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DSC FTIR and Raman Spectroscopy Coupled with Multivariate Analysis in a Study of Co-Crystals of Pharmaceutical Interest

机译:DSCFTIR和拉曼光谱与多元分析相结合研究药物共晶体

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摘要

Co-crystals have garnered increasing interest in recent years as a beneficial approach to improving the solubility of poorly water soluble active pharmaceutical ingredients (APIs). However, their preparation is a challenge that requires a simple approach towards co-crystal detection. The objective of this work was, therefore, to verify to what extent a multivariate statistical approach such as principal component analysis (PCA) and cluster analysis (CA) can be used as a supporting tool for detecting co-crystal formation. As model samples, physical mixtures and co-crystals of indomethacin with saccharin and furosemide with p-aminobenzoic acid were prepared at API/co-former molar ratios 1:1, 2:1 and 1:2. Data acquired from DSC curves and FTIR and Raman spectroscopies were used for CA and PCA calculations. The results obtained revealed that the application of physical mixtures as reference samples allows a deeper insight into co-crystallization than is possible with the use of API and co-former or API and co-former with physical mixtures. Thus, multivariate matrix for PCA and CA calculations consisting of physical mixtures and potential co-crystals could be considered as the most profitable and reliable way to reflect changes in samples after co-crystallization. Moreover, complementary interpretation of results obtained using DSC, FTIR and Raman techniques is most beneficial.
机译:作为改善水溶性差的活性药物成分(API)溶解度的有益方法,近年来,共晶体越来越受到关注。但是,它们的制备是一个挑战,需要采用简单的方法进行共晶体检测。因此,这项工作的目的是验证多变量统计方法(例如主成分分析(PCA)和聚类分析(CA))可以在多大程度上用作检测共晶形成的支持工具。作为模型样品,制备了吲哚美辛与糖精和速尿与对氨基苯甲酸的物理混合物和共晶体,原料药/共形成剂的摩尔比为1:1、2:1和1:2。从DSC曲线以及FTIR和拉曼光谱学获得的数据用于CA和PCA计算。所获得的结果表明,与使用API​​和助成型剂或API和助成型剂与物理混合物相比,使用物理混合物作为参考样品可以更深入地了解共结晶。因此,用于PCA和CA计算的多元矩阵由物理混合物和潜在的共晶体组成,被认为是反映共结晶后样品变化的最有利和最可靠的方法。此外,使用DSC,FTIR和拉曼技术获得的结果的互补解释是最有益的。

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