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 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.

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:15

Enthalten in:

Pharmaceutics - 15(2023), 6 vom: 23. Mai

Sprache:

Englisch

Beteiligte Personen:

Elderderi, Suha [VerfasserIn]
Bonnier, Franck [VerfasserIn]
Perse, Xavier [VerfasserIn]
Byrne, Hugh J [VerfasserIn]
Yvergnaux, Florent [VerfasserIn]
Chourpa, Igor [VerfasserIn]
Elbashir, Abdalla A [VerfasserIn]
Munnier, Emilie [VerfasserIn]

Links:

Volltext

Themen:

Alginate nanocarriers
Hydrogels
Journal Article
Label-free quantification
Partial least squares regression
Raman spectroscopy

Anmerkungen:

Date Revised 01.07.2023

published: Electronic

Citation Status PubMed-not-MEDLINE

doi:

10.3390/pharmaceutics15061571

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM358773334