scholarly journals Quantitative analysis and resolution of pharmaceuticals in the environment using multivariate curve resolution-alternating least squares (MCR-ALS)

2019 ◽  
Vol 69 (2) ◽  
pp. 217-231 ◽  
Author(s):  
Ahmed Mostafa ◽  
Heba Shaaban
Keyword(s):  
Least Squares ◽  
Water Samples ◽  
Alternating Least Squares ◽  
Multivariate Curve Resolution ◽  
Least Squares Regression ◽  
Environmental Matrices ◽  
Curve Resolution ◽  
Real Water Samples ◽  
Target Analytes ◽  
Spectrophotometric Data

Abstract The study presents the application of multivariate curve resolution alternating least squares (MCR-ALS) with a correlation constraint for simultaneous resolution and quantification of ketoprofen, naproxen, paracetamol and caffeine as target analytes and triclosan as an interfering component in different water samples using UV-Vis spectrophotometric data. A multivariate regression model using the partial least squares regression (PLSR) algorithm was developed and calculated. The MCR-ALS results were compared with the PLSR obtained results. Both models were validated on external sample sets and were applied to the analysis of real water samples. Both models showed comparable and satisfactory results with the relative error of prediction of real water samples in the range of 1.70–9.75 % and 1.64–9.43 % for MCR-ALS and PLSR, resp. The obtained results show the potential of MCR-ALS with correlation constraint to be applied for the determination of different pharmaceuticals in complex environmental matrices.

scholarly journals Eco-Friendly Pharmaceutical Analysis of Multicomponent Drugs Coformulated in Different Dosage Forms Using Multivariate Curve Resolution and Partial Least Squares: A Comparative Study

2019 ◽  
Vol 102 (2) ◽  
pp. 465-472 ◽  
Author(s):  
Ahmed Mostafa ◽  
Heba Shaaban ◽  
Mishal Almousa ◽  
Mishal Al Sheqawi ◽  
Muntdher Almousa
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Dosage Forms ◽  
Multivariate Curve Resolution ◽  
Control Analysis ◽  
Least Squares Regression ◽  
Pharmaceutical Dosage Forms ◽  
Curve Resolution ◽  
Target Analytes ◽  
Significant Difference

Abstract Background: Considering the environmental impact of analytical procedures necessitates replacing the polluting analytical methods with green alternatives. Objective: This study aims to develop and validate a multivariate curve resolution–alternating least-squares (MCR-ALS) method with correlation constraint for the simultaneous determination of theophylline, ambroxol, and guaifenesin as target analytes in the presence of methylparaben and propylparaben as interfering components. In addition, a partial least-squares regression (PLSR) method was also developed andoptimized. Method: The developed methods were validated according to International Conference on Harmonization guidelines and successfully applied for the quantification of the target analytes in different pharmaceutical dosage forms. Results: Figures of merit such as root mean square error of prediction, bias, standard error of prediction, and relative error of prediction for both models were calculated, and they showedsimilar and satisfactory results. Correlation coefficients ranged between 0.9988 and 0.9992, reflectinghigh predictive ability. The optimized methods werecompared with a reported HPLC method using one-wayanalysis of variance and showed no significant difference regarding accuracy and precision. Conclusions: The proposed chemometrics methods can be used as an eco-friendly alternative for chromatographic techniques for the quality control analysis of the studied mixture in different pharmaceutical dosage forms. Highlights: An MCR-ALS model was developed. The developed model was compared with a PLSR model. Both models were validated and successfully used for the determinationof a multicomponent pharmaceutical mixture. The developed method is eco-friendly, fast, reliable, and cost-effective.

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