New Chemometric Algorithms In Multivariate Image Analysis And Quantitative Structure-Activity Relationships Studies

The research work in this thesis focuses on the multivariate image analysis and QSAR studies and the design of some new chemometric algorithms used in these two fields.Chemical imaging analysis holds great potential in probing the chemical heterogeneity of samples with high spatial resolution and molecular specificity. This thesis demonstrates the implementation of Raman mapping for microscopic characterization of tablets containing chloramphenicol palmitate polymorphs with the aid of a new multivariate image segmentation approach based on spatial directed agglomeration clustering. This approach performs the agglomeration clustering by stepwise merging the pixels possessing both spatial closeness and spectral similarity into clusters that define the image segmentation. Additionally, the stepwise merging of clusters offers an F-statistics based procedure to automatically ascertain the number of image segments. Raman mapping analysis of tablets containing two polymorphs of chloramphenicol palmitate followed by multivariate image segmentation reveals that the proposed technique offers the identification of each polymorph and a quantitative visualization of the spatial distribution of the polymorphs identified. This technique holds promise in rapid, noninvasive and quantitative polymorph analysis for pharmaceutical production processes.A pure variable resolution algorithm coupled with Raman mapping technique is applied to identify pure spectral profiles of the ingredients in sulfa drug tablets. With the spectral data matrix obtained by Raman mapping and the identified pure spectral variables, one can obtain the matrix of the concentration profiles. Then concentration distribution maps are constructed using the concentration profiles at all pixels. The results obtained with laboratory-manufactured mixtures and commercial pharmaceutical formulations reveal that the proposed technique offers the identification of the two effective ingredients and a qualitative visualization of the spatial distribution of the ingredient identified. This approach was expected to be a promising tool in rapid noninvasive analysis for pharmaceutical production processes such as monitoring the distribution of effective ingredients as well as visualizing the pharmaceutical formulations.Morphology, chemical distribution and domain size in high-density polyethylene/ polyethylene terephthalate (HDPE/PET) polymer blends of various ratios prepared...