Ciprofloxacin; FT-NIR; MCR-ALS; Matrix effect; PLS; Spectroscopy; Instrumentation; Atomic and Molecular Physics, and Optics; Analytical Chemistry
Abstract :
[en] This study aims to quantify ciprofloxacin in commercial tablets with varying excipient compositions using Fourier Transform Near-Infrared Spectroscopy (FT-NIR) and chemometric models: Partial Least Squares (PLS) and Multivariate Curve Resolution - Alternating Least Squares (MCR-ALS). Matrix variation, arising from differences in excipient compositions among the tablets, can impact quantification accuracy. We discuss this phenomenon, emphasizing potential issues introduced by varying certain excipients and its importance in reliable ciprofloxacin quantification. We evaluated the performance of PLS and MCR-ALS models independently on two sets of tablets, each containing the same drug substance but different excipients. The statistical results revealed promising results with PLS prediction error of 0.38% w/w of the first set and 0.47% w/w of the second set, while MCR-ALS achieved prediction errors of 0.67% w/w of the first set and 1.76% w/w of the second set. To address the challenge of matrix variation, we developed single models for PLS and MCR-ALS using a dataset combining both first and second sets. The PLS single model demonstrated a prediction error of 4.3% w/w and a relative error of 6.41% w/w, while the MCR-ALS single model showed a prediction error of 1.88% w/w and a relative error of 1.29% w/w. We then assessed the performance of the single PLS and MCR-ALS models developed based on the combination of the first and the second set in quantifying ciprofloxacin in various commercial tablet brands containing new excipients. The PLS model achieved a prediction error ranging between 6.2% w/w and 8.39% w/w, with relative errors varied between 8.53% w/w and 12.82% w/w. On the other hand, the MCR-ALS model had a prediction error between 1.11% w/w and 2.66% w/w, and the relative errors ranging from 0.8% to 1.74% w/w.
Disciplines :
Pharmacy, pharmacology & toxicology
Author, co-author :
Alaoui Mansouri, Mohammed ; Université de Liège - ULiège > Unités de recherche interfacultaires > Centre Interdisciplinaire de Recherche sur le Médicament (CIRM) ; Nano and Molecular Systems Research Unit, University of Oulu, Finland , Bio-Pharmaceutical and Toxicological Analysis Research Team, Laboratory of Pharmacology and Toxicology, Faculty of Medicine and Pharmacy, University Mohammed V, Rabat, Morocco
Kharbach, M; Bio-Pharmaceutical and Toxicological Analysis Research Team, Laboratory of Pharmacology and Toxicology, Faculty of Medicine and Pharmacy, University Mohammed V, Rabat, Morocco, Research Unit of Mathematical Sciences, University of Oulu, FI-90014 Oulu, Finland. Electronic address: mourad1kharbach@gmail.com
El Maouardi, M; Bio-Pharmaceutical and Toxicological Analysis Research Team, Laboratory of Pharmacology and Toxicology, Faculty of Medicine and Pharmacy, University Mohammed V, Rabat, Morocco
Barra, I ; Bio-Pharmaceutical and Toxicological Analysis Research Team, Laboratory of Pharmacology and Toxicology, Faculty of Medicine and Pharmacy, University Mohammed V, Rabat, Morocco, Center of Excellence in Soil and Fertilizer Research in Africa, Mohammed VI Polytechnic University, Benguerir, Morocco
Bouklouze, A; Bio-Pharmaceutical and Toxicological Analysis Research Team, Laboratory of Pharmacology and Toxicology, Faculty of Medicine and Pharmacy, University Mohammed V, Rabat, Morocco
Language :
English
Title :
Quantification of ciprofloxacin in pharmaceutical products from various brands using FT-NIR: A comparative investigation of PLS and MCR-ALS.
Publication date :
16 August 2023
Journal title :
Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy
B. Igne, C. Airiau, S. Talwar, E. Towns, 4.02 - Chemometrics in the Pharmaceutical Industry, in: S. Brown, R. Tauler, B.B.T.-C.C. (Second E. Walczak (Eds.), Elsevier, Oxford, 2020, pp. 33–68. https://doi.org/https://doi.org/10.1016/B978-0-12-409547-2.14638-4.
da Silva, V.H., Soares-Sobrinho, J.L., Pereira, C.F., Rinnan, Å., Evaluation of chemometric approaches for polymorphs quantification in tablets using near-infrared hyperspectral images. Eur. J. Pharm. Biopharm. 134 (2019), 20–28 10.1016/j.ejpb.2018.11.007.
Alaoui Mansouri, M., Ziemons, E., Sacré, P.-Y., Kharbach, M., Barra, I., Cherrah, Y., Hubert, P., Marini, R.D., Bouklouze, A., Classification of polymorphic forms of fluconazole in pharmaceuticals by FT-IR and FT-NIR spectroscopy. J. Pharm. Biomed. Anal., 196, 2021, 10.1016/j.jpba.2021.113922.
De Bleye, C., Chavez, P.F., Mantanus, J., Marini, R., Hubert, P., Rozet, E., Ziemons, E., Critical review of near-infrared spectroscopic methods validations in pharmaceutical applications. J. Pharm. Biomed. Anal. 69 (2012), 125–132, 10.1016/j.jpba.2012.02.003.
Jamrógiewicz, M., Application of the near-infrared spectroscopy in the pharmaceutical technology. J. Pharm. Biomed. Anal. 66 (2012), 1–10 10.1016/j.jpba.2012.03.009.
Moustafa, H., Fayez, Y., Spectrophotometric methods manipulating ratio spectra for simultaneous determination of binary mixtures with sever overlapping spectra: A comparative study. Spectrochim. Acta A Mol. Biomol. Spectrosc. 133 (2014), 759–766 10.1016/j.saa.2014.06.059.
De Luca, M., Ioele, G., Spatari, C., Ragno, G., Optimization of wavelength range and data interval in chemometric analysis of complex pharmaceutical mixtures. J. Pharm. Anal. 6 (2016), 64–69 10.1016/j.jpha.2015.10.001.
Yehia, A.M., Mohamed, H.M., Chemometrics resolution and quantification power evaluation: Application on pharmaceutical quaternary mixture of Paracetamol, Guaifenesin, Phenylephrine and p-aminophenol. Spectrochim. Acta A Mol. Biomol Spectrosc. 152 (2016), 491–500 10.1016/j.saa.2015.07.101.
De Luca, M., Oliverio, F., Ioele, G., Ragno, G., Multivariate calibration techniques applied to derivative spectroscopy data for the analysis of pharmaceutical mixtures. Chemom. Intel. Lab. Syst. 96 (2009), 14–21 10.1016/j.chemolab.2008.10.009.
Wang, X., Mao, D.-Z., Yang, Y.-J., Calibration transfer between modelled and commercial pharmaceutical tablet for API quantification using backscattering NIR, Raman and transmission Raman spectroscopy (TRS). J. Pharm. Biomed. Anal., 194, 2021, 113766 10.1016/j.jpba.2020.113766.
Rajalahti, T., Kvalheim, O.M., Multivariate data analysis in pharmaceutics: A tutorial review. Int. J. Pharm. 417 (2011), 280–290 10.1016/j.ijpharm.2011.02.019.
De Luca, M., Ioele, G., Spatari, C., Ragno, G., A single MCR-ALS model for drug analysis in different formulations: Application on diazepam commercial preparations. J. Pharm. Biomed. Anal. 134 (2017), 346–351, 10.1016/j.jpba.2016.10.022.
Pinto, L., Stechi, F., Breitkreitz, M.C., A simplified and versatile multivariate calibration procedure for multiproduct quantification of pharmaceutical drugs in the presence of interferences using first order data and chemometrics. Microchem. J. 146 (2019), 202–209, 10.1016/j.microc.2019.01.014.
Tawakkol, S.M., Farouk, M., Abd Elaziz, O., Hemdan, A., Shehata, M.A., Comparative study between univariate spectrophotometry and multivariate calibration as analytical tools for simultaneous quantitation of Moexipril and Hydrochlorothiazide. Spectrochim. Acta A Mol. Biomol. Spectrosc. 133 (2014), 300–306.
Dinc, E., Ragno, G., Ioele, G., Baleanu, D., DRUG FORMULATIONS AND CLINICAL METHODS-Fractional Wavelet Analysis for the Simultaneous Quantitative Analysis of Lacidipine and Its Photodegradation Product by Continuous Wavelet Transform and Multilinear Regression Calibration. J. AOAC Int., 89, 2006, 1538.
Jaumot, J., de Juan, A., Tauler, R., MCR-ALS GUI 2.0: New features and applications. Chemom. Intel. Lab. Syst. 140 (2015), 1–12 10.1016/j.chemolab.2014.10.003.