Testing of complementarity of PDA and MS detectors using chromatographic fingerprinting of genuine and counterfeit samples containing sildenafil citrate

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• 作者：Deborah Custers ; Barbara Krakowska…
• 关键词：Counterfeit medicines ; Viagra® ; Chemometrics ; High ; performance liquid chromatography ; Photodiode array detection ; Mass spectrometry
• 刊名：Analytical and Bioanalytical Chemistry
• 出版年：2016
• 出版时间：February 2016
• 年：2016
• 卷：408
• 期：6
• 页码：1643-1656
• 全文大小：971 KB
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• 作者单位：Deborah Custers (1) (2)
  Barbara Krakowska (3)
  Jacques O. De Beer (1)
  Patricia Courselle (1)
  Michal Daszykowski (3)
  Sandra Apers (2)
  Eric Deconinck (1)
  
  1. Division of Food, Medicines and Consumer Safety, Section Medicinal Products, Scientific Institute of Public Health (WIV-ISP), J. Wytsmanstraat 14, 1050, Brussels, Belgium
  2. Research group NatuRA (Natural products and Food - Research and Analysis), Department of Pharmaceutical Sciences, University of Antwerp, Universiteitsplein 1, 2610, Wilrijk, Belgium
  3. Institute of Chemistry, University of Silesia, 9 Szkolna Street, 40-006, Katowice, Poland
  
• 刊物类别：Chemistry and Materials Science
• 刊物主题：Chemistry
  Analytical Chemistry
  Food Science
  Inorganic Chemistry
  Physical Chemistry
  Monitoring, Environmental Analysis and Environmental Ecotoxicology
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1618-2650

文摘

Counterfeit medicines are a global threat to public health. High amounts enter the European market, which is why characterization of these products is a very important issue. In this study, a high-performance liquid chromatography–photodiode array (HPLC-PDA) and high-performance liquid chromatography–mass spectrometry (HPLC-MS) method were developed for the analysis of genuine Viagra®, generic products of Viagra®, and counterfeit samples in order to obtain different types of fingerprints. These data were included in the chemometric data analysis, aiming to test whether PDA and MS are complementary detection techniques. The MS data comprise both MS1 and MS2 fingerprints; the PDA data consist of fingerprints measured at three different wavelengths, i.e., 254, 270, and 290 nm, and all possible combinations of these wavelengths. First, it was verified if both groups of fingerprints can discriminate between genuine, generic, and counterfeit medicines separately; next, it was studied if the obtained results could be ameliorated by combining both fingerprint types. This data analysis showed that MS1 does not provide suitable classification models since several genuines and generics are classified as counterfeits and vice versa. However, when analyzing the MS1_MS2 data in combination with partial least squares-discriminant analysis (PLS-DA), a perfect discrimination was obtained. When only using data measured at 254 nm, good classification models can be obtained by k nearest neighbors (kNN) and soft independent modelling of class analogy (SIMCA), which might be interesting for the characterization of counterfeit drugs in developing countries. However, in general, the combination of PDA and MS data (254 nm_MS1) is preferred due to less classification errors between the genuines/generics and counterfeits compared to PDA and MS data separately.