Journal of Innovative Optical Health Sciences, 2016, 9 (6): 1650002, Published Online: Dec. 27, 2018  

Near-infrared chemical imaging for quantitative analysis of chlorpheniramine maleate and distribution homogeneity assessment in pharmaceutical formulations

Manfei Xu 1,2,3,4Luwei Zhou 1,2,3,4Qiao Zhang 1,2,3,4Zhisheng Wu 1,2,3,4,*Xinyuan Shi 1,2,3,4Yanjiang Qiao 1,2,3,4
Author Affiliations
1 Beijing University of Chinese Medicine, P. R. China 100102
2 Pharmaceutical Engineering and New Drug Development of Traditional Chinese Medicine (TCM) of Ministry of Education, P. R. China 100102
3 Key Laboratory of TCM-information Engineering of State Administration of TCM Beijing, P. R. China 100102
4 Beijing Key Laboratory for Basic and Development Research on Chinese Medicine Beijing, P. R. China 100102
Abstract
Near infrared chemical imaging (NIR-CI) combines conventional near infrared (NIR) spectroscopy with chemical imaging, thus provides spectral and spatial information simultaneously. It could be utilized to visualize the spatial distribution of the ingredients in a sample. The data acquired using NIR-CI instrument are hyperspectral data cube (hypercube) containing thousands of spectra. Chemometric methodologies are necessary to transform spectral information into chemical information. Partial least squares (PLS) method was performed to extract chemical information of chlorpheniramine maleate in pharmaceutical formulations. A series of samples which consisted of different CPM concentrations (w/w) were compressed and hypercube data were measured. The spectra extracted from the hypercube were used to establish the PLS model of CPM. The results of the model were R2val0.981, RMSEC 0.384%, RMSECV 0.483%, RMSEP 0.631%, indicating that this model was reliable.

Manfei Xu, Luwei Zhou, Qiao Zhang, Zhisheng Wu, Xinyuan Shi, Yanjiang Qiao. Near-infrared chemical imaging for quantitative analysis of chlorpheniramine maleate and distribution homogeneity assessment in pharmaceutical formulations[J]. Journal of Innovative Optical Health Sciences, 2016, 9(6): 1650002.

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