| Full text | |
| Author(s): Show less - |
Dias, Felipe Moura
;
Teruya, Milena Miyu
;
Camalhonte, Samanta Omae
;
Dias, Vinicius Aragao Tejo
;
Guardalini, Luis Giovani de Oliveira
;
Leme, Jaci
;
Bernardino, Thaissa Consoni
;
Sposito, Felipe S.
;
Dias, Eduardo
;
Astray, Renato Manciny
;
Tonso, Aldo
;
Jorge, Soraia Attie Calil
;
Nunez, Eutimio Gustavo Fernandez
Total Authors: 13
|
| Document type: | Journal article |
| Source: | Bioprocess and Biosystems Engineering; v. N/A, p. 22-pg., 2024-10-09. |
| Abstract | |
The present work focused on inline Raman spectroscopy monitoring of SARS-CoV-2 VLP production using two culture media by fitting chemometric models for biochemical parameters (viable cell density, cell viability, glucose, lactate, glutamine, glutamate, ammonium, and viral titer). For that purpose, linear, partial least square (PLS), and nonlinear approaches, artificial neural network (ANN), were used as correlation techniques to build the models for each variable. ANN approach resulted in better fitting for most parameters, except for viable cell density and glucose, whose PLS presented more suitable models. Both were statistically similar for ammonium. The mean absolute error of the best models, within the quantified value range for viable cell density (375,000-1,287,500 cell/mL), cell viability (29.76-100.00%), glucose (8.700-10.500 g/), lactate (0.019-0.400 g/L), glutamine (0.925-1.520 g/L), glutamate (0.552-1.610 g/L), viral titer (no virus quantified-7.505 log10 PFU/mL) and ammonium (0.0074-0.0478 g/L) were, respectively, 41,533 +/- 45,273 cell/mL (PLS), 1.63 +/- 1.54% (ANN), 0.058 +/- 0.065 g/L (PLS), 0.007 +/- 0.007 g/L (ANN), 0.007 +/- 0.006 g/L (ANN), 0.006 +/- 0.006 g/L (ANN), 0.211 +/- 0.221 log10 PFU/mL (ANN), and 0.0026 +/- 0.0026 g/L (PLS) or 0.0027 +/- 0.0034 g/L (ANN). The correlation accuracy, errors, and best models obtained are in accord with studies, both online and offline approaches while using the same insect cell/baculovirus expression system or different cell host. Besides, the biochemical tracking throughout bioreactor runs using the models showed suitable profiles, even using two different culture media. (AU) | |
| FAPESP's process: | 23/14085-0 - Online monitoring of the SARS-CoV-2 VLP bioreactor production process by Raman spectroscopy |
| Grantee: | Milena Miyu Teruya |
| Support Opportunities: | Scholarships in Brazil - Scientific Initiation |
| FAPESP's process: | 22/04711-8 - Off-line monitoring of the rabies VLP production bioprocess by Raman spectroscopy |
| Grantee: | Vinícius Aragão Tejo Dias |
| Support Opportunities: | Scholarships in Brazil - Scientific Initiation |
| FAPESP's process: | 22/02713-3 - Establishment of scalable bioprocesses for producing virus-like particles |
| Grantee: | Eutimio Gustavo Fernández Núñez |
| Support Opportunities: | Research Grants - Initial Project |
| FAPESP's process: | 21/14451-0 - Monitoring of SARS-CoV-2 VLP production bioprocess by mid-infrared spectroscopy |
| Grantee: | Felipe Moura Dias |
| Support Opportunities: | Scholarships in Brazil - Master |
| FAPESP's process: | 20/05264-0 - SARS-CoV-2 VLP production |
| Grantee: | Soraia Attie Calil Jorge |
| Support Opportunities: | Regular Research Grants |