Literature DB >> 22464559

Non-destructive detection of adulterated tablets of glibenclamide using NIR and solid-phase fluorescence spectroscopy and chemometric methods.

Rafael da Silva Fernandes1, Fernanda Saadna Lopes da Costa, Patrícia Valderrama, Paulo Henrique Março, Kássio Michell Gomes de Lima.   

Abstract

This study describes a method for non-destructive detection of adulterated glibenclamide tablets. This method uses near infrared spectroscopy (NIRS) and fluorescence spectroscopy along with chemometric tools such as Soft Independent Modeling of Class Analogy (SIMCA), Partial Least Squares-Discriminant Analysis (PLS-DA) and Unfolded Partial Least Squares with Discriminant Analysis (UPLS-DA). Both brand name (Daonil) and generic glibenclamide tablets were used for analysis. The levels of glibenclamide in each type of tablet were evaluated by derivative spectrophotometry in the ultraviolet region. The results obtained from the NIR and fluorescence spectroscopy along with those obtained from multivariate data classification show that this combined technique is an effective way to detect adulteration in drugs for the treatment of diabetes. In the future, this method may be extended to detect different types of counterfeit medications.
Copyright © 2012 Elsevier B.V. All rights reserved.

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Year:  2012        PMID: 22464559     DOI: 10.1016/j.jpba.2012.03.004

Source DB:  PubMed          Journal:  J Pharm Biomed Anal        ISSN: 0731-7085            Impact factor:   3.935


  3 in total

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Authors:  Stephanie Kovacs; Stephen E Hawes; Stephen N Maley; Emily Mosites; Ling Wong; Andy Stergachis
Journal:  PLoS One       Date:  2014-03-26       Impact factor: 3.240

Review 2.  Chemometric Methods for Spectroscopy-Based Pharmaceutical Analysis.

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

Review 3.  A Review of Pharmaceutical Robot based on Hyperspectral Technology.

Authors:  Xuesan Su; Yaonan Wang; Jianxu Mao; Yurong Chen; ATing Yin; Bingrui Zhao; Hui Zhang; Min Liu
Journal:  J Intell Robot Syst       Date:  2022-07-22       Impact factor: 3.129

  3 in total

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