image Analysis) which was used in order to characterize the homogeneity of powder mixture in a V-Blender as well as a Cubic Blender which are most used in the pharmaceutical industry.