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

TALANTA

卷:217

Article

Dowek, Antoine^1,2  Le, Laetitia Minh Mai^1,2  Rohmer, Tom^3,4  Legrand, Francois-Xavier⁵  Remita, Hynd⁶  Lampre, Isabelle⁶  Tfayli, Ali²  Lavielle, Marc^3,4  Caudron, Eric^1,2 

[1] Ctr Univ Paris, Hop Europeen Georges Pompidou, AP HP, Serv Pharm, 20 Rue Leblanc, F-75015 Paris, France

[2] Univ Paris Saclay, Lipides Syst Analyt & Biol, F-92296 Chatenay Malabry, France

[3] INRIA, Rocquencourt, France

[4] Ecole Polytech, Inst Polytech Paris, CNRS, CMAP, Paris, France

[5] Univ Paris Saclay, Inst Galien Paris Sud, CNRS, F-92296 Chatenay Malabry, France

[6] Univ Paris Saclay, Inst Chim Phys, CNRS, UMR 8000, F-91405 Orsay, France

关键词: Surface enhanced Raman spectroscopy;    Quantitative analysis;    Antineoplastic agents;    Nanoparticle polydispersity;    Non-linear regression;   

DOI  :  10.1016/j.talanta.2020.121040

来源: Elsevier

【 摘 要 】

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.

【 授权许可】

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