Pattern recognition methods as supplementary techniques for identification of salicylamide — cyclodextrins inclusion complexes

Abstract

AbstractThe objective of this study was to learn whether or not the pattern recognition methods, such as agglomerative cluster analysis (CA) and principal component analysis (PCA), can be used as supplementary techniques for identification of salicylamide (SAA) inclusion complexes with β-cyclodextrin (β-CD) and 2-hydroxypropyl-β-cyclodextrin (HP-β-CD). To do this, phase-solubility of SAA in the presence of the cyclodextrins was studied by the Higuchi-Connors method, which showed that the cyclodextrins enhanced the solubility of SAA in water as compared to that of the drug. Next, the solid phase complexes of the drug with β-CD and HP-β-CD were prepared by using the coprecipitation, precipitation-evaporation, and kneading methods. Identification of the inclusion complexes was performed by using thermal analysis, infrared spectroscopy, and wide angle X-ray scattering. Two multivariate statistical methods, CA and PCA, were used as the supplementary techniques for identification of the inclusion complexes. The results of the statistical analysis have shown that CA and PCA are helpful for interpretation of the thermoanalytical and spectral data. Moreover, these methods enabled proper classification of the products in all doubtful cases. They can be used as supplementary techniques to verify the conclusions of the above-mentioned standard methods.