Theme 3.2: Qualitative and quantitative monitoring of pharmaceutical and cosmetic active ingredients

Nanosystems

Quantitative analysis for cosmetology and pharmaceutical research

SERS&Fluo maps of hybrid NPs in cancer cells Fluo map of polymeric NPs delivering an ACI to human hair Raman-PAT of a CHO cells culture in bioreactor - CPP Raman-PAT of a CHO cells culture in bioreactor - CQA
SERS&Fluo maps of hybrid NPs in cancer cells Fluo map of polymeric NPs delivering an ACI to human hair Raman-PAT of a CHO cell culture
in a bioreactor
(Carrouée et al. 2015) (Van Gheluwe PhD thesis, 2021) (Rubini et al. 2025a) (Rubini et al. 2025b)

Objectives

Summary

This theme focuses on the development of modern bioanalytical tools based on molecular optical spectroscopy (Raman, SERS, fluorescence, IR) and separation techniques (UHPLC) in the aim of qualitative and quantitative assessment of complex molecular systems which are relevant in the domains of cosmetology and pharmaceutics.

First of all, it concerns characterization of composition and homogenity of cosmetic and pharmaceutic forms.

For dermo-cosmetic applications, we determine the Active cosmetic ingredient (ACI) distribution within gels and then establish the profiles of its penetration into human skin, in vitro and in vivo.

Confocal spectral imaging (Raman, SERS, fluorescence) algorithms we develop allow to follow quantitatively the active molecules in cancer cells & tissues, within 2D and 3D matrix. In this way, it is possible to monitor the drug delivery and understand its action mechanism.

In clinical context, namely concerning the therapeudic drug monitoring (TDM), we have demonstrated that Quality Control (QC) of clinical solutions can be made both qualitatively and quantitatively, through the walls of the perfusion bag, by means of Raman confocal spectroscopy.

Our expertise in SERS spectroscopy allows us to design and to develop SERS substrates for cancer diagnostics in vitro, through detection of seric biomarkers such as miRNA.

Finally, Raman spectroscopy made through an immersed fiber optic probe can be used in the framework of Process Analytical Technology (PAT), for In-line monitoring of tens of critical parameters of bioprocessing of a recombinant therapeutic antibody by CHO cells cultivated in a bioreactor.

For all these applications, the spectroscopic data treatment is strongly improved thanks to multivariate data analysis (MVDA) and machine learning (ML).

Keywords