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,...
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| Veröffentlicht in: | Talanta (Oxford) 2020-09, Vol.217, p.121040, Article 121040 |
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| creator | Dowek, Antoine Lê, Laetitia Minh Mai Rohmer, Tom Legrand, François-Xavier Remita, Hynd Lampre, Isabelle Tfayli, Ali Lavielle, Marc Caudron, Eric |
| description | 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 |
| doi_str_mv | 10.1016/j.talanta.2020.121040 |
| format | Article |
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•Quantitative analysis by Surface Enhanced Raman Spectroscopy.•Exaltation of Raman signal of 5-fluorouracil more than 104.•A predictive model dealing with variability of nanoparticle suspensions.•Predictive performance significantly improved by nearest neighbors algorithm.</description><identifier>ISSN: 0039-9140</identifier><identifier>EISSN: 1873-3573</identifier><identifier>DOI: 10.1016/j.talanta.2020.121040</identifier><identifier>PMID: 32498908</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Analytical chemistry ; Antineoplastic agents ; Antineoplastic Agents - analysis ; Chemical Sciences ; Classical Analysis and ODEs ; Fluorouracil - analysis ; Humans ; Least-Squares Analysis ; Material chemistry ; Mathematics ; Metal Nanoparticles - chemistry ; Nanoparticle polydispersity ; Non-linear regression ; Nonlinear Dynamics ; Particle Size ; Quantitative analysis ; Silver - chemistry ; Spectrum Analysis, Raman ; Surface enhanced Raman spectroscopy ; Surface Properties</subject><ispartof>Talanta (Oxford), 2020-09, Vol.217, p.121040, Article 121040</ispartof><rights>2020 Elsevier B.V.</rights><rights>Copyright © 2020 Elsevier B.V. All rights reserved.</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c446t-865868544496ba236c6f55027356c5096cd1df683cd556e30d8df29303c6b3023</citedby><cites>FETCH-LOGICAL-c446t-865868544496ba236c6f55027356c5096cd1df683cd556e30d8df29303c6b3023</cites><orcidid>0000-0002-7271-7284 ; 0000-0003-3698-9327 ; 0000-0003-2186-9592 ; 0000-0002-9222-2852 ; 0000-0002-0834-1083 ; 0000-0003-0027-8638 ; 0000-0002-4751-2324</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0039914020303313$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,776,780,881,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32498908$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://hal.science/hal-02557279$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Dowek, Antoine</creatorcontrib><creatorcontrib>Lê, Laetitia Minh Mai</creatorcontrib><creatorcontrib>Rohmer, Tom</creatorcontrib><creatorcontrib>Legrand, François-Xavier</creatorcontrib><creatorcontrib>Remita, Hynd</creatorcontrib><creatorcontrib>Lampre, Isabelle</creatorcontrib><creatorcontrib>Tfayli, Ali</creatorcontrib><creatorcontrib>Lavielle, Marc</creatorcontrib><creatorcontrib>Caudron, Eric</creatorcontrib><title>A mathematical approach to deal with nanoparticle polydispersity in surface enhanced Raman spectroscopy to quantify antineoplastic agents</title><title>Talanta (Oxford)</title><addtitle>Talanta</addtitle><description>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.
[Display omitted]
•Quantitative analysis by Surface Enhanced Raman Spectroscopy.•Exaltation of Raman signal of 5-fluorouracil more than 104.•A predictive model dealing with variability of nanoparticle suspensions.•Predictive performance significantly improved by nearest neighbors algorithm.</description><subject>Analytical chemistry</subject><subject>Antineoplastic agents</subject><subject>Antineoplastic Agents - analysis</subject><subject>Chemical Sciences</subject><subject>Classical Analysis and ODEs</subject><subject>Fluorouracil - analysis</subject><subject>Humans</subject><subject>Least-Squares Analysis</subject><subject>Material chemistry</subject><subject>Mathematics</subject><subject>Metal Nanoparticles - chemistry</subject><subject>Nanoparticle polydispersity</subject><subject>Non-linear regression</subject><subject>Nonlinear Dynamics</subject><subject>Particle Size</subject><subject>Quantitative analysis</subject><subject>Silver - chemistry</subject><subject>Spectrum Analysis, Raman</subject><subject>Surface enhanced Raman spectroscopy</subject><subject>Surface Properties</subject><issn>0039-9140</issn><issn>1873-3573</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFUU1r3DAUFKWh2ab9CS269uCtPizZPpUlpE1gIRDas3grybUWr6VK2gT_hPzryjjNtRc9GGae3swg9ImSLSVUfj1uM4wwZdgywgrGKKnJG7ShbcMrLhr-Fm0I4V3V0ZpcovcpHQkhjBP-Dl1yVndtR9oNet7hE-TBlsdpGDGEED3oAWePjS3Ak8sDnmDyAWKhjBYHP87GpWBjcnnGbsLpHHvQFttpgElbgx_gBAUOVufok_ZhXvb9OZd7XT_jZUzWhxFSWYnht51y-oAuehiT_fgyr9Cv7zc_r2-r_f2Pu-vdvtJ1LXPVStHKVtR13ckDMC617IUgrOFCakE6qQ01vWy5NkJIy4lpTc-64lvLAy8BXKEv694BRhWiO0GclQenbnd7tWCECdGwpnukhStWri42UrT9q4AStdSgjuqlBrXUoNYaiu7zqgvnw8maV9W_3Avh20qwxemjs1El7eySnYslNGW8-88XfwHcK51t</recordid><startdate>20200901</startdate><enddate>20200901</enddate><creator>Dowek, Antoine</creator><creator>Lê, Laetitia Minh Mai</creator><creator>Rohmer, Tom</creator><creator>Legrand, François-Xavier</creator><creator>Remita, Hynd</creator><creator>Lampre, Isabelle</creator><creator>Tfayli, Ali</creator><creator>Lavielle, Marc</creator><creator>Caudron, Eric</creator><general>Elsevier B.V</general><general>Elsevier</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0002-7271-7284</orcidid><orcidid>https://orcid.org/0000-0003-3698-9327</orcidid><orcidid>https://orcid.org/0000-0003-2186-9592</orcidid><orcidid>https://orcid.org/0000-0002-9222-2852</orcidid><orcidid>https://orcid.org/0000-0002-0834-1083</orcidid><orcidid>https://orcid.org/0000-0003-0027-8638</orcidid><orcidid>https://orcid.org/0000-0002-4751-2324</orcidid></search><sort><creationdate>20200901</creationdate><title>A mathematical approach to deal with nanoparticle polydispersity in surface enhanced Raman spectroscopy to quantify antineoplastic agents</title><author>Dowek, Antoine ; Lê, Laetitia Minh Mai ; Rohmer, Tom ; Legrand, François-Xavier ; Remita, Hynd ; Lampre, Isabelle ; Tfayli, Ali ; Lavielle, Marc ; Caudron, Eric</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c446t-865868544496ba236c6f55027356c5096cd1df683cd556e30d8df29303c6b3023</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Analytical chemistry</topic><topic>Antineoplastic agents</topic><topic>Antineoplastic Agents - analysis</topic><topic>Chemical Sciences</topic><topic>Classical Analysis and ODEs</topic><topic>Fluorouracil - analysis</topic><topic>Humans</topic><topic>Least-Squares Analysis</topic><topic>Material chemistry</topic><topic>Mathematics</topic><topic>Metal Nanoparticles - chemistry</topic><topic>Nanoparticle polydispersity</topic><topic>Non-linear regression</topic><topic>Nonlinear Dynamics</topic><topic>Particle Size</topic><topic>Quantitative analysis</topic><topic>Silver - chemistry</topic><topic>Spectrum Analysis, Raman</topic><topic>Surface enhanced Raman spectroscopy</topic><topic>Surface Properties</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dowek, Antoine</creatorcontrib><creatorcontrib>Lê, Laetitia Minh Mai</creatorcontrib><creatorcontrib>Rohmer, Tom</creatorcontrib><creatorcontrib>Legrand, François-Xavier</creatorcontrib><creatorcontrib>Remita, Hynd</creatorcontrib><creatorcontrib>Lampre, Isabelle</creatorcontrib><creatorcontrib>Tfayli, Ali</creatorcontrib><creatorcontrib>Lavielle, Marc</creatorcontrib><creatorcontrib>Caudron, Eric</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>Talanta (Oxford)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dowek, Antoine</au><au>Lê, Laetitia Minh Mai</au><au>Rohmer, Tom</au><au>Legrand, François-Xavier</au><au>Remita, Hynd</au><au>Lampre, Isabelle</au><au>Tfayli, Ali</au><au>Lavielle, Marc</au><au>Caudron, Eric</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A mathematical approach to deal with nanoparticle polydispersity in surface enhanced Raman spectroscopy to quantify antineoplastic agents</atitle><jtitle>Talanta (Oxford)</jtitle><addtitle>Talanta</addtitle><date>2020-09-01</date><risdate>2020</risdate><volume>217</volume><spage>121040</spage><pages>121040-</pages><artnum>121040</artnum><issn>0039-9140</issn><eissn>1873-3573</eissn><abstract>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.
[Display omitted]
•Quantitative analysis by Surface Enhanced Raman Spectroscopy.•Exaltation of Raman signal of 5-fluorouracil more than 104.•A predictive model dealing with variability of nanoparticle suspensions.•Predictive performance significantly improved by nearest neighbors algorithm.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>32498908</pmid><doi>10.1016/j.talanta.2020.121040</doi><orcidid>https://orcid.org/0000-0002-7271-7284</orcidid><orcidid>https://orcid.org/0000-0003-3698-9327</orcidid><orcidid>https://orcid.org/0000-0003-2186-9592</orcidid><orcidid>https://orcid.org/0000-0002-9222-2852</orcidid><orcidid>https://orcid.org/0000-0002-0834-1083</orcidid><orcidid>https://orcid.org/0000-0003-0027-8638</orcidid><orcidid>https://orcid.org/0000-0002-4751-2324</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Analytical chemistry Antineoplastic agents Antineoplastic Agents - analysis Chemical Sciences Classical Analysis and ODEs Fluorouracil - analysis Humans Least-Squares Analysis Material chemistry Mathematics Metal Nanoparticles - chemistry Nanoparticle polydispersity Non-linear regression Nonlinear Dynamics Particle Size Quantitative analysis Silver - chemistry Spectrum Analysis, Raman Surface enhanced Raman spectroscopy Surface Properties |
| title | A mathematical approach to deal with nanoparticle polydispersity in surface enhanced Raman spectroscopy to quantify antineoplastic agents |
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