Different modeling approaches for inline biochemical monitoring over the VLP-making upstream stages using Raman spectroscopy.

Autor: Aragão Tejo Dias V; Laboratório de Engenharia de Bioprocessos, Escola de Artes, Ciências e Humanidades (EACH), Universidade de São Paulo, Rua Arlindo Béttio, 1000, CEP 03828-000, São Paulo, SP, Brazil., Oliveira Guardalini LG; Laboratório de Biotecnologia Viral, Instituto Butantan, Av Vital Brasil 1500, CEP 05503-900 São Paulo, SP, Brazil., Leme J; Laboratório de Biotecnologia Viral, Instituto Butantan, Av Vital Brasil 1500, CEP 05503-900 São Paulo, SP, Brazil., Consoni Bernardino T; Laboratório de Biotecnologia Viral, Instituto Butantan, Av Vital Brasil 1500, CEP 05503-900 São Paulo, SP, Brazil., da Silveira SR; Pensalab, Rua Minerva, 129 - Perdizes, CEP: 05007-030 São Paulo, SP, Brazil., Tonso A; Laboratório de Células Animais, Departamento de Engenharia Química, Escola Politécnica, Universidade de São Paulo, Av. Prof. Luciano Gualberto, travessa do Politécnico, 380, 05508-010 São Paulo, SP, Brazil., Attie Calil Jorge S; Laboratório de Biotecnologia Viral, Instituto Butantan, Av Vital Brasil 1500, CEP 05503-900 São Paulo, SP, Brazil., Fernández Núñez EG; Laboratório de Engenharia de Bioprocessos, Escola de Artes, Ciências e Humanidades (EACH), Universidade de São Paulo, Rua Arlindo Béttio, 1000, CEP 03828-000, São Paulo, SP, Brazil. Electronic address: egfnunez@usp.br.
Jazyk: angličtina
Zdroj: Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy [Spectrochim Acta A Mol Biomol Spectrosc] 2024 Nov 05; Vol. 320, pp. 124638. Date of Electronic Publication: 2024 Jun 10.
DOI: 10.1016/j.saa.2024.124638
Abstrakt: This work aimed to set inline Raman spectroscopy models to monitor biochemically (viable cell density, cell viability, glucose, lactate, glutamine, glutamate, and ammonium) all upstream stages of a virus-like particle-making process. Linear (Partial least squares, PLS; Principal components regression, PCR) and nonlinear (Artificial neural networks, ANN; supported vector machine, SVM) modeling approaches were assessed. The nonlinear models, ANN and SVM, were the more suitable models with the lowest absolute errors. The mean absolute error of the best models within the assessed parameter ranges for viable cell density (0.01-8.83 × 10 6 cells/mL), cell viability (1.3-100.0 %), glucose (5.22-10.93 g/L), lactate (18.6-152.7 mg/L), glutamine (158-1761 mg/L), glutamate (807.6-2159.7 mg/L), and ammonium (62.8-117.8 mg/L) were 1.55 ± 1.37 × 10 6 cells/mL (ANN), 5.01 ± 4.93 % (ANN), 0.27 ± 0.22 g/L (SVM), 4.7 ± 2.6 mg/L (SVM), 51 ± 49 mg/L (ANN), 57 ± 39 mg/L (SVM) and 2.0 ± 1.8 mg/L (ANN), respectively. The errors achieved, and best-fitted models were like those for the same bioprocess using offline data and others, which utilized inline spectra for mammalian cell lines as a host.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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