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RAMAN SUPPLEMENT


FIGURE 7 Chemical classification of 30 counterfeits’ seizures. Several hierarchical levels of classification could be determined. Thesewere built on Raman classes coupled with other variables such as API impurity profile and physical characteristics of the capsules


The interpretation of Raman spectra


constitutes a quick and efficient way of determining the major compounds constituting counterfeits. This can be used for the evaluation of the hazard while providing information for forensic investigation about the case.


Forensic investigation of counterfeits Raman spectroscopy presents an interesting chemical selectivity and generates repeatable profiles. In association with chemometrics, it represents an interesting tool for the chemical profiling of counterfeits. This is illustrated in Figure 1 (page 4) as the third step of counterfeits’ analysis. This step consists in classifying counterfeits


following their chemical content so that potential links between the seizures can be made. Chemical classifications of counterfeits should consequently lead to additional information for law enforcement investigators, especially if combined with seizure or packaging


REFERENCES


1. SafeMedicines, Counterfeit Drug Incident Encyclopedia. Partnership for Safe Medicines, 2009. http://www.safemedicines.org/counterfeit-drug- incident-encyclopedia.html (Accessed 30 May 2011)


2. Primo-Carpenter, J., McGinnis, M., Matrix of Drug Quality Reports on USAID-assisted Countries by the USP Drug Quality and Information Program. The USP Convention Inc., Rockville, 2009


3. Seiter, A., Health and Economic Consequences of Counterfeit Drugs. Clinical Pharmacology and Therapeutics, 2009. 85(6): p. 576-578


4. Harris, J., Stevens, P., Morris, J., Keeping It Real. Combating the Spread of Fake Drugs in Poor Countries. International Policy Network, 2009. http://www.africanliberty.org/pdf/Keepingitreal.pdf (Accessed 30 May 2011)


5. Wertheimer, A.I., Norris, J., Safeguarding Against Substandard/Counterfeit Drugs: Mitigating a Macroeconomic Pandemic. Research in Social and Administrative Pharmacy, 2009. 5(1): p. 4-16


6. Bobée, J.M., How Can Technology Help to Fight Counterfeits? World Intellectual Property Organization Magazine, 2009. September 2009


7. Gaudiano, M.C., Di Maggio, A., Antoniella, E., Valvo, L., 08


European Pharmaceutical Review Volume 16 | Issue 5 | 2011


Bertocchi, P., Manna, L., Bartolomei, M., Alimonti, S., Rodomonte, A. L., An LC Method for the Simultaneous Screening of Some Common Counterfeit and Sub- standard Antibiotics: Validation and Uncertainty Estimation. J. of Pharma. and Biom. Ana., 2008. 48(2): p. 303-309


8. Nyadong, L., Hohenstein, E.G., Johnson, K., Sherrill, C. D., Green, M.D., Fernandez, F.M., Desorption Electrospray Ionization Reactions Between Host Crown Ethers and the Influenza Neuraminidase Inhibitor Oseltamivir for the Rapid Screening of Tamiflu®. Analyst, 2008. 133(11): p. 1513 – 1522


9. Dowell, F.E., Maghirang, E. B., Fernandez, F. M., Newton, P.N., Green, M. D., Detecting Counterfeit Antimalarial Tablets by Near-infrared Spectroscopy. J. of Pharma. and Biom. Ana., 2008. 48(3): p. 1011-1014


10. Roggo, Y., Degardin, K., Margot, P., Identification of Pharmaceutical Tablets by Raman Spectroscopy and Chemometrics. Talanta, 2010. 81(3): p. 988-995


11. United States Pharmacopoeia, U.S.P., Raman Spectrophotometry, Qualitative Analysis. 2009. 31(Chapter <1120>)


12. Dégardin, K., Roggo, Y., Margot, P., Evaluation de spectromètres portables Raman, Infrarouge et Proche


Infrarouge pour la détection de contrefaçons de médicaments. Spectra Analyse, 2010. 276: p. 46-52


13. Ricci, C., Nyadong, L., Yang, F., Fernandez, F.M., Brown, C.D., Newton, P.N., Kazarian, S.G., Assessment of Hand- held Raman Instrumentation for in Situ Screening for Potentially Counterfeit Artesunate Antimalarial Tablets by FT-Raman Spectroscopy and Direct Ionization mass spectrometry. Ana. Chim. Acta, 2008. 623(2): p. 178-186


14. Eglovitch, S.J., Drug Manufacturers Find They Must Trust But Verify Anti-Counterfeting Methods. The Gold Sheet, 2009. November 2009: p. 6-11


15. Ricci, C., Eliasson, C., Macleod, N., Newton, P., Matousek, P., Kazarian, S., Characterization of Genuine and Fake Artesunate Anti-malarial Tablets Using Fourier Transform Infrared Imaging and Spatially Offset Raman Spectroscopy Through Blister Packs. Ana. and Bioana. Chem., 2007. 389(5): p. 1525-1532


16. De Veij, M., Deneckere, A., Vandenabeele, P., de Kaste, D. and L. Moens, Detection of Counterfeit Viagra® with Raman Spectroscopy. J. of Pharma. and Biom. Ana., 2008. 46(2): p. 303-309


17. Been, F., Roggo, Y., Dégardin, K., Esseiva, P., Margot, P., Profiling of Counterfeit Medicines by Vibrational Spectroscopy. Forensic Science International, 2011 In Press


serious criminal issue that requires fast and efficient decisions and repercussions for the criminals”


“Medicine counterfeiting is a


information. The aim is to bring a new type of information that would facilitate the sourcing of future counterfeits. The analysis of chemical links could subsequently enable the understanding of the manufacturing of counterfeits, such as the rate of production of a chemical batch, its size or distribution. The method presented as an example uses


primarily PCA for classification with Raman spectroscopy17


. A PCA was applied on the


spectra of the counterfeits to determine underlying classes within the seizures. Fifteen Raman classes could be observed among the historical counterfeits (Figure 6, page 7). If a new


case of counterfeit occurs, the product is classified within the database so that potential links with former counterfeits can be made. The chemical profiling of counterfeits using


Raman spectroscopy is one of the steps to establish chemical links between seizures. Other variables have to be studied in order to complete this classification scheme. In the present case, they consisted of impurity profiles of APIs or physical characteristics of the counterfeits. The association of the results of these variables can then lead to relations between the different seizures, as observed in Figure 7. Several levels of linking could be found


between the seizures, such as the same impurity profile, i.e. allegedly same source, of API. The different chemical classes would represent the different variations of recipes of counterfeits. Finally, chemical subgroups or types of chemical subgroups would group the same production batches. On the whole, almost all the seizures


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