Classification and Quantitative Analysis of Azithromycin Tablets by Raman Spectroscopy and Chemometrics

Yan Li, Guorong Du, Wensheng Cai, Xueguang Shao

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DOI: 10.4236/ajac.2011.22015                

Abstract

Raman spectroscopy has been proven a noninvasive technique with high potential in pharmaceutical industry. In this study, micro Raman technique and chemometric tools were used for identification of azithromycin (AZM) tablets by different manufacturers and quantitative analysis of the active pharmaceutical ingredient (API) in the samples. Support vector machine (SVM), Bayes classifier and K-nearest neighbour (KNN) were employed for identification, partial least squares (PLS) regression was used for quantitative determination, and interval partial least squares (iPLS) and Monte Carlo based uninformative variable elimination (MC-UVE) methods were used to select informative variables for improving the models. The results show that all the samples can be classified into groups by manufacturers with high accuracy, and the correlation coefficient between the predicted API concentrations and reference values is as high as 0.96. Therefore, micro Raman spectroscopy coupled with chemometrics may be a fast and powerful tool for identification and quantitative determination of pharmaceutical tablets.

Keywords

Azithromycin, Raman spectroscopy, Pharmaceutical tablets, Variable selection, Partial least squares (PLS)

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	K. A. Shaikh, S. D. Patil and A. B. Devkhile, “Development and Validation of a Reversed-Phase HPLC Method for Simultaneous Estimation of Ambroxol Hydrochloride and Azithromycin in Tablet Dosage Form,” Journal of Pharmaceutical and Biomedical Analysis, Vol. 48, No. 5, 2008, pp. 1481-1484. doi:10.1016/j.jpba.2008.09.031
[2]	C. Gendrin, Y. Roggo and C. Collet, “Pharmaceutical Applications of Vibrational Chemical Imaging and Chemometrics: A Review,” Journal of Pharmaceutical and Biomedical Analysis, Vol. 48, No. 3-4, 2008, pp. 533-553. doi:10.1016/j.jpba.2008.08.014
[3]	S. H. F. Scafi and C. Pasquini, “Identification of Counterfeit Drugs Using Near-Infrared Spectroscopy,” Analyst, Vol. 126, No. 12, 2001, pp. 2218-2224. doi:10.1039/b106744n
[4]	S. E. J. Bell, D. T. Burns, A. C. Dennis, L. J. Matchett and J. S. Speers, “Composition Profiling of Seized Ecstasy Tablets by Raman Spectroscopy,” Analyst, Vol. 125, No. 10, 2000, pp. 1811-1815. doi:10.1039/b005662f
[5]	T. Okumura and M. Otsuka, “Evaluation of the Microcrystallinity of a Drug Substance, Indomethacin, in a Pharmaceutical Model Tablet by Chemometric FT-Raman Spectroscopy,” Pharmaceutical Research, Vol. 22, No. 8, 2005, pp. 1350-1357. doi:10.1007/s11095-005-5281-9
[6]	M. S. Hwang, S. Cho, H. Chung and Y. A. Woo, “Nondestructive Determination of the Ambroxol Content in Tablets by Raman Spectroscopy,” Journal of Pharmaceutical and Biomedical Analysis, Vol. 38, No. 2, 2005, pp. 210-215. doi:10.1016/j.jpba.2004.12.031
[7]	M. Dyrby, S. B. Engelsen, L. Norgaard, M. Bruhn and L. Lundsberg-Nielsen, “Chemometric Quantitation of the Active Substance (Containing C ? N) in a Pharmaceutical Tablet Using Near-Infrared (NIR) Transmittance and NIR FT-Raman Spectra,” Applied Spectroscopy, Vol. 56, No. 5, 2002, pp. 579-585. doi:10.1366/0003702021955358
[8]	S. Sasic, “An In-Depth Analysis of Raman and Near-In- frared Chemical Images of Common Pharmaceutical Tablets,” Applied Spectroscopy, Vol. 61, No. 3, 2007, pp. 239-250. doi:10.1366/000370207780220769
[9]	S. E. J. Bell, L. A. Fido, N. M. S. Sirimuthu, S. J. Speers, K. L. Peters and S. H. Cosbey, “Screening Tablets for DOB Using Surface-Enhanced Raman Spectroscopy,” Journal of Forensic Sciences, Vol. 52, No. 5, 2007, pp. 1063-1067. doi:10.1111/j.1556-4029.2007.00515.x
[10]	C. Ricci, C. Eliasson, N. A. Macleod, P. N. Newton, P. Matousek and S. G. Kazarian, “Characterization of Genuine and Fake Artesunate Anti-Malarial Tablets Using Fourier Transform Infrared Imaging and Spatially Offset Raman Spectroscopy Through Blister Packs,” Analytical and Bioanalytical Chemistry, Vol. 389, No. 5, 2007, pp. 1525-1532. doi:10.1007/s00216-007-1543-1
[11]	C. Ricci, L. Nyadong, F. Yang, F. M. Fernandez, C. D. Brown, P. N. Newton and S. G. Kazarian, “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,” Analytica Chimica Acta, Vol. 623, No. 2, 2008, pp. 178-186. doi:10.1016/j.aca.2008.06.007
[12]	C. Eliasson and P. Matousek, “Noninvasive Authentication of Pharmaceutical Products Through Packaging Using Spatially Offset Raman Spectroscopy,” Analytical Chemistry, Vol. 79, No. 4, 2007, pp. 1696-1701. doi:10.1021/ac062223z
[13]	P. Matousek and A. W. Parker, “Bulk Raman Analysis of Pharmaceutical Tablets,” Applied Spectroscopy, Vol. 60, No. 12, 2006, pp. 1353-1357. doi:10.1366/000370206779321463
[14]	R. B. Shah, M. A. Tawakkul and M. A. Khan, “Process Analytical Technology: Chemometric Analysis of Raman And Near Infrared Spectroscopic Data for Predicting Physical Properties of Extended Release Matrix Tablets,” Journal of Pharmaceutical Sciences, Vol. 96, No. 5, 2007, pp. 1356-1365. doi:10.1002/jps.20931
[15]	M. de Veij, P. Vandenabeele, K. A. Hall, F. M. Fernandez, M. D. Green, N. J. White, A. M. Dondorp, P. N. Newton and L. Moens, “Fast Detection and Identification of Counterfeit Antimalarial Tablets by Raman Spectroscopy,” Journal of Raman Spectroscopy, Vol. 38, No. 2, 2007, pp. 181-187. doi:10.1002/jrs.1621
[16]	Y. Roggo, K. Degardin and P. Margot, “Identification of Pharmaceutical Tablets by Raman Spectroscopy and Che- mometrics,” Talanta, Vol. 81, No. 3, 2010, pp. 988-995. doi:10.1016/j.talanta.2010.01.046
[17]	L. Zhang, M. J. Henson and S. S. Sekulic, “Multivariate Data Analysis for Raman Imaging of a Model Pharmaceutical Tablet,” Analytica Chimica Acta, Vol. 545, No. 2, 2005, pp. 262-278. doi:10.1016/j.aca.2005.04.080
[18]	P. de Peinder, M. J. Vredenbregt, T. Visser and D. de Kaste, “Detection of Lipitor (R) Counterfeits: A Comparison of NIR And Raman Spectroscopy in Combination with Chemometrics,” Journal of Pharmaceutical and Biomedical Analysis, Vol. 47, No. 4-5, 2008, pp. 688-694. doi:10.1016/j.jpba.2008.02.016
[19]	R. Szostak and S. Mazurek, “FT-Raman Quantitative Determination of Ambroxol in Tablets,” Journal of Molecular Structure, Vol. 704, No. 1-3, 2004, pp. 229-233. doi:10.1016/j.molstruc.2004.01.057
[20]	J. Johansson, A. Sparen, O. Svensson, S. Folestad and M. Claybourn, “Quantitative Transmission Raman Spectroscopy of Pharmaceutical Tablets and Capsule,” Applied Spectroscopy, Vol. 61, No. 11, 2007, pp. 1211-1218. doi:10.1366/000370207782597085
[21]	R. Szostak and S. Mazurek, “Quantitative Determination of Acetylsalicylic Acid and Acetaminophen in Tablets by FT-Raman Spectroscopy,” Analyst, Vol. 127, No. 1, 2002, pp. 144-148. doi:10.1039/b108240j
[22]	S. Mazurek and R. Szostak, “Quantification of Atorvastatin Calcium in Tablets by FT-Raman Spectroscopy,” Journal of Pharmaceutical and Biomedical Analysis, Vol. 49, No. 1, 2009, pp. 168-172. doi:10.1016/j.jpba.2008.10.015
[23]	S. Mazurek and R. Szostak, “Quantitative Determination of Captopril and Prednisolone in Tablets by FT-Raman Spectroscopy,” Journal of Pharmaceutical and Biomedical Analysis, Vol. 40, No. 5, 2006, pp. 1225-1230. doi:10.1016/j.jpba.2005.03.047
[24]	S. Mazurek and R. Szostak, “Quantitative Determination of Diclofenac Sodium in Solid Dosage Forms by FT-Raman Spectroscopy,” Journal of Pharmaceutical and Biomedical Analysis, Vol. 48, No. 3, 2008, pp. 814-821. doi:10.1016/j.jpba.2008.08.013
[25]	H. Sun, “A Naive Bayes Classifier for Prediction of Multidrug Resistance Reversal Activity on the Basis of Atom typing,” Journal of Medicinal Chemistry, Vol. 48, No. 12, 2005, pp. 4031-4039. doi:10.1021/jm050180t
[26]	K. C. Chou and H. B. Shen, “Predicting Eukaryotic Protein Subcellular Location by Fusing Optimized Evidence-Theoretic K-Nearest Neighbor Classifiers,” Journal of Proteome Research, Vol. 5, No. 8, 2006, pp. 1888-1897. doi:10.1021/pr060167c
[27]	U. Schmid, P. Rosch, M. Krause, M. Harz, J. Popp and K. Baumann, “Gaussian Mixture Discriminant Analysis for the Single-Cell Differentiation of Bacteria Using Micro-Raman Spectroscopy,” Chemometrics and Intelligent Laboratory Systems, Vol. 96, No. 2, 2009, pp. 159-171. doi:10.1016/j.chemolab.2009.01.008
[28]	R. Karchin, K. Karplus and D. Haussler, “Classifying G- protein Coupled Receptors with Support Vector Machines,” Bioinformatics, Vol. 18, No. 1, 2002, pp. 147-159. doi:10.1093/bioinformatics/18.1.147
[29]	S. Zomer, R. G. Brereton, J. F. Carter and C. Eckers, “Support Vector Machines for the Discrimination of Analytical Chemical Data: Application to the Determination of Tablet Production by Pyrolysis-Gas Chromatography-Mass Spectrometry,” Analyst, Vol. 129, No. 2, 2004, pp. 175-181. doi:10.1039/b312982a
[30]	C. D. Natale, A. Macagnano, E. Martinelli, R. Paolesse, G. D'Arcangelo, C. Roscioni, A. Finazzi-Agro and A. D'Amico, “Lung Cancer Identification by the Analysis of Breath by Means of an Array of Non-Selective Gas Sensors,” Biosensors and Bioelectronics, Vol. 18, No. 10, 2003, pp. 1209-1218. doi:10.1016/S0956-5663(03)00086-1
[31]	S. Bijlsma, L. Bobeldijk, E. R. Verheij, R. Ramaker, S. Kochhar, I. A. Macdonald, B. van Ommen and A. K. Smilde, “Large-Scale Human Metabolomics Studies: A Strategy For Data (Pre-) Processing And Validation,” Analytical Chemistry, Vol. 78, No. 2, 2006, pp. 567-574. doi:10.1021/ac051495j
[32]	R. W. Kennard and L. A. Stone, “Computer Aided Design of Experiments,” Technometrics, Vol. 11, 1969, pp. 137-148. doi:10.2307/1266770
[33]	L. Norgaard, A. Saudland, J. Wagner, J. P. Nielsen, L. Munck and S. B. Engelsen, “Interval Partial Least-Squares Regression (iPLS): A Comparative Chemometric Study with an Example from Near-Infrared Spectroscopy,” Applied Spectroscopy, Vol. 54, No. 3, 2000, pp. 413-419. doi:10.1366/0003702001949500
[34]	C. Abrahamsson, J. Johansson, A. Sparen and F. Lindg- ren, “Comparison of Different Variable Selection Methods Conducted on NIR Transmission Measurements on Intact Tablets,” Chemometrics and Intelligent Laboratory Systems, Vol. 69, No. 1, 2003, pp. 3-12. doi:10.1016/S0169-7439(03)00064-9
[35]	X. B. Zou, J. W. Zhao, M. J. W. Povey, M. Holmes and H. P. Mao, “Variables Selection Methods in Near-Infrared Spectroscopy,” Analytica Chimca Acta, Vol. 667, No. 1, 2010, pp. 14-32.doi:10.1016/j.aca.2010.03.048
[36]	W. S. Cai, Y. K. Li and X. G. Shao, “A Variable Selection Method Based on Uninformative Variable Elimination for Multivariate Calibration of Near-Infrared Spectra,” Chemometrics and Intelligent Laboratory Systems, Vol. 90, No. 2, 2008, pp. 188-194. doi:10.1016/j.chemolab.2007.10.001
[37]	H. Xu, Z. C. Liu, W. S. Cai and X. G. Shao, “A WaveLength Selection Method Based on Randomization Test for Near-Infrared Spectral Analysis,” Chemometrics and Intelligent Laboratory Systems, Vol. 97, No. 2, 2009, pp. 189-193. doi:10.1016/j.chemolab.2009.04.006
[38]	P. Vandenabeele, B. Wehling, L. Moens, H. Edwards, M. De Reu and G. Van Hooydonk, “Analysis with Micro-Raman Spectroscopy of Natural Organic Binding Media and Varnishes Used in Art,” Analytica Chimica Acta, Vol. 407, No. 1-2, 2000, pp. 261-274. doi:10.1016/S0003-2670(99)00827-2
[39]	J. De Gelder, K. De Gussem, P. Vandenabeele and L. Moens, “Reference Database of Raman Spectra of Biological Molecules,” Journal of Raman Spectroscopy, Vol. 38, No. 9, 2007, pp. 1133-1147. doi:10.1002/jrs.1734
[40]	M. de Veij, P. Vandenabeele, T. De Beer, J. P. Remon and L. Moens, “Reference Database of Raman Spectra of Pharmaceutical Excipients,” Journal of Raman Spectroscopy, Vol. 40, No. 3, 2009, pp. 297-307. doi:10.1002/jrs.2125