Abstract
This paper presents a three step methodology based on the use of chemical oriented models (MCR and CLS) for extracting out the chemical distribution maps (CDMs) from hyperspectral images, afterwards performing multivariate image analysis (MIA) on the CDMs, and finally extracting channel and textural features from the score images related to quality characteristics These features show complementary properties to those directly obtained from the CDMs, since they take advantage of their internal correlation structure. The approach has been successfully applied to the evaluation of homogeneity and cluster presence of API in a novel formulation developed to improve the dissolution of poorly soluble drugs.
