Document Type: Research Paper

**Authors**

Razi University

**Abstract**

Prediction using pure standards is expected to be biased whenever the slope of the calibration is affected by the presence of sample matrix. Moreover, in the presence of unknown spectral interferents, first-order algorithms like partial least squares cannot be used. In this study, a method for determination of carvedilol (CAR) in tablet and urine samples is proposed by excitation-emission fluorescence spectroscopy (EEM). The multivariate curve resolution-alternating least-squares (MCR-ALS) coupled with trilinearity constraint exploiting the second order advantage is applied for the analysis of EEMs. Moreover, the combination of standard addition with MCR-ALS was used to correct the matrix effect. Indeed, by the proposed strategy, both matrix effect and the problem of the presence of unknown interferents in determination of CAR are overcome. The MCR-ALS method was applied on EEMs under non-negativity and trilinearity constraints. For both samples, CAR was quantified at low mg l^{-1} level with an overall prediction error of -3.1% and -4.0% in urine and tablet samples, respectively.

**Keywords**

[1] R.R. Ruffolo, M. Gellai, J.P. Hieble, R.N. Willette, A.J. Nichols, The pharmacology of carvedilol, Eur. J. Clin. Pharmacol. 38 (1990) S82-S88.

[2] A.J. Nichols, M. Gellai, R.R. Ruffolo, Studies on the mechanism of arterial vasodilation produced by the novel antihypertensive agent carvedilol, Fundam. Clin. Pharmacol. 5 (1991) 25–38.

[3] C. de Mey, K. Breithaupt, J. Schloos, G. Neugebauer, D. Palm, G.G. Belz, Dose-effect and pharmacokinetic-pharmacodynamic relationships of the beta 1-adrenergic receptor blocking properties of various doses of carvedilol in healthy humans, Clin. Pharmacol. Ther. 55 (1994) 329-337.

[4] L.X. Xu, N.Hui, L.Y. Ma, H.Y. Wang, Study on fluorescence property of carvedilol and determination of carvedilol by fluorimetry, Spectrochim. Acta A 61 (2005) 855–859.

[5] L.E. Sayed, A. Mohamed, E.A. Taha, A. Fattah, A. Taghreed, Spectrofluorimetric determination of carvedilol in dosage form and spiked human plasma through derivatization with 1-Dimethylamino-naphthalene-5-sulphonyl chloride, Chemi. Ind. Chem. Engin. Quat. 16 (2010) 31-38.

[6] J.C.G.E. da Silva, M.J. Tavares, R. Tauler, Multivariate curve resolution of multidimensional excitation–emission quenching matrices of a Laurentian soil fulvic acid, Chemosphere 64 (2006) 1939–1948.

[7] M.C.G. Antunes, C.C.C. Pereira, J.C.G. E. da Silva, MCR of the quenching of the EEM of fluorescence of dissolved organic matter by metal ions, Anal. Chim. Acta 595 (2007) 9–18.

[8] J. Saurina, R. Tauler, Strategies for solving matrix effects in the analysis of triphenyltin in sea-water samples by three-way multivariate curve resolution, Analyst 125 (2000) 2038–2043.

[9] J. Saurina, C. Leal, R. Compano, M. Granados, M.D. Prat, R. Tauler, Estimation of figures of merit using univariate statistics for quantitative second-order multivariate curve resolution, Anal. Chim. Acta 432 (2001) 241–251.

[10] J. Saurina, S. Hemandez-Cassou, R. Tauler, Multivariate Curve Resolution and Trilinear Decomposition Methods in the Analysis of Stopped-Flow Kinetic Data for Binary Amino Acid Mixtures, Anal. Chem. 69 (1997) 2329–2336.

[11] A. Juan, S. C. Rutan, R. Tauler, D.L. Massart, Comparison between the direct trilinear decomposition and the multivariate curve resolution-alternating least squares methods for the resolution of three-way data sets, Chemometr. Intell. Lab. Syst. 40 (1998) 19-32.

[12] K. Kumar, A. K. Mishra, Application of multivariate curve resolution alternating least square (MCR–ALS) analysis to extract pure component synchronous fluorescence spectra at various wavelength offsets from total synchronous fluorescence spectroscopy (TSFS) data set of dilute aqueous solutions of fluorophores, Chemometr. Intell. Lab. Syst. 116 (2012) 78–86.

[13] J. Saurina, C. Leal, R. Compano, M. Granados, R. Tauler, M.D. Prat, Determination of triphenyltin in sea-water by excitation–emission matrix fluorescence and multivariate curve resolution, Anal. Chim. Acta 409 (2000) 237–245.

[14] S.H. Zhu, H.L. Wu, B.R. Li, A.L. Xia, Q.J. Han, Y. Zhang, Y.C. Bian, R.Q. Yu, Determination of pesticides in honey using excitation–emission matrix fluorescence coupled with second-order calibration and second-order standard addition methods, Anal. Chim. Acta 619 (2008) 165–172.

[15] J. Saurina, S. Hernandez-Cassou, R. Tauler, Multivariate curve resolution applied to continuous-flow spectrophotometric titrations. Reaction between amino acids and 1, 2-naphthoquinone-4-sulfonic acid, Anal. Chem. 67 (1995) 3722–3726.

[16] R. Tauler, D. Barcelo, Multivariate curve resolution applied to liquid chromatography-diode array detection, Trends Anal. Chem. 12 (1993) 319-327.

[17] J. Jaumot, R. Gargallo, N. Escaja, C. Gonzalez, E. Pedroso, R. Tauler, Multivariate curve resolution: a powerful tool for the analysis of conformational transitions in nucleic acids, Nucleic Acid Res. 30 (2002) 1-10.

[18] T. Azzouz, R. Tauler, Application of multivariate curve resolution alternating least squares (MCR-ALS) to the quantitative analysis of pharmaceutical and agricultural samples, Talanta 74 (2008) 1201–1210.

[19] S.E. Richards, E. Becker, R. Tauler, A.D. Walmsley, A novel approach to the quantification of industrial mixtures from the Vinyl Acetate Monomer (VAM) process using Near Infrared spectroscopic data and a Quantitative Self Modeling Curve Resolution (SMCR) methodology, Chemometr. Intell. Lab. Syst. 94 (2008) 9–18.

[20] R.A. Harshman, Foundations of the PARAFAC procedure: Models and conditions for an "explanatory" multi-modal factor analysis, UCLA Working Papers in Phonetics 16 (1970) 1-84.

[21] J.D. Carroll, J.J. Chang, Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition, Psychometrika 35 (1970) 283-319.

[22] A.P. Silva, A.S. Luna, T.M.D. Silva Costa, R.Q. Aucelio, J.W.B. Braga, R. Boque, J. Ferre, Spectrofluorimetric determination of levofloxacin in pharmaceuticals and in human urine, Int. J. Life Sci. Pharma Res. 2 (2012) L147-L158.

[23] H.L. Wu, M. Shibukawa, K. Oguma, An alternating trilinear decomposition method with application to calibration of HPLC-DAD for simultaneous determination of overlapped chlorinated aromatic hydrocarbons, J. Chemometr. 12 (1998) 1-26.

[24] Z.P. Chen, H.L. Wu, R. Q. Yu, On the self-weighted alternating trilinear decomposition algorithm—the property of being insensitive to excess factors used in calculation, J. Chemometr. 15 (2001) 439–453.

[25] A.L. Xia, H.L. Wu, D.M. Fang, Y.J. Ding, L.Q. Hu, R.Q. Yu, Alternating penalty trilinear decomposition algorithm for second-order calibration with application to interference-free analysis of excitation–emission matrix fluorescence data, J. Chemometr. 19 (2005) 65–76.

[26] H. Gampp, M. Maeder, C. Meyer, A.D. Zuberbuhler, Calculation of equilibrium constants from multiwavelength spectroscopic data-IV Model-free least-squares refinement by use of evolving factor analysis, Talanta 33 (1986) 943-951.

[27] M. Maeder, A. Zilian, Evolving factor analysis, a new multivariate technique in chromatography, Chemometr. Intell. Lab. Syst. 3 (1988) 205-213.

[28] M. Maeder, Evolving factor analysis for the resolution of overlapping chromatographic peaks, Anal. Chem. 59 (1987) 527-530.

[29] W. Windig, J. Guilment, Interactive Self-Modeling Mixture Analysis, Anal. Chem. 63 (1991) 1425-1432.

[30] W. Windig, D.A. Stephenson, Self-modeling mixture analysis of second-derivative near-infrared spectral data using the SIMPLISMA approach, Anal. Chem. 64 (1992) 2735-2742.

[31] W. Windig, C.E. Heckler, F.A. Agblevor, R.J. Evans, Self-modeling mixture analysis of categorized pyrolysis mass spectral data with the SIMPLISMA approach, Chemometr. Intell. Lab. 14 (1992) 195–207.

[32] M. Shariati-Rad, M. Hasani, Application of multivariate curve resolution– alternating least squares (MCR–ALS) for secondary structure resolving of proteins, Biochimie 91 (2009) 850–856.

[33] R. Tauler, D. Barcelo, Multivariate curve resolution applied to liquid chromatography– diode array detection, Anal. Chem. 12 (1993) 319–327

[34] R. Tauler, A. Smilde, B.R. Kowalski, Selectivity, local rank, three-way data analysis and ambiguity in multivariate curve resolution, J. Chemometr. 9 (1995) 31-58.

[35] R. Tauler, Multivariate data analysis-in practice. An introduction to multivariate data analysis and experimental design, J. Chemometr. 16 (2002) 117-118.

[36] S. Wold, K. Esbensen, P. Geladi, Principal Component Analysis, Chemometr. Intell. Lab. Syst. 2 (1987) 37-52.

[37] B.M.G. Vandeginste, D.L.Massart, L.M.C. Buydens, S. De Jong, P.J. Lewi, J. Smeyers-Verbeke, Handbook of Chemometrics and Qualimetrics: Part B., Elsevier Science B.V., Amsterdam,1998.

[38] J.R. de Haan , R. Wehrens , S. Bauerschmidt , E. Piek , R.C. van Schaik, L.M.C. Buydens, Interpretation of ANOVA models for microarray data using PCA, Bioinformatics . 23 (2007) 184–190.

[40] V. Gomez, R. Cuadros, I. Ruisanchez, M.P. Callao, Matrix effect in second-order data: Determination of dyes in tanning process using vegetable tanning agents, Anal. Chim. Acta 600 (2007) 233-239.

[41] V. A. Lozanoa, R. Tauler, G. A. Ibanez, A. C. Olivieri, Standard addition analysis of fluoroquinolones in human serum in the presence of the interferent salicylate using lanthanide-sensitized excitation-time decay luminescence data and multivariate curve resolution, Talanta 77 (2009) 1715-1723.

Volume 2, Issue 2

Autumn 2015

Page 129-137