Surface-enhanced Raman scattering (SERS) is a powerful and sensitive technique for the detection of fingerprint signals of molecules and for the investigation of a series of surface chemical reactions. Many studies introduced quantitative applications of SERS in various fields, and several SERS methods have been implemented for each specific application, ranging in performance characteristics, analytes used, instruments, and analytical matrices. In general, very few methods have been validated according to international guidelines. As a consequence, the application of SERS in highly regulated environments is still considered risky, and the perception of a poorly reproducible and insufficiently robust analytical technique has persistently retarded its routine implementation. Collaborative trials are a type of interlaboratory study (ILS) frequently performed to ascertain the quality of a single analytical method. The idea of an ILS of quantification with SERS arose within the framework of Working Group 1 (WG1) of the EU COST Action BM1401 Raman4Clinics in an effort to overcome the problematic perception of quantitative SERS methods. Here, we report the first interlaboratory SERS study ever conducted, involving 15 laboratories and 44 researchers. In this study, we tried to define a methodology to assess the reproducibility and trueness of a quantitative SERS method and to compare different methods. In our opinion, this is a first important step toward a “standardization” process of SERS protocols, not proposed by a single laboratory but by a larger community.

The variable configuration of Raman spectroscopic platforms is one of the major obstacles in establishing Raman spectroscopy as a valuable physicochemical method within real-world scenarios such as clinical diagnostics. For such real world applications like diagnostic classification, the models should ideally be usable to predict data from different setups. Whether it is done by training a rugged model with data from many setups or by a primary-replica strategy where models are developed on a 'primary' setup and the test data are generated on 'replicate' setups, this is only possible if the Raman spectra from different setups are consistent, reproducible, and comparable. However, Raman spectra can be highly sensitive to the measurement conditions, and they change from setup to setup even if the same samples are measured. Although increasingly recognized as an issue, the dependence of the Raman spectra on the instrumental configuration is far from being fully understood and great effort is needed to address the resulting spectral variations and to correct for them. To make the severity of the situation clear, we present a round robin experiment investigating the comparability of 35 Raman spectroscopic devices with different configurations in 15 institutes within seven European countries from the COST (European Cooperation in Science and Technology) action Raman4clinics. The experiment was developed in a fashion that allows various instrumental configurations ranging from highly confocal setups to fibre-optic based systems with different excitation wavelengths. We illustrate the spectral variations caused by the instrumental configurations from the perspectives of peak shifts, intensity variations, peak widths, and noise levels. We conclude this contribution with recommendations that may help to improve the inter-laboratory studies.

Background: Monitoring the transcutaneous permeation of exogenous molecules using conventional techniques generally requires long pre-analytical preparation or labelling of samples. However, Raman spectroscopy is a label-free and nondestructive method which provides spatial distribution of tracked actives in skin. The aim of our study was to prove the interest of Raman imaging coupled with multivariate curve resolution alternating least square (MCR-ALS) analysis in monitoring retinol penetration into frozen and living human skin. Materials and Methods:After topical treatment of skin samples by free or encapsulated retinol, thin cross sections were analysed by Raman imaging (up to 100 µm depth). Mann-Whitney test was used to identify retinol spectroscopic markers in skin. MCR-ALS was used to estimate retinol contribution in Raman spectral images.Heat maps were constructed to compare the distribution of free and encapsulated retinol in skin models. Results:We identified the bands at 1158, 1196 and 1591 cm -1 as specific features for monitoring retinol in skin. Moreover, our MCR-ALS results showed an improvement of retinol penetration (up to 30 µm depth) with the encapsulated form as well as storage reservoir formation in stratum corneum, for each skin model. Finally, greater retinol penetration into living skin was observed. Conclusion:This study shows a proof of concept for the evaluation of retinol penetration in skin using Raman imaging coupled with MCR-ALS. This concept needs to be validated on more subjects to include inter-individual variability but also other factors affecting skin permeation (age, sex, pH, etc). Our study can be extended to other actives.

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Vibrational data of biological samples require appropriate pre-processing for ensuring relevant interpretation. Here, mathematical criteria (validity indices) are used to select how to normalize Raman data collected in the protein glycation context.

Correction for ‘Towards normalization selection of Raman data in the context of protein glycation: application of validity indices to PCA processed spectra’ by Fatima Alsamad et al., Analyst, 2020, DOI: 10.1039/c9an02155h.

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