Abstract

Particle and granule properties play a key role in the final product quality of pharmaceuticals.

Thus the identification and monitoring of key chemical and physical parameters is essential in the production of pharmaceuticals. The existing off-line methods are generally slow and labour intensive. Near infra-red (NIR) multipoint spectroscopy and image analysis are an attractive alternative compared to the traditional methods because they are both nondestructive and non-interfering allowing the analysis in real time of particles physical and chemical properties. This research is a preliminary study performed at laboratory scale and aims at developing chemometric and imaging algorithms for real time measuring of pharmaceutical chemical and physical properties. These algorithms utilised real time NIR multipoint spectroscopy and a novel imaging system. NIR multipoint spectroscopy followed by a regression technique (such as PLS) was used to build calibration models to quantify a compound in a small size binary granule mixture under both static and dynamic conditions.

The imaging technology provided key physical properties such as size, shape and texture. The Haralick correlation property and the variogram were used to analyse the surface texture of particles. These algorithms allowed the classification of particles by their morphological nature under both static and dynamic conditions.