Enabling PAT in insect cell bioprocesses: In situ monitoring of recombinant adeno‐associated virus production by fluorescence spectroscopy
Abstract
The process analytical technology (PAT) initiative shifted the bioprocess development mindset towards real‐time monitoring and control tools to measure relevant process variables online, and acting accordingly when undesirable deviations occur. Online monitoring is especially important in lytic production systems in which released proteases and changes in cell physiology are likely to affect product quality attributes, as is the case of the insect cell‐baculovirus expression vector system (IC‐BEVS), a well‐established system for production of viral vectors and vaccines. Here, we applied fluorescence spectroscopy as a real‐time monitoring tool for recombinant adeno‐associated virus (rAAV) production in the IC‐BEVS. Fluorescence spectroscopy is simple, yet sensitive and informative. To overcome the strong fluorescence background of the culture medium and improve predictive ability, we combined artificial neural network models with a genetic algorithm‐based approach to optimize spectra preprocessing. We obtained predictive models for rAAV titer, cell viability and cell concentration with normalized root mean squared errors of 7%, 4%, and 7%, respectively, for leave‐one‐batch‐out cross‐validation. Our approach shows fluorescence spectroscopy allows real‐time determination of the best time of harvest to maintain rAAV infectivity, an important quality attribute, and detection of deviations from the golden batch profile. This methodology can be applied to other biopharmaceuticals produced in the IC‐BEVS, supporting the use of fluorescence spectroscopy as a versatile PAT tool.
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Monitoring of rAAV production culture and prediction of intra- and extracellular rAAV titer with in situ FS spectroscopy and online digital holographic microscopy have been reported.
“Recently, the monitoring of rAAV production culture and prediction of the intra- and extracellular rAAV titer, among other process-related quality attributes, with in situ FS spectroscopy110 and online digital holographic microscopy,111 were reported.”
From Analytical methods for process and product characterization of recombinant adeno-associated virus-based gene therapies (2021) · cites this paper as [110]
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- Authors
- Pais, D. A. M., Portela, R. M. C., Carrondo, M. J. T., Isidro, I. A., & Alves, P. M.
- Affiliations
- Instituto de Biologia Experimental e Tecnológica (PT)
- GlaxoSmithKline (Belgium) (BE)
- Corresponding author
- Alves, Paula M.
- Venue
- Biotechnology and Bioengineering
- Publisher
- Wiley
- Published
- 2019-07-26
- Volume
- 116
- Issue
- 11
- Pages
- 2803-2814
- ISSN
- 0006-3592 (ISSN-L)
- 1097-0290
- OpenAlex
- W2964239069
- Cited by
- 36
- References
- 39
- Citations by year
- 2026: 1 · 2025: 7 · 2024: 4 · 2023: 10 · 2022: 4 · 2021: 5 · 2020: 5
- FWCI
- 1.16
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Biotechnology and Bioengineering (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Fundação para a Ciência e a Tecnologia (PD/BD/105873/2014, EXPL/BBBBIO/1129/2013)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Viral Infectious Diseases and Gene Expression in Insects
- Physical Sciences › Chemistry › Analytical Chemistry › Spectroscopy and Chemometric Analyses
- Physical Sciences › Engineering › Control and Systems Engineering › Fault Detection and Control Systems
- Keywords
- process analytical technology, recombinant adeno-associated virus, fluorescence spectroscopy, artificial neural networks, genetic algorithm optimization, cell viability, cell density, harvest time, viral vector production, biopharmaceutical manufacturing
- MeSH terms
- Dependovirus, Animals, Models, Biological, Spectrometry, Fluorescence, Spodoptera, Bioreactors, Sf9 Cells
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