Coupling the image analysis and the artificial neural networks to predict a mixing time of a pharmaceutical powder

Abstract

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^® software. The validation of the neural network was assumed by studying others mixing powder s 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.

Keywords: ANN; Image analysis; Homogeneity; Back-propagation algorithm; multi-layer perceptron