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Application of Transmission Raman Spectroscopy in Combination with Partial Least-Squares (PLS) for the Fast Quantification of Paracetamol
In recent years, transmission Raman spectroscopy (TRS) has emerged as a potent new tool for rapid, nondestructive quantitation in pharmaceutical manufacturing. In order to expand the applicability of TRS and enhance its use in product quality monitoring during drug production, we aimed, in the prese...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8911717/ https://www.ncbi.nlm.nih.gov/pubmed/35268808 http://dx.doi.org/10.3390/molecules27051707 |
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author | Zhao, Xuejia Wang, Ning Zhu, Minghui Qiu, Xiaodan Sun, Shengnan Liu, Yitong Zhao, Ting Yao, Jing Shan, Guangzhi |
author_facet | Zhao, Xuejia Wang, Ning Zhu, Minghui Qiu, Xiaodan Sun, Shengnan Liu, Yitong Zhao, Ting Yao, Jing Shan, Guangzhi |
author_sort | Zhao, Xuejia |
collection | PubMed |
description | In recent years, transmission Raman spectroscopy (TRS) has emerged as a potent new tool for rapid, nondestructive quantitation in pharmaceutical manufacturing. In order to expand the applicability of TRS and enhance its use in product quality monitoring during drug production, we aimed, in the present study, to apply partial least-squares (PLS) approaches to build a model consisting of 150 handmade tablets and covering 15 levels through the use of a multifactor orthogonal design of experiment (DOE), which was used to predict concentrations of validation tablets made by hand. The difference between results according to HPLC and TRS were negligible. The model was used to predict the active pharmaceutical ingredient (API) content in four random commercial paracetamol tablets, and corrected with the spectra of the commercial tablets to obtain four corresponding models. The results show that the content relative error in the model’s predictions after correction with commercially available tablets was significantly lower than that before correction. The corrected model was used to make predictions for 20 tablets from the brand Panadol. Compared with the HPLC results, the prediction relative error was basically less than 4.00%, and the relative standard deviation (RSD) of the content was 0.86%. |
format | Online Article Text |
id | pubmed-8911717 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-89117172022-03-11 Application of Transmission Raman Spectroscopy in Combination with Partial Least-Squares (PLS) for the Fast Quantification of Paracetamol Zhao, Xuejia Wang, Ning Zhu, Minghui Qiu, Xiaodan Sun, Shengnan Liu, Yitong Zhao, Ting Yao, Jing Shan, Guangzhi Molecules Article In recent years, transmission Raman spectroscopy (TRS) has emerged as a potent new tool for rapid, nondestructive quantitation in pharmaceutical manufacturing. In order to expand the applicability of TRS and enhance its use in product quality monitoring during drug production, we aimed, in the present study, to apply partial least-squares (PLS) approaches to build a model consisting of 150 handmade tablets and covering 15 levels through the use of a multifactor orthogonal design of experiment (DOE), which was used to predict concentrations of validation tablets made by hand. The difference between results according to HPLC and TRS were negligible. The model was used to predict the active pharmaceutical ingredient (API) content in four random commercial paracetamol tablets, and corrected with the spectra of the commercial tablets to obtain four corresponding models. The results show that the content relative error in the model’s predictions after correction with commercially available tablets was significantly lower than that before correction. The corrected model was used to make predictions for 20 tablets from the brand Panadol. Compared with the HPLC results, the prediction relative error was basically less than 4.00%, and the relative standard deviation (RSD) of the content was 0.86%. MDPI 2022-03-05 /pmc/articles/PMC8911717/ /pubmed/35268808 http://dx.doi.org/10.3390/molecules27051707 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhao, Xuejia Wang, Ning Zhu, Minghui Qiu, Xiaodan Sun, Shengnan Liu, Yitong Zhao, Ting Yao, Jing Shan, Guangzhi Application of Transmission Raman Spectroscopy in Combination with Partial Least-Squares (PLS) for the Fast Quantification of Paracetamol |
title | Application of Transmission Raman Spectroscopy in Combination with Partial Least-Squares (PLS) for the Fast Quantification of Paracetamol |
title_full | Application of Transmission Raman Spectroscopy in Combination with Partial Least-Squares (PLS) for the Fast Quantification of Paracetamol |
title_fullStr | Application of Transmission Raman Spectroscopy in Combination with Partial Least-Squares (PLS) for the Fast Quantification of Paracetamol |
title_full_unstemmed | Application of Transmission Raman Spectroscopy in Combination with Partial Least-Squares (PLS) for the Fast Quantification of Paracetamol |
title_short | Application of Transmission Raman Spectroscopy in Combination with Partial Least-Squares (PLS) for the Fast Quantification of Paracetamol |
title_sort | application of transmission raman spectroscopy in combination with partial least-squares (pls) for the fast quantification of paracetamol |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8911717/ https://www.ncbi.nlm.nih.gov/pubmed/35268808 http://dx.doi.org/10.3390/molecules27051707 |
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