Profiling of counterfeit medicines by vibrational spectroscopy

Détails

ID Serval
serval:BIB_8715B21B8173
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Profiling of counterfeit medicines by vibrational spectroscopy
Périodique
Forensic Science International
Auteur(s)
Béen F., Roggo Y., Degardin K., Esseiva P., Margot P.
ISSN
1872-6283
Statut éditorial
Publié
Date de publication
09/2011
Peer-reviewed
Oui
Volume
211
Numéro
1-3
Pages
83-100
Langue
anglais
Résumé
Counterfeit pharmaceutical products have become a widespread problem in the last decade. Various analytical techniques have been applied to discriminate between genuine and counterfeit products. Among these, Near-infrared (NIR) and Raman spectroscopy provided promising results.The present study offers a methodology allowing to provide more valuable information fororganisations engaged in the fight against counterfeiting of medicines.A database was established by analyzing counterfeits of a particular pharmaceutical product using Near-infrared (NIR) and Raman spectroscopy. Unsupervised chemometric techniques (i.e. principal component analysis - PCA and hierarchical cluster analysis - HCA) were implemented to identify the classes within the datasets. Gas Chromatography coupled to Mass Spectrometry (GC-MS) and Fourier Transform Infrared Spectroscopy (FT-IR) were used to determine the number of different chemical profiles within the counterfeits. A comparison with the classes established by NIR and Raman spectroscopy allowed to evaluate the discriminating power provided by these techniques. Supervised classifiers (i.e. k-Nearest Neighbors, Partial Least Squares Discriminant Analysis, Probabilistic Neural Networks and Counterpropagation Artificial Neural Networks) were applied on the acquired NIR and Raman spectra and the results were compared to the ones provided by the unsupervised classifiers.The retained strategy for routine applications, founded on the classes identified by NIR and Raman spectroscopy, uses a classification algorithm based on distance measures and Receiver Operating Characteristics (ROC) curves. The model is able to compare the spectrum of a new counterfeit with that of previously analyzed products and to determine if a new specimen belongs to one of the existing classes, consequently allowing to establish a link with other counterfeits of the database.
Mots-clé
Counterfeit, Forensic science, Profiling, NIR, Raman, Chemometrics, Forensic intelligence
Pubmed
Web of science
Création de la notice
27/06/2011 9:47
Dernière modification de la notice
03/03/2018 19:00
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