Drug expiration study using Raman spectroscopy and super paramagnetic clustering

Authors

  • J. I. Gu´ızar-Ruiz Centro Universitario de los Lagos, Universidad de Guadalajara
  • E. Anaya-Martin Centro Universitario de los Lagos, Universidad de Guadalajara
  • J. L. González-Solís Centro Universitario de los Lagos, Universidad de Guadalajara https://orcid.org/0000-0002-2144-8651

DOI:

https://doi.org/10.31349/RevMexFis.70.061302

Keywords:

Drugs Expiration, Raman Spectroscopy, Super Paramagnetic Clustering, PCA

Abstract

Currently, there is a belief that drugs used after the expiration date no longer work, or even these can cause some damage. In the present work, several types of drugs on the market with different expiration dates are analyzed to find out if these, with the expired expiration date, present spectroscopic differences from those drugs whose expiration date is still valid. This study used the Raman spectroscopy technique to determine the chemical composition of drugs. To measure the drug Raman spectra, Horiba equipment, LabRam HR800, was used with an Olympus confocal microscope focusing a laser of 830 nm and 17 mW on the drugs through a 50 X Leica long-range objective. The Super Paramagnetic Clustering (SPC) method was applied to classify the Raman spectra. In the SPC method, the clustering process is based on a phenomenon of clustering observed in nature at the atomic level and perfectly described by a statistical physics model known as the Potts model, which describes the interacting spins on a crystalline lattice. This clustering method allows for identifying hierarchical structures in the spectra data banks. Fourteen drugs were analyzed, including 2 capsules, 5 tablets, 2 liquid samples, 4 ointments, and one spray with 1 to 3 expired expiration dates. Comparing drugs with expiration dates that are still valid and expired, the SPC results applied to the Raman spectra showed that, although some drugs indicated chemical differences, others indicated no chemical differences, even among those with up to two expired expiration dates. The results showed that Raman spectroscopy and SPC are excellent tools for discriminating between expired and non-expired drugs. The Principal Components Analysis (PCA) was also applied as a cross-checking method of the SPC result, obtaining consistent results. To our knowledge, it is the first preliminary result evaluating the usefulness of Raman spectroscopy and SPC in identifying expired drugs distributed on the market.

References

FDA, U.S. Food and Drug Administration. Expiration dating extension. Available in: https://www.fda.gov/emergency-preparedness-and-response/mcm-legal-regulatory-and-policy-framework/expiration-dating-extension. Accessed on January 01, 2024

WHO Expert Committee on specifications for pharmaceutical preparations. 34th Report. Geneva: World Health Organization; 1990. (Technical Report Series; No. 790)

F. Debesa-García, R. Fernández-Argüelles, and J. Pérez-Pe, La caducidad de los medicamento: justificación de una duda, Rev. Cubana. Farm. 38 (2004). https://scielo.sld.cu/scielo.php?script=sciarttext&pid=S0034-75152004000300010&lng=es

D. Gikonyo, A. Gikonyo, D. Luvayo, P. Ponoth, Drug expiry debate: the myth and the reality, Afr. Health. Sci. 19 (2019) 2737

The Medical Letter. Drugs past their expiration date, Med. Lett. Drugs. Ther. 57 (2015) 164

K. Uehara, T. Tagami, I. Miyazaki, N. Murata, Y. Takahashi, H. Ohkubo, T. Ozeki, Effect of x-ray exposure on the pharmaceutical quality of drug tablets using x-ray inspection equipment, Drug Dev Ind Pharm 41 (2015) 953

R. J. A. Goodwin RJA, Z. Takats, and J. Bunch, A critical and concise review of mass spectrometry applied to imaging in drug discovery, SLAS Discovery 25 (2020) 963

M. Taleuzzaman, S. Ali, S. J. Gilani, S. S. Imam, and A. Hafeez, Ultra performance liquid chromatography (uplc) - a review. Austin J. Anal. Pharm. Chem., 2 (2015) 1056

H. Hahn, J. D. Pallua, C. Pezzei, V. Huck-Pezzei, G. K. C. Bonn, C. Huck, Infrared spectroscopy: A non-invasive tool for medical diagnostics and drug analysis, Current Medicinal Chemistry, 17 (2010) 2956

R. S. Das, Y. K. Agrawal, Raman spectroscopy: Recent advancements, techniques and applications. Vibrational Spectroscopy, 57 (2011) 163

D. A Skoog, F. J. Holler, S. R. Crouch, Principles of Instrumental Analysis (6th Ed.), (Thomson, Brooks-Cole 2007). ISBN 978-0-495-01201-6

O. Gómez, Application of Raman Spectroscopy to Analytical study of Drugs. PhD thesis, Ingeniería superior de Telecomunicación. Universitat Politecnica de Catalunya, España, (2011)

K. C. Gordon, C. M. McGoverin, Raman mapping of pharmaceuticals, Int. J. Pharmaceutics 417 (2011) 151

L. Gasparov, T. Jegorel, L. Loetgering, S. Middey, J. Chakhalian, Thin film substrates from the Raman spectroscopy point of view, J. Raman spectroscopy 45(6), 465-469 (2014)

B. Nagy, A. Farkas, M. Gyürkés, S. Komaromy-Hiller, B. Démuth, B. Szabó, D. Nusser, E. Borbás, G. Marosi, Z. Krist of Nagy, In-line Raman spectroscopic monitoring and feedback control of a continuous twin-screw pharmaceutical powder blending and tableting process, International Journal of Pharmaceutics 530(1-2), 21-29 (2017)

E. Vargas-Obieta, B. E. Martínez-Zerega, J. C. Martínez Espinosa, L. F. Jave-Suárez, A. C. Aguilar-Lemarroy, J. L. González-Solís, Breast cancer detection based on serum samples SERS, Lasers Med Sci 31, 1317-1324 (2016)

J. L. González-Solís, J. C. Martínez-Espinosa, L. Torres González, L. F. Jave-Suárez, A. C. Aguilar-Lemarroy, P. Palomares-Anda, Cervical cancer detection based on serum sample Raman spectroscopy, Lasers Med. Sci. 29(3), 979-985 (2014)

J. L. González-Solís, J. C. Martínez-Espinosa, P. PalomaresAnda, Monitoring of chemotherapy leukemia treatment using Raman spectroscopy and principal component analysis, Lasers Med Sci 29, 1241-1249 (2014)

P. D´haeseleer. How does gene expression clustering work. Nature Biotechnology 23(12), 1499-1501 (2005)

A. Kumar, R. Kannan, Clustering with Spectral Norm and the k-means Algorithm, arXiv:1004.1823 (2010)

M. Blatt, S. Wiseman, E. Domany, Super-paramagnetic clustering of data, Physical Review Letters 76, 3251-3254 (1996)

M. Blatt, S. Wiseman, E. Domany, Data Clustering Using a Model Granular Magnet, Neur. Compt. 9, 1805-1842 (1997)

S. Wiseman, M. Blatt, E. Domany, Super-paramagnetic clustering of data, Phys. Rev. E 57 3767-3787 (1998)

H. Agrawal, E. Domany, Potts Ferromagnets on Coexpressed Gene Networks: Identifying Maximally Stable Partitions, Physical Review Letters 90(15), 158102-1 (2003)

R. König, R. Eils, Gene expression analysis on biochemical networks using the Potts spin model, Bioinformatics 20, 1500- 1505 (2004)

I. V. Tetko, A. F. Facius, A. Ruepp, M. Hans-Werner, Super paramagnetic clustering of protein sequences, BMC Bioinformatics 6(82), 1-13 (2005)

J. L. González-Solís, Discrimination of different cancer types clustering Raman spectra by a super paramagnetic stochastic network approach, PLOS ONE 0213621 (2019)

J. L. González-Solís, L. A. Torres-González, J. R. Villafán-Bernal, Superparamagnetic Clustering of Diabetes Patients Raman Spectra, Journal of Spectroscopy 4296153 (2019)

S. Wang, R. H. Swendsen, Cluster Monte Carlo algorithms, Physica A 167 (1990) 565

R. H. Swendsen, S. Wang, A. M. Ferrenberg, New Monte Carlo methods for improved efficiency of computer simulations in statistical mechanics, The Monte Carlo Methods in Condensed Matter Physics, K. Binder (Eds.), Springer-Verlang: Berlin, Germany, 75-91 (1992)

Chalmers JM, Griffiths PR (2002) Handbook of vibrational spectroscopy, vol. 5. Application in life, pharmaceutical and natural science. Wiley, New York

H. F. Boelens, P. H. Eiler, T. Hankemeier, Sing constrains improve the detection of differences between complex spectral data sets: LC-IR as an example, Anal Chem 77(24), 7998-8007 (2005)

T. Ott, A. Kern, Willi-Hans Steeb, R. Stoop, Sequential clustering: tracking down the most natural clusters, J. Stat. Mech. (2005) DOI:10.1088/1742-5468/2005/11/P11014

T. Ott, A. Kern, A. Schuffenhauer, M. Popov, P. Acklin, E. Jacoby, R. Stoop, Sequential superparamagnetic clustering for unbiased classification of high-dimensional chemical data, J. Chem. Inf. Comput. Sci. 44 (2004) 1358

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Published

2024-11-01

How to Cite

[1]
J. I. Guizar-Ruiz, E. Anaya-Martin, and J. L. González-Solís, “Drug expiration study using Raman spectroscopy and super paramagnetic clustering”, Rev. Mex. Fís., vol. 70, no. 6 Nov-Dec, pp. 061302 1–, Nov. 2024.