A comparative analysis of univariate versus multivariate eco-friendly spectrophotometric manipulations for resolving severely overlapped spectra of vonoprazan and amoxicillin new combination
Copyright © 2024 Elsevier Inc. All rights reserved..
Vonoprazan and amoxicillin are pharmacological combinations that demonstrate synergistic effects in treating Helicobacter pylori (H. pylori), a global public health concern associated with peptic ulcer disease and gastric cancer. Four spectrophotometric methods were developed, including two univariate techniques (Fourier self-deconvolution and ratio difference) and two multivariate chemometric approaches (partial least squares and principal component regression). These methods provide innovative solutions for effectively resolving and accurately quantifying the overlapping spectra of vonoprazan and amoxicillin. The concentration ranges covered were 3-60 μg ml-1 for vonoprazan and 5-140 μg ml-1 for amoxicillin. To assess the environmental sustainability of the methodologies, various measures such as the Green Analytical Procedure Index (GAPI), National Environmental Method Index (NEMI), Analytical GREEnness Calculator, and Analytical Eco-scale, as well as RGB12 and hexagon toll were implemented. The validation of the developed techniques was carried out in compliance with ICH standards. The present study is highly significant because it is the first time that the mixture has been determined using the current approaches. The comparative analysis demonstrated no significant difference in terms of accuracy and precision compared to reference HPLC method (p = 0.05). The established spectrophotometric methods offer a straightforward, rapid, and cost-effective alternative to complex analytical techniques for determining the vonoprazan and amoxicillin mixture. They show potential for routine analysis in research laboratories and pharmaceutical industries.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:689 |
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| Enthalten in: |
Analytical biochemistry - 689(2024) vom: 15. Apr., Seite 115501 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Kammoun, Ahmed K [VerfasserIn] |
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| Links: |
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| Anmerkungen: |
Date Completed 01.04.2024 Date Revised 01.04.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.ab.2024.115501 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a Vonoprazan and amoxicillin are pharmacological combinations that demonstrate synergistic effects in treating Helicobacter pylori (H. pylori), a global public health concern associated with peptic ulcer disease and gastric cancer. Four spectrophotometric methods were developed, including two univariate techniques (Fourier self-deconvolution and ratio difference) and two multivariate chemometric approaches (partial least squares and principal component regression). These methods provide innovative solutions for effectively resolving and accurately quantifying the overlapping spectra of vonoprazan and amoxicillin. The concentration ranges covered were 3-60 μg ml-1 for vonoprazan and 5-140 μg ml-1 for amoxicillin. To assess the environmental sustainability of the methodologies, various measures such as the Green Analytical Procedure Index (GAPI), National Environmental Method Index (NEMI), Analytical GREEnness Calculator, and Analytical Eco-scale, as well as RGB12 and hexagon toll were implemented. The validation of the developed techniques was carried out in compliance with ICH standards. The present study is highly significant because it is the first time that the mixture has been determined using the current approaches. The comparative analysis demonstrated no significant difference in terms of accuracy and precision compared to reference HPLC method (p = 0.05). The established spectrophotometric methods offer a straightforward, rapid, and cost-effective alternative to complex analytical techniques for determining the vonoprazan and amoxicillin mixture. They show potential for routine analysis in research laboratories and pharmaceutical industries | ||
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