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Chemometrics and analytical blank on the at-line monitoring of Zika-VLP production using near-infrared spectroscopy

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Rabello, Julia Publio ; Cavalcante, Paulo Eduardo da Silva ; Leme, Jaci ; Dias, Vinicius Aragao Tejo ; Barrence, Fernanda Angela Correia ; Guardalini, Luis Giovani de Oliveira ; Bernardino, Thaissa Consoni ; Nunes, Robson ; Barros, Iago Henrique ; Tonso, Aldo ; Jorge, Soraia Attie Calil ; Nunez, Eutimio Gustavo Fernandez
Total Authors: 12
Document type: Journal article
Source: SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY; v. 326, p. 12-pg., 2024-10-05.
Abstract

The Zika disease caused by the Zika virus was declared a Public Health Emergency by the World Health Union (WHO), with microcephaly as the most critical consequence. Aiming to reduce the spread of the virus, biopharmaceutical organizations invest in vaccine research and production, based on multiple platforms. A crescent vaccine production approach is based on virus-like particles (VLP), for not having genetic material in its composition, hypoallergenic and non-mutant character. For bioprocess, it is essential to have means of real-time monitoring, which can be assessed using process analysis techniques such as Near-infrared (NIR) spectroscopy, that can be combined with chemometric methods, like Partial-Least Squares (PLS) and Artificial Neural Networks (ANN) for prediction of biochemical variables. This work proposes a biochemical Zika VLP upstream production at-line monitoring model using NIR spectroscopy comparing sampling conditions (with or without cells), analytical blank (air, ultrapure water), and spectra pre-processing approaches. Seven experiments in a benchtop bioreactor using recombinant baculovirus/Sf9 Sf9 insect cell platform in serum-free medium were performed to obtain biochemical and spectral data for chemometrics modeling (PLS and ANN), composed by a random data split (80 % calibration, 20 % validation) for cross-validation of the PLS models and 70 % training, 15 % testing, 15 % validation for ANN. The best models generated in the present work presented an average absolute error of 1.59 x 105 5 cell/mL for density of viable cells, 2.37% for cell viability, 0.25 g/L for glucose, 0.007 g/L for lactate, 0.138 g/L for glutamine, 0.18 g/L for glutamate, 0,003 g/L for ammonium, and 0.014 g/L for potassium. (AU)

FAPESP's process: 23/09463-5 - Laser wavelength and sample conditioning effects on biochemical monitoring of SARS-CoV-2 VLP production upstream stage by Raman spectroscopy
Grantee:Júlia Públio Rabello
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