Falsification; Near infrared spectroscopy; Raman spectroscopy; DD-SIMCA
Abstract :
[en] Over the last decade, the growth of the global pharmaceutical market has led to an overall increase of substandard and falsified drugs especially on the African market (or emerging countries). Recently, several methods using handheld/portable vibrational spectroscopy have been developed for rapid and on-field drug analysis. The objective of this work was evaluate the performances of various NIR and Raman handheld spectrophotometers in specific brand identification of medicines through their primary packaging. Three groups of drug samples (artemether-lumefantrine, paracetamol, and ibuprofen) were used in tablet or capsule forms. In order to perform a critical comparison, the analytical performances of the two analytical systems was compared statistically using three methods: hierarchical clustering algorithm (HCA), data-driven soft independent modeling of class analogy (DD-SIMCA) and hit quality index (HQI). The overall results show good detection abilities for NIR systems compared to Raman systems based on Matthews’s correlation coefficients, generally close to one. Raman systems are less sensitive to the physical state of the samples than the NIR systems, it also suffers of the auto-fluorescence phenomenon and the signal of highly dosed active pharmaceutical ingredient (e.g. paracetamol or lumefantrine) may mask the signal of low-dosed and weaker Raman active compounds (e.g. artemether). Hence, Raman systems are less effective for specific product identification purposes but are interesting in the context of falsification because they allow a visual interpretation of the spectral signature (presence or absence of API).
Research center :
CIRM - Centre Interdisciplinaire de Recherche sur le Médicament - ULiège
Hubert, Philippe ; Université de Liège - ULiège > Département de pharmacie > Chimie analytique
Ziemons, Eric ; Université de Liège - ULiège > Département de pharmacie > Chimie analytique
✱ These authors have contributed equally to this work.
Language :
English
Title :
Comparing the qualitative performances of handheld NIR and Raman spectrophotometers for the detection of falsified pharmaceutical products
Publication date :
01 September 2019
Journal title :
Talanta
ISSN :
0039-9140
eISSN :
1873-3573
Publisher :
Elsevier, Netherlands
Volume :
202
Pages :
469-478
Peer reviewed :
Peer Reviewed verified by ORBi
Name of the research project :
Vibra4Fake project (convention n°:7517)
Funders :
Académie de Recherche et d'Enseignement Supérieur (Belgique). Coopération au Développement - ARES. CCD Service public de Wallonie : Direction générale opérationnelle de l'économie, de l'emploi et de la recherche - DG06
Tannoury, M., Attieh, Z., The Influence of Emerging Markets on the Pharmaceutical Industry (2017)
Hoen, E.F.M.T., Hogerzeil, H.V., Quick, J.D., Sillo, H.B., A quiet revolution in global public health: the World Health Organization's Prequalification of Medicines Programme (2014) J. Public Health Policy, 35, pp. 137-161
Yao, K., McKinney, B., Murphy, A., Rotz, P., Wafula, W., Sendagire, H., Okui, S., Nkengasong, J.N., Improving quality management systems of laboratories in developing countries (2010) Am. J. Clin. Pathol., 134, pp. 401-409
Caudron, J.M., Ford, N., Henkens, M., Mace, C., Kiddle-Monroe, R., Pinel, J., Substandard medicines in resource-poor settings: a problem that can no longer be ignored (2008) Trop. Med. Int. Health, 13, pp. 1062-1072
(2017) Strengthening Manufacturing Capacity to Improve Access to Quality-Assured Essential Medicines about PQM, , http://www.usp-pqm.org/sites/default/files/pqms/article/manufacturing-final-dec2017.pdf
(2007) Ensuring the Quality of Medicines in Resource-Limited Countries World Health Organization National Drug Authority of Uganda · Program for Appropriate Technology in Health National Pharmaceutical Control Bureau of Malaysia, , National Institute for Drug Qua
Kelesidis, T., Kelesidis, I., Rafailidis, P.I., Falagas, M.E., Counterfeit or substandard antimicrobial drugs: a review of the scientific evidence (2007) J. Antimicrob. Chemother., 60, pp. 214-236
Rebiere, H., Guinot, P., Chauvey, D., Brenier, C., Fighting falsified medicines: the analytical approach (2017) J. Pharm. Biomed. Anal., 142, pp. 286-306
Ludasi, K., Sovány, T., Laczkovich, O., Hopp, B., Smausz, T., Regdon, G., Unique laser coding technology to fight falsified medicines (2018) Eur. J. Pharm. Sci., 123, pp. 1-9
Vickers, S., Bernier, M., Zambrzycki, S., Fernandez, F.M., Newton, P.N., Caillet, C., Field detection devices for screening the quality of medicines: a systematic review (2018) BMJ Glob. Heal., 3
Nayyar, G.M.L., Breman, J.G., Herrington, J.E., The global pandemic of falsified medicines: laboratory and field innovations and policy perspectives (2015) Am. J. Trop. Med. Hyg., 92, pp. 2-7
Kovacs, S., Hawes, S.E., Maley, S.N., Mosites, E., Wong, L., Stergachis, A., Technologies for detecting falsified and substandard drugs in low and middle-income countries (2014) PLoS One, 9
Reich, G., Near-infrared spectroscopy and imaging: Basic principles and pharmaceutical applications (2005) Adv. Drug Deliv. Rev., 57, pp. 1109-1143
Dégardin, K., Guillemain, A., Guerreiro, N.V., Roggo, Y., Near infrared spectroscopy for counterfeit detection using a large database of pharmaceutical tablets (2016) J. Pharm. Biomed. Anal., 128, pp. 89-97
Mbinze, J.K., Sacré, P.-Y., Yemoa, A., Mavar Tayey Mbay, J., Habyalimana, V., Kalenda, N., Hubert, P., Ziemons, E., Development, validation and comparison of NIR and Raman methods for the identification and assay of poor-quality oral quinine drops (2015) J. Pharm. Biomed. Anal., 111, pp. 21-27
Casian, T., Reznek, A., Loredana Vonica-Gligor, A., Van Renterghem, J., De Beer, T., Tomuță, I., Development, Validation and Comparison of Near Infrared and Raman Spectroscopic Methods for Fast Characterization of Tablets with Amlodipine and Valsartan (2017)
Modroño, S., Soldado, A., Martínez-Fernández, A., de la Roza-Delgado, B., Handheld NIRS sensors for routine compound feed quality control: real time analysis and field monitoring (2017) Talanta, 162, pp. 597-603
https://www.europeanpharmaceuticalreview.com/whitepaper/21744/whitepaper-handheld-analyzers-screening-pharmaceutical-counterfeits/, Handheld Analyzers for the Screening of Pharmaceutical Counterfeits
Dégardin, K., Guillemain, A., Roggo, Y., Comprehensive study of a handheld Raman spectrometer for the analysis of counterfeits of solid-dosage form medicines (2017) J. Spectrosc., 2017
Rodionova, O.Y., Balyklova, K.S., Titova, A.V., Pomerantsev, A.L., Application of NIR spectroscopy and chemometrics for revealing of the ‘high quality fakes’ among the medicines (2018) Forensic Chem, 8, pp. 82-89
Neuberger, S., Neusüß, C., Determination of counterfeit medicines by Raman spectroscopy: systematic study based on a large set of model tablets (2015) J. Pharm. Biomed. Anal., 112, pp. 70-78
Rodriguez, J.D., Westenberger, B.J., Buhse, L.F., Kauffman, J.F., Quantitative evaluation of the sensitivity of library-based Raman spectral correlation methods (2011) Anal. Chem., 83, pp. 4061-4067
Lee, S., Lee, H., Chung, H., New discrimination method combining hit quality index based spectral matching and voting (2013) Anal. Chim. Acta, 758, pp. 58-65
Wold, S., Pattern recognition by means of disjoint principal components models (1976) Pattern Recogn., 8, pp. 127-139
Telaar, A., Liland, K.H., Repsilber, D., Nürnberg, G., An extension of PPLS-DA for classification and comparison to ordinary PLS-DA (2013) PLoS One, 8
Pomerantsev, A.L., Rodionova, O.Y., Multiclass partial least squares discriminant analysis: taking the right way-A critical tutorial (2018) J. Chemom.
Westerhuis, J.A., Hoefsloot, H.C.J., Smit, S., Vis, D.J., Smilde, A.K., van Velzen, E.J.J., van Duijnhoven, J.P.M., van Dorsten, F.A., Assessment of PLSDA cross validation (2008) Metabolomics, 4, pp. 81-89
Liland, K.H., Indahl, U.G., Powered partial least squares discriminant analysis (2009) J. Chemom., 23, pp. 7-18
Lee, L.C., Liong, C.-Y., Jemain, A.A., Partial least squares-discriminant analysis (PLS-DA)for classification of high-dimensional (HD)data: a review of contemporary practice strategies and knowledge gaps (2018) Analyst
Rodionova, O.Y., Titova, A.V., Pomerantsev, A.L., Discriminant analysis is an inappropriate method of authentication (2016) TrAC Trends Anal. Chem., 78, pp. 17-22
Oliveri, P., Downey, G., Multivariate class modeling for the verification of food-authenticity claims (2012) TrAC - Trends Anal. Chem., 35, pp. 74-86
Singh, A., Yadav, A., Rana, A., K-means with three different distance metrics (2013) Int. J. Comput. Appl., 67, pp. 13-17
James, G., Witten, D., Hastie, T., Tibshirani, R., An Introduction to Statistical Learning (2013), Springer New York New York, NY
Xu, D., Tian, Y., A comprehensive survey of clustering algorithms (2015) Ann. Data Sci., 2, pp. 165-193
Pérez Ortega, J., Boone Rojas, M.D.R., Somodevilla García, M.J., Research issues on k-means algorithm: An experimental trial using Matlab (2009) CEUR Workshop Proc, pp. 83-96
Rinnan, van den Berg, F., Engelsen, S.B., Review of the most common pre-processing techniques for near-infrared spectra (2009) TrAC Trends Anal. Chem., 28, pp. 1201-1222
Gagolewski, M., Bartoszuk, M., Cena, A., Genie: a new, fast, and outlier-resistant hierarchical clustering algorithm (2016) Inf. Sci. (Ny), 363, pp. 8-23
Aggarwal, C.C., Hinneburg, A., Keim, D.A., On the Surprising Behavior of Distance Metrics in High Dimensional Space (2001), pp. 420-434
Strauss, T., von Maltitz, M.J., Generalising Ward's method for use with manhattan distances (2017) PLoS One, 12
Kauffman, J., Rodriguez, J.D., Buhse, L.F., Spectral preprocessing for raman library searching (2011) Am. Pharm. Rev., 14, pp. 34-40
Rodionova, O.Y., Oliveri, P., Pomerantsev, A.L., Rigorous and compliant approaches to one-class classification (2016) Chemometr. Intell. Lab. Syst., 159, pp. 89-96
Pomerantsev, A.L., Rodionova, O.Y., Concept and role of extreme objects in PCA/SIMCA (2013) J. Chemom., 28. , n/a-n/a
Pomerantsev, A.L., Rodionova, O.Y., On the type II error in SIMCA method (2014) J. Chemom., 28, pp. 518-522
Zontov, Y.V., Rodionova, O.Y., Kucheryavskiy, S.V., Pomerantsev, A.L., DD-SIMCA — a MATLAB GUI tool for data driven SIMCA approach (2017) Chemometr. Intell. Lab. Syst., 167, pp. 23-28
Boughorbel, S., Jarray, F., El-Anbari, M., Optimal classifier for imbalanced data using Matthews Correlation Coefficient metric (2017) PLoS One, 12, pp. 1-17
Scafi, S.H.F., Pasquini, C., Identification of counterfeit drugs using near-infrared spectroscopy (2001) Analyst, 126, pp. 2218-2224
Deidda, R., Sacre, P.-Y., Clavaud, M., Coïc, L., Avohou, H., Hubert, P., Ziemons, E., Vibrational spectroscopy in analysis of pharmaceuticals: critical review of innovative portable and handheld NIR and Raman spectrophotometers (2019) TrAC Trends Anal. Chem., 114, pp. 251-259
