Advanced spectrophotometric chemometric methods for resolving the binary mixture of doxylamine succinate and pyridoxine hydrochloride
The prediction power of partial least squares (PLS) and multivariate curve resolution-alternating least squares (MCR-ALS) methods have been studied for simultaneous quantitative analysis of the binary drug combination - doxylamine succinate and pyridoxine hydrochloride. Analysis of first-order UV ov...
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Sciendo
2018-03-01
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Series: | Acta Pharmaceutica |
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Online Access: | https://doi.org/10.2478/acph-2018-0008 |
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author | Katsarov Plamen Gergov Georgi Alin Aylin Pilicheva Bissera Al-Degs Yahya Simeonov Vasil Kassarova Margarita |
author_facet | Katsarov Plamen Gergov Georgi Alin Aylin Pilicheva Bissera Al-Degs Yahya Simeonov Vasil Kassarova Margarita |
author_sort | Katsarov Plamen |
collection | DOAJ |
description | The prediction power of partial least squares (PLS) and multivariate curve resolution-alternating least squares (MCR-ALS) methods have been studied for simultaneous quantitative analysis of the binary drug combination - doxylamine succinate and pyridoxine hydrochloride. Analysis of first-order UV overlapped spectra was performed using different PLS models - classical PLS1 and PLS2 as well as partial robust M-regression (PRM). These linear models were compared to MCR-ALS with equality and correlation constraints (MCR-ALS-CC). All techniques operated within the full spectral region and extracted maximum information for the drugs analysed. The developed chemometric methods were validated on external sample sets and were applied to the analyses of pharmaceutical formulations. The obtained statistical parameters were satisfactory for calibration and validation sets. All developed methods can be successfully applied for simultaneous spectrophotometric determination of doxylamine and pyridoxine both in laboratory-prepared mixtures and commercial dosage forms. |
format | Article |
id | doaj-art-7658766319de4a049ad88dc858712ddc |
institution | Kabale University |
issn | 1846-9558 |
language | English |
publishDate | 2018-03-01 |
publisher | Sciendo |
record_format | Article |
series | Acta Pharmaceutica |
spelling | doaj-art-7658766319de4a049ad88dc858712ddc2025-02-02T19:57:25ZengSciendoActa Pharmaceutica1846-95582018-03-01681617310.2478/acph-2018-0008acph-2018-0008Advanced spectrophotometric chemometric methods for resolving the binary mixture of doxylamine succinate and pyridoxine hydrochlorideKatsarov Plamen0Gergov Georgi1Alin Aylin2Pilicheva Bissera3Al-Degs Yahya4Simeonov Vasil5Kassarova Margarita6Department of Pharmaceutical Sciences Faculty of Pharmacy, Medical University-Plovdiv, 4002 Plovdiv, BulgariaDepartment of Chemistry, Faculty of Pharmacy, Medical University Sofia 1000 Sofia, BulgariaDepartment of Statistics, Dokuz Eylul University, 35160 Izmir, TurkeyDepartment of Pharmaceutical Sciences Faculty of Pharmacy, Medical University-Plovdiv, 4002 Plovdiv, BulgariaChemistry Department, The Hashemite University, P. O. Box 150459 Zarqa 13115 JordanLaboratory of Chemometrics and Environmetrics, Faculty of Chemistry and Pharmacy, Sofia University “St. Kliment Ohridski”, 1164 Sofia, BulgariaDepartment of Pharmaceutical Sciences Faculty of Pharmacy, Medical University-Plovdiv, 4002 Plovdiv, BulgariaThe prediction power of partial least squares (PLS) and multivariate curve resolution-alternating least squares (MCR-ALS) methods have been studied for simultaneous quantitative analysis of the binary drug combination - doxylamine succinate and pyridoxine hydrochloride. Analysis of first-order UV overlapped spectra was performed using different PLS models - classical PLS1 and PLS2 as well as partial robust M-regression (PRM). These linear models were compared to MCR-ALS with equality and correlation constraints (MCR-ALS-CC). All techniques operated within the full spectral region and extracted maximum information for the drugs analysed. The developed chemometric methods were validated on external sample sets and were applied to the analyses of pharmaceutical formulations. The obtained statistical parameters were satisfactory for calibration and validation sets. All developed methods can be successfully applied for simultaneous spectrophotometric determination of doxylamine and pyridoxine both in laboratory-prepared mixtures and commercial dosage forms.https://doi.org/10.2478/acph-2018-0008doxylamine succinatepyridoxine hydrochloridebinary mixturepartial least squares (pls)partial robust m-regression (prm)multivariate curve resolution-alternative least squares (mcr-als) |
spellingShingle | Katsarov Plamen Gergov Georgi Alin Aylin Pilicheva Bissera Al-Degs Yahya Simeonov Vasil Kassarova Margarita Advanced spectrophotometric chemometric methods for resolving the binary mixture of doxylamine succinate and pyridoxine hydrochloride Acta Pharmaceutica doxylamine succinate pyridoxine hydrochloride binary mixture partial least squares (pls) partial robust m-regression (prm) multivariate curve resolution-alternative least squares (mcr-als) |
title | Advanced spectrophotometric chemometric methods for resolving the binary mixture of doxylamine succinate and pyridoxine hydrochloride |
title_full | Advanced spectrophotometric chemometric methods for resolving the binary mixture of doxylamine succinate and pyridoxine hydrochloride |
title_fullStr | Advanced spectrophotometric chemometric methods for resolving the binary mixture of doxylamine succinate and pyridoxine hydrochloride |
title_full_unstemmed | Advanced spectrophotometric chemometric methods for resolving the binary mixture of doxylamine succinate and pyridoxine hydrochloride |
title_short | Advanced spectrophotometric chemometric methods for resolving the binary mixture of doxylamine succinate and pyridoxine hydrochloride |
title_sort | advanced spectrophotometric chemometric methods for resolving the binary mixture of doxylamine succinate and pyridoxine hydrochloride |
topic | doxylamine succinate pyridoxine hydrochloride binary mixture partial least squares (pls) partial robust m-regression (prm) multivariate curve resolution-alternative least squares (mcr-als) |
url | https://doi.org/10.2478/acph-2018-0008 |
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