<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></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.

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

College of Clinical Pharmacy Imam Abdulrahman Bin Faisal University

Acta Pharmaceutica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The study presents the application of multivariate curve resolution alternating least squares (MCR-ALS) with a correlation constraint for simultaneous...

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

Publié en ligne: 28 mars 2019

Pages: 217 - 231

Accepté: 29 sept. 2018

DOI: https://doi.org/10.2478/acph-2019-0011

Mots clés
multivariate curve resolution alternating least squares, correlation constraint, partial least squares, multivariate calibration, environmental analysis, UV-Vis spectrophotometry

© 2019 Ahmed Mostafa et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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

Publié en ligne: 28 mars 2019

Pages: 217 - 231

Accepté: 29 sept. 2018

DOI: https://doi.org/10.2478/acph-2019-0011

Mots clésmultivariate curve resolution alternating least squares, correlation constraint, partial least squares, multivariate calibration, environmental analysis, UV-Vis spectrophotometry

© 2019 Ahmed Mostafa et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
multivariate curve resolution alternating least squares, correlation constraint, partial least squares, multivariate calibration, environmental analysis, UV-Vis spectrophotometry