Optimization of experimental conditions by surface enhanced Raman Scattering (SERS) spectroscopy with gold nanoparticles suspensions

Surface Enhanced Raman Scattering (SERS) spectroscopy is a rapid and innovative analysis technique involving metallic nanoparticles (NPs). The interaction between NPs and norepinephrine gives an exaltation of the Raman signal under certain experimental conditions. The control of the signal exaltation, crucial for sensitive analyses, remains one of the main limitations of this technique. The aim of this work is to optimize the exaltation conditions for an optimal SERS signal at two concentrations of norepinephrine (NOR) and spherical gold NPs in suspension. This first work will fix the optimal experimental conditions essential for the development of robust discriminant and quantitative analysis of catecholamine. Two complete 3-factors 3-levels experiment designs were performed at 20 µg.mL^-1 and 100 µg.mL^-1 norepinephrine concentrations, each experiment being repeated 3 times. The optimization factors were the process of synthesis (variation of the quantity of gold and citrate used for the three synthesis SA, SB and SC) and HCl (0.3 M, 0.5 M, 0.7 M) as well as the volume ratio of NPs and norepinephrine (0.5, 2, 3.5) for SERS acquisition. Spectral acquisitions were performed with a handheld Raman spectrometer with an excitation source at 785 nm. For each sample, 31 acquisitions were realized during 3 s every 8 s. The optimization parameter was the intensity of the characteristic band of norepinephrine at 1280 cm^-1. A total of 5,042 spectra were acquired and the pre-treatment selected for all spectra was asymmetric least square combined to a smoothing of Savistsky Golay (ALS - SG). The optimal contact time between norepinephrine and NPs depends on the experimental conditions and was determined for each experiment according to the mean intensity between the three replicates. After interpretation of the experimental designs, the optimal conditions retained were the quantity of gold corresponding to SA and the HCl concentration 0.7 M for the two concentrations of norepinephrine. Indeed, the optimal volume ratio depend on the NOR concentration.

Discriminative and quantitative analysis of norepinephrine and epinephrine by surface-enhanced Raman spectroscopy with gold nanoparticle suspensions

Surface-enhanced Raman spectroscopy (SERS) is a powerful analytical technique capable of increasing the Raman signal of an analyte using specific nanostructures. The close contact between those nanostructures, usually a suspension of nanoparticles, and the molecule of interest produces an important exaltation of the intensity of the Raman signal. Even if the exaltation leads to an improvement of Raman spectroscopy sensitivity, the complexity of the SERS signal and the numbers of parameters to be controlled allow the use of SERS for detection rather than quantification. The aim of this study was to develop a robust discriminative and quantitative analysis in accordance with pharmaceutical standards. In this present work, we develop a discriminative and quantitative analysis based on the previous optimized parameters obtained by the design of experiments fixed for norepinephrine (NOR) and extended to epinephrine (EPI) which are two neurotransmitters with very similar structures. Studying the short evolution of the Raman signal intensity over time coupled with chemometric tools allowed the identification of outliers and their removal from the data set. The discriminant analysis showed an excellent separation of EPI and NOR. The comparative analysis of the data showed the superiority of the multivariate analysis after logarithmic transformation. The quantitative analysis allowed the development of robust quantification models from several gold nanoparticle batches with limits of quantification of 32 µg/mL for NOR and below 20 µg/mL for EPI even though no Raman signal is observable for such concentrations. This study improves SERS analysis over ultrasensitive detection for discrimination and quantification using a handheld Raman spectrometer.

A mathematical approach to deal with nanoparticle polydispersity in surface enhanced Raman spectroscopy to quantify antineoplastic agents

Antineoplastic agents are, for most of them, highly toxic drugs prepared at hospital following individualized prescription. To protect patients and healthcare workers, it is important to develop analytical tools able to identify and quantify such drugs on a wide concentration range. In this context, surface enhanced Raman spectroscopy (SERS) has been tested as a specific and sensitive technique. Despite the standardization of the nanoparticle synthesis, a polydispersity of nanoparticles in the suspension and a lack of reproducibility persist. This study focuses on the development of a new mathematical approach to deal with this nanoparticle polydispersity and its consequences on SERS signal variability through the feasibility of 5-fluorouracil (5FU) quantification using silver nanoparticles (AgNPs) and a handled Raman spectrophotometer. Variability has been maximized by synthetizing six different batches of AgNPs for an average size of 24.9 nm determined by transmission electron microscopy, with residual standard deviation of 17.0%. Regarding low performances of the standard multivariate data processing, an alternative approach based on the nearest neighbors were developed to quantify 5FU. By this approach, the predictive performance of the 5FU concentration was significantly improved. The mean absolute relative error (MARE) decreased from 16.8% with the traditional approach based on PLS regression to 6.30% with the nearest neighbors approach (p-value < 0.001). This study highlights the importance of developing mathematics adapted to SERS analysis which could be a step to overcome the spectral variability in SERS and thus participate in the development of this technique as an analytical tool in quality control to quantify molecules with good performances, particularly in the pharmaceutical field.