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Label-Free Quantification of Nanoencapsulated Piperonyl Esters in Cosmetic Hydrogels Using Raman Spectroscopy

Raman spectroscopy is a well-established technique for the molecular characterisation of samples and does not require extensive pre-analytical processing for complex cosmetic products. As an illustration of its potential, this study investigates the quantitative performance of Raman spectroscopy cou...

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Autores principales: Elderderi, Suha, Bonnier, Franck, Perse, Xavier, Byrne, Hugh J., Yvergnaux, Florent, Chourpa, Igor, Elbashir, Abdalla A., Munnier, Emilie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10304590/
https://www.ncbi.nlm.nih.gov/pubmed/37376021
http://dx.doi.org/10.3390/pharmaceutics15061571
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author Elderderi, Suha
Bonnier, Franck
Perse, Xavier
Byrne, Hugh J.
Yvergnaux, Florent
Chourpa, Igor
Elbashir, Abdalla A.
Munnier, Emilie
author_facet Elderderi, Suha
Bonnier, Franck
Perse, Xavier
Byrne, Hugh J.
Yvergnaux, Florent
Chourpa, Igor
Elbashir, Abdalla A.
Munnier, Emilie
author_sort Elderderi, Suha
collection PubMed
description Raman spectroscopy is a well-established technique for the molecular characterisation of samples and does not require extensive pre-analytical processing for complex cosmetic products. As an illustration of its potential, this study investigates the quantitative performance of Raman spectroscopy coupled with partial least squares regression (PLSR) for the analysis of Alginate nanoencapsulated Piperonyl Esters (ANC-PE) incorporated into a hydrogel. A total of 96 ANC-PE samples covering a 0.4% w/w–8.3% w/w PE concentration range have been prepared and analysed. Despite the complex formulation of the sample, the spectral features of the PE can be detected and used to quantify the concentrations. Using a leave-K-out cross-validation approach, samples were divided into a training set (n = 64) and a test set, samples that were previously unknown to the PLSR model (n = 32). The root mean square error of cross-validation (RMSECV) and prediction (RMSEP) was evaluated to be 0.142% (w/w PE) and 0.148% (w/w PE), respectively. The accuracy of the prediction model was further evaluated by the percent relative error calculated from the predicted concentration compared to the true value, yielding values of 3.58% for the training set and 3.67% for the test set. The outcome of the analysis demonstrated the analytical power of Raman to obtain label-free, non-destructive quantification of the active cosmetic ingredient, presently PE, in complex formulations, holding promise for future analytical quality control (AQC) applications in the cosmetics industry with rapid and consumable-free analysis.
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spelling pubmed-103045902023-06-29 Label-Free Quantification of Nanoencapsulated Piperonyl Esters in Cosmetic Hydrogels Using Raman Spectroscopy Elderderi, Suha Bonnier, Franck Perse, Xavier Byrne, Hugh J. Yvergnaux, Florent Chourpa, Igor Elbashir, Abdalla A. Munnier, Emilie Pharmaceutics Article Raman spectroscopy is a well-established technique for the molecular characterisation of samples and does not require extensive pre-analytical processing for complex cosmetic products. As an illustration of its potential, this study investigates the quantitative performance of Raman spectroscopy coupled with partial least squares regression (PLSR) for the analysis of Alginate nanoencapsulated Piperonyl Esters (ANC-PE) incorporated into a hydrogel. A total of 96 ANC-PE samples covering a 0.4% w/w–8.3% w/w PE concentration range have been prepared and analysed. Despite the complex formulation of the sample, the spectral features of the PE can be detected and used to quantify the concentrations. Using a leave-K-out cross-validation approach, samples were divided into a training set (n = 64) and a test set, samples that were previously unknown to the PLSR model (n = 32). The root mean square error of cross-validation (RMSECV) and prediction (RMSEP) was evaluated to be 0.142% (w/w PE) and 0.148% (w/w PE), respectively. The accuracy of the prediction model was further evaluated by the percent relative error calculated from the predicted concentration compared to the true value, yielding values of 3.58% for the training set and 3.67% for the test set. The outcome of the analysis demonstrated the analytical power of Raman to obtain label-free, non-destructive quantification of the active cosmetic ingredient, presently PE, in complex formulations, holding promise for future analytical quality control (AQC) applications in the cosmetics industry with rapid and consumable-free analysis. MDPI 2023-05-23 /pmc/articles/PMC10304590/ /pubmed/37376021 http://dx.doi.org/10.3390/pharmaceutics15061571 Text en © 2023 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
Elderderi, Suha
Bonnier, Franck
Perse, Xavier
Byrne, Hugh J.
Yvergnaux, Florent
Chourpa, Igor
Elbashir, Abdalla A.
Munnier, Emilie
Label-Free Quantification of Nanoencapsulated Piperonyl Esters in Cosmetic Hydrogels Using Raman Spectroscopy
title Label-Free Quantification of Nanoencapsulated Piperonyl Esters in Cosmetic Hydrogels Using Raman Spectroscopy
title_full Label-Free Quantification of Nanoencapsulated Piperonyl Esters in Cosmetic Hydrogels Using Raman Spectroscopy
title_fullStr Label-Free Quantification of Nanoencapsulated Piperonyl Esters in Cosmetic Hydrogels Using Raman Spectroscopy
title_full_unstemmed Label-Free Quantification of Nanoencapsulated Piperonyl Esters in Cosmetic Hydrogels Using Raman Spectroscopy
title_short Label-Free Quantification of Nanoencapsulated Piperonyl Esters in Cosmetic Hydrogels Using Raman Spectroscopy
title_sort label-free quantification of nanoencapsulated piperonyl esters in cosmetic hydrogels using raman spectroscopy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10304590/
https://www.ncbi.nlm.nih.gov/pubmed/37376021
http://dx.doi.org/10.3390/pharmaceutics15061571
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