{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T21:51:49Z","timestamp":1781646709994,"version":"3.54.5"},"reference-count":20,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T00:00:00Z","timestamp":1774483200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T00:00:00Z","timestamp":1774483200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100005639","name":"Universidade De S\u00e3o Paulo","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100005639","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Bioprocess Biosyst Eng"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    The spectral preprocessing step of data derived from Raman spectroscopy is important for chemometric models\u2019 calibration, which allows real-time monitoring of pharmaceutical bioprocesses. Thus, the present work aimed to establish, with statistical criteria, the best combination of spectral filters for the biochemical monitoring of the baculovirus\/\n                    <jats:italic>Sf9<\/jats:italic>\n                    insect cell system. The production of rabies virus-like particles was used as a model. Combining moving window smoothing and offset baseline correction spectral filters demonstrated the highest efficacy in biochemically monitoring the baculovirus\/\n                    <jats:italic>Sf9<\/jats:italic>\n                    insect cell system using Raman spectroscopic data and Partial Least Squares regression. However, when applying Artificial Neural Network modeling, a different set of filters proved more effective: wavelet denoise spectral smoothing, asymmetric least square baseline correction, standard normal variate normalization, and quadratic first derivative. The simulation results demonstrate that by following these guidelines for spectral preprocessing, cell viability, glucose, lactate, glutamine, glutamate, and ammonium can be satisfactorily monitored in real-time, but not the density of viable cells. The absolute errors for cell viability, glucose, lactate, glutamine, glutamate, and ammonium were lower than 12%, 0.47\u00a0g L\n                    <jats:sup>\u2212\u20091<\/jats:sup>\n                    , 8.95 mg L\n                    <jats:sup>\u2212\u20091<\/jats:sup>\n                    , 0.11\u00a0g L\n                    <jats:sup>\u2212\u20091<\/jats:sup>\n                    , 0.10\u00a0g L\n                    <jats:sup>\u2212\u20091<\/jats:sup>\n                    , 3.21 mg L\n                    <jats:sup>\u2212\u20091<\/jats:sup>\n                    , respectively, which are suitable for bioprocess in-line monitoring and control through a soft sensor.\n                  <\/jats:p>","DOI":"10.1007\/s00449-026-03301-1","type":"journal-article","created":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T08:59:00Z","timestamp":1774515540000},"page":"999-1013","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Selecting Raman spectra filtering based on an exhaustive statistical approach for inline bioprocesses monitoring using Sf9 insect cells"],"prefix":"10.1007","volume":"49","author":[{"given":"Milena Miyu","family":"Teruya","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J\u00falia","family":"P\u00fablio Rabello","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luis Giovani","family":"Oliveira Guardalini","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fernanda Angela","family":"Correia Barrence","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eutimio Gustavo","family":"Fern\u00e1ndez N\u00fa\u00f1ez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,3,26]]},"reference":[{"key":"3301_CR1","doi-asserted-by":"publisher","first-page":"651","DOI":"10.1007\/s00216-016-0068-x","volume":"409","author":"J Cla\u00dfen","year":"2017","unstructured":"Cla\u00dfen J, Aupert F, Reardon KF et al (2017) Spectroscopic sensors for in-line bioprocess monitoring in research and pharmaceutical industrial application. Anal Bioanal Chem 409:651\u2013666. https:\/\/doi.org\/10.1007\/s00216-016-0068-x","journal-title":"Anal Bioanal Chem"},{"key":"3301_CR2","doi-asserted-by":"publisher","first-page":"969","DOI":"10.1007\/s00216-021-03727-4","volume":"414","author":"KA Esmonde-White","year":"2022","unstructured":"Esmonde-White KA, Cuellar M, Lewis IR (2022) The role of Raman spectroscopy in biopharmaceuticals from development to manufacturing. Anal Bioanal Chem 414:969\u2013991. https:\/\/doi.org\/10.1007\/s00216-021-03727-4","journal-title":"Anal Bioanal Chem"},{"key":"3301_CR3","doi-asserted-by":"publisher","first-page":"30","DOI":"10.3390\/instruments7040030","volume":"7","author":"E-A Rusu","year":"2023","unstructured":"Rusu E-A, Baia M (2023) Moving from Raman Spectroscopy Lab towards Analytical Applications: A Review of Interlaboratory Studies. Instruments 7:30. https:\/\/doi.org\/10.3390\/instruments7040030","journal-title":"Instruments"},{"key":"3301_CR4","doi-asserted-by":"publisher","first-page":"1831","DOI":"10.1002\/bit.28688","volume":"121","author":"X Dong","year":"2024","unstructured":"Dong X, Yan X, Wan Y et al (2024) Enhancing real-time cell culture monitoring: Automated Raman model optimization with Taguchi method. Biotechnol Bioeng 121:1831\u20131845. https:\/\/doi.org\/10.1002\/bit.28688","journal-title":"Biotechnol Bioeng"},{"key":"3301_CR5","doi-asserted-by":"publisher","first-page":"109013","DOI":"10.1016\/j.bej.2023.109013","volume":"198","author":"LG Oliveira Guardalini","year":"2023","unstructured":"Oliveira Guardalini LG, Arag\u00e3o Tejo Dias V, Leme J et al (2023) Comparison of chemometric models using Raman spectroscopy for offline biochemical monitoring throughout the VLP-making upstream process. Biochem Eng J 198:109013. https:\/\/doi.org\/10.1016\/j.bej.2023.109013","journal-title":"Biochem Eng J"},{"key":"3301_CR6","doi-asserted-by":"publisher","first-page":"5426","DOI":"10.1038\/s41596-021-00620-3","volume":"16","author":"S Guo","year":"2021","unstructured":"Guo S, Popp J, Bocklitz T (2021) Chemometric analysis in Raman spectroscopy from experimental design to machine learning\u2013based modeling. Nat Protoc 16:5426\u20135459. https:\/\/doi.org\/10.1038\/s41596-021-00620-3","journal-title":"Nat Protoc"},{"key":"3301_CR7","doi-asserted-by":"publisher","first-page":"731","DOI":"10.1002\/jrs.5835","volume":"51","author":"MT Gebrekidan","year":"2020","unstructured":"Gebrekidan MT, Knipfer C, Braeuer AS (2020) Vector casting for noise reduction. J Raman Spectrosc 51:731\u2013743. https:\/\/doi.org\/10.1002\/jrs.5835","journal-title":"J Raman Spectrosc"},{"key":"3301_CR8","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1038\/s41377-024-01394-5","volume":"13","author":"J Hu","year":"2024","unstructured":"Hu J, Chen GJ, Xue C et al (2024) RSPSSL: A novel high-fidelity Raman spectral preprocessing scheme to enhance biomedical applications and chemical resolution visualization. Light Sci Appl 13:52. https:\/\/doi.org\/10.1038\/s41377-024-01394-5","journal-title":"Light Sci Appl"},{"key":"3301_CR9","doi-asserted-by":"publisher","unstructured":"Guardalini LGO, Leme J, da Silva Cavalcante PE et al (2023) Sf9 Cell Metabolism Throughout the Recombinant Baculovirus and Rabies Virus-Like Particles Production in Two Culture Systems. Mol Biotechnol. https:\/\/doi.org\/10.1007\/s12033-023-00759-2","DOI":"10.1007\/s12033-023-00759-2"},{"key":"3301_CR10","doi-asserted-by":"publisher","first-page":"1134","DOI":"10.3390\/v7031134","volume":"7","author":"H Kang","year":"2015","unstructured":"Kang H, Qi Y, Wang H et al (2015) Chimeric Rabies Virus-Like Particles Containing Membrane-Anchored GM-CSF Enhances the Immune Response against Rabies Virus. Viruses 7:1134\u20131152. https:\/\/doi.org\/10.3390\/v7031134","journal-title":"Viruses"},{"key":"3301_CR11","doi-asserted-by":"publisher","first-page":"124638","DOI":"10.1016\/j.saa.2024.124638","volume":"320","author":"TDV Arag\u00e3o","year":"2024","unstructured":"Arag\u00e3o TDV, Oliveira Guardalini LG, Leme J et al (2024) Different modeling approaches for inline biochemical monitoring over the VLP-making upstream stages using Raman spectroscopy. Spectrochim Acta Mol Biomol Spectrosc 320:124638. https:\/\/doi.org\/10.1016\/j.saa.2024.124638","journal-title":"Spectrochim Acta Mol Biomol Spectrosc"},{"key":"3301_CR12","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1016\/j.jbiotec.2022.12.009","volume":"363","author":"LG Oliveira Guardalini","year":"2023","unstructured":"Oliveira Guardalini LG, da Silva Cavalcante PE, Leme J et al (2023) Biochemical monitoring throughout all stages of rabies virus-like particles production by Raman spectroscopy using global models. J Biotechnol 363:19\u201331. https:\/\/doi.org\/10.1016\/j.jbiotec.2022.12.009","journal-title":"J Biotechnol"},{"key":"3301_CR13","doi-asserted-by":"publisher","first-page":"535","DOI":"10.1002\/bit.27997","volume":"119","author":"DA Zavala-Ortiz","year":"2022","unstructured":"Zavala-Ortiz DA, Denner A, Aguilar\u2010Uscanga MG et al (2022) Comparison of partial least square, artificial neural network, and support vector regressions for real\u2010time monitoring of CHO cell culture processes using in situ near\u2010infrared spectroscopy. Biotechnol Bioeng 119:535\u2013549. https:\/\/doi.org\/10.1002\/bit.27997","journal-title":"Biotechnol Bioeng"},{"key":"3301_CR14","doi-asserted-by":"publisher","first-page":"1215","DOI":"10.1002\/bit.23023","volume":"108","author":"NR Abu-Absi","year":"2011","unstructured":"Abu-Absi NR, Kenty BM, Cuellar ME et al (2011) Real time monitoring of multiple parameters in mammalian cell culture bioreactors using an in-line Raman spectroscopy probe. Biotechnol Bioeng 108:1215\u20131221. https:\/\/doi.org\/10.1002\/bit.23023","journal-title":"Biotechnol Bioeng"},{"key":"3301_CR15","doi-asserted-by":"publisher","first-page":"108063","DOI":"10.1016\/j.bej.2021.108063","volume":"172","author":"G Chen","year":"2021","unstructured":"Chen G, Hu J, Qin Y, Zhou W (2021) Viable cell density on-line auto-control in perfusion cell culture aided by in-situ Raman spectroscopy. Biochem Eng J 172:108063. https:\/\/doi.org\/10.1016\/j.bej.2021.108063","journal-title":"Biochem Eng J"},{"key":"3301_CR16","doi-asserted-by":"publisher","first-page":"8890","DOI":"10.3390\/app14198890","volume":"14","author":"X Dong","year":"2024","unstructured":"Dong X, Yan X, Qu H (2024) Improving Raman-Based Models for Real-Time Monitoring the CHO Cell Culture Process with Effective Variable Selection Strategies. Appl Sci 14:8890. https:\/\/doi.org\/10.3390\/app14198890","journal-title":"Appl Sci"},{"key":"3301_CR17","doi-asserted-by":"publisher","first-page":"535","DOI":"10.1002\/bit.27997","volume":"119","author":"DA Zavala-Ortiz","year":"2022","unstructured":"Zavala-Ortiz DA, Denner A, Aguilar\u2010Uscanga MG et al (2022) Comparison of partial least square, artificial neural network, and support vector regressions for real\u2010time monitoring of CHO cell culture processes using in situ near\u2010infrared spectroscopy. Biotechnol Bioeng 119:535\u2013549. https:\/\/doi.org\/10.1002\/bit.27997","journal-title":"Biotechnol Bioeng"},{"key":"3301_CR18","doi-asserted-by":"publisher","unstructured":"Abu-Absi NR, Kenty BM, Cuellar ME et al (2011) Real time monitoring of multiple parameters in mammalian cell culturebioreactors using an in-line Raman spectroscopy probe. Biotechnol Bioeng 108:1215\u20131221 https:\/\/doi.org\/10.1002\/bit.23023","DOI":"10.1002\/bit.23023"},{"key":"3301_CR19","doi-asserted-by":"publisher","unstructured":"Chen G, Hu J, Qin Y, Zhou W (2021) Viable cell density on-line auto-control in perfusion cell culture aided by in-situ Raman spectroscopy. Biochem Eng J 172:108063 https:\/\/doi.org\/10.1016\/j.bej.2021.108063","DOI":"10.1016\/j.bej.2021.108063"},{"key":"3301_CR20","doi-asserted-by":"publisher","unstructured":"Dong X, Yan X, Qu H (2024) Improving Raman-Based Models for Real-Time Monitoring the CHO Cell Culture Processwith Effective Variable Selection Strategies. Applied Sciences 14:8890 https:\/\/doi.org\/10.3390\/app14198890","DOI":"10.3390\/app14198890"}],"container-title":["Bioprocess and Biosystems Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00449-026-03301-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00449-026-03301-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00449-026-03301-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T20:54:21Z","timestamp":1781643261000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00449-026-03301-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,26]]},"references-count":20,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2026,4]]}},"alternative-id":["3301"],"URL":"https:\/\/doi.org\/10.1007\/s00449-026-03301-1","relation":{},"ISSN":["1615-7591","1615-7605"],"issn-type":[{"value":"1615-7591","type":"print"},{"value":"1615-7605","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,26]]},"assertion":[{"value":"23 September 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 February 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 March 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"No research involving humans and\/or animals was carried out.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}