Literature DB >> 24632161

Identification of anisodamine tablets by Raman and near-infrared spectroscopy with chemometrics.

Lian Li1, Hengchang Zang1, Jun Li2, Dejun Chen2, Tao Li2, Fengshan Wang3.   

Abstract

Vibrational spectroscopy including Raman and near-infrared (NIR) spectroscopy has become an attractive tool for pharmaceutical analysis. In this study, effective calibration models for the identification of anisodamine tablet and its counterfeit and the distinguishment of manufacturing plants, based on Raman and NIR spectroscopy, were built, respectively. Anisodamine counterfeit tablets were identified by Raman spectroscopy with correlation coefficient method, and the results showed that the predictive accuracy was 100%. The genuine anisodamine tablets from 5 different manufacturing plants were distinguished by NIR spectroscopy using partial least squares discriminant analysis (PLS-DA) models based on interval principal component analysis (iPCA) method. And the results showed the recognition rate and rejection rate were 100% respectively. In conclusion, Raman spectroscopy and NIR spectroscopy combined with chemometrics are feasible and potential tools for rapid pharmaceutical tablet discrimination.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Chemometrics; Identification of anisodamine tablet; Near-infrared spectroscopy; Raman spectroscopy

Mesh:

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Year:  2014        PMID: 24632161     DOI: 10.1016/j.saa.2014.02.022

Source DB:  PubMed          Journal:  Spectrochim Acta A Mol Biomol Spectrosc        ISSN: 1386-1425            Impact factor:   4.098


  2 in total

Review 1.  Chemometric Methods for Spectroscopy-Based Pharmaceutical Analysis.

Authors:  Alessandra Biancolillo; Federico Marini
Journal:  Front Chem       Date:  2018-11-21       Impact factor: 5.221

Review 2.  Vibrational Spectroscopy in Assessment of Early Osteoarthritis-A Narrative Review.

Authors:  Chen Yu; Bing Zhao; Yan Li; Hengchang Zang; Lian Li
Journal:  Int J Mol Sci       Date:  2021-05-15       Impact factor: 5.923

  2 in total

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