Real‐time online monitoring of insect cell proliferation and baculovirus infection using digital differential holographic microscopy and machine learning

Altenburg, Jort J; Klaverdijk, None Maarten; Cabosart, Damien; Desmecht, Laurent; Brunekreeft-Terlouw, Sonja S; Both, None Joshua; Tegelbeckers, Vivian I P; Willekens, Marieke L P M; Oosten, Linda van; Hick, Tessy A.H.; Aalst, Tom M H van der; Pijlman, Gorben P.; Oers, Monique M. van; Wijffels, René H.; Martens, Dirk E.

doi:10.1002/btpr.3318

Cited by 6 publications

(3 citation statements)

References 56 publications

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“…It becomes evident that the values measured offline correspond well with the values measured online over the entire cultivation period. Altenburg et al [ 144 ] showed similar accuracies between the VCD determination using iLineF and offline determination in cultivations with insect cells. The cell aggregation rate correlates with the VCD.…”

Section: Resultsmentioning

confidence: 89%

Improvement of HEK293 Cell Growth by Adapting Hydrodynamic Stress and Predicting Cell Aggregate Size Distribution

et al. 2023

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HEK293 is a widely used cell line in the fields of research and industry. It is assumed that these cells are sensitive to hydrodynamic stress. The aim of this research was to use particle image velocimetry validated computational fluid dynamics (CFD) to determine the hydrodynamic stress in both shake flasks, with and without baffles, and in stirred Minifors 2 bioreactors to evaluate its effect on the growth and aggregate size distribution of HEK293 suspension cells. The HEK FreeStyleTM 293-F cell line was cultivated in batch mode at different specific power inputs (from 63W/m3–451W/m3), whereby ≈60W/m3 corresponds to the upper limit, which is what has been typically described in published experiments. In addition to the specific growth rate and maximum viable cell density VCDmax, the cell size distribution over time and cluster size distribution were investigated. The VCDmax of 5.77±0.02e6cells/mL was reached at a specific power input of 233W/m3 and was 23.8% higher than the value obtained at 63W/m3 and 7.2% higher than the value obtained at 451W/m3. No significant change in the cell size distribution could be measured in the investigated range. It was shown that the cell cluster size distribution follows a strict geometric distribution whose free parameter p is linearly dependent on the mean Kolmogorov length scale. Based on the performed experiments, it has been shown that by using CFD-characterised bioreactors, the VCDmax can be increased and the cell aggregate rate can be precisely controlled.

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Section: Resultsmentioning

confidence: 89%

Improvement of HEK293 Cell Growth by Adapting Hydrodynamic Stress and Predicting Cell Aggregate Size Distribution

et al. 2023

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“…Cell proliferation could be monitored through ML based algorithms. An ML model was trained for monitoring insect cell proliferation and viability percentage upon baculovirus infection in the bioreactor ( Altenburg et al., 2023 ).…”

Section: Ai-based ML Algorithms In Recombinant Protein Productionmentioning

confidence: 99%

Artificial intelligence-driven systems engineering for next-generation plant-derived biopharmaceuticals

Parthiban,

Vijeesh,

Gayathri

et al. 2023

Front. Plant Sci.

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Recombinant biopharmaceuticals including antigens, antibodies, hormones, cytokines, single-chain variable fragments, and peptides have been used as vaccines, diagnostics and therapeutics. Plant molecular pharming is a robust platform that uses plants as an expression system to produce simple and complex recombinant biopharmaceuticals on a large scale. Plant system has several advantages over other host systems such as humanized expression, glycosylation, scalability, reduced risk of human or animal pathogenic contaminants, rapid and cost-effective production. Despite many advantages, the expression of recombinant proteins in plant system is hindered by some factors such as non-human post-translational modifications, protein misfolding, conformation changes and instability. Artificial intelligence (AI) plays a vital role in various fields of biotechnology and in the aspect of plant molecular pharming, a significant increase in yield and stability can be achieved with the intervention of AI-based multi-approach to overcome the hindrance factors. Current limitations of plant-based recombinant biopharmaceutical production can be circumvented with the aid of synthetic biology tools and AI algorithms in plant-based glycan engineering for protein folding, stability, viability, catalytic activity and organelle targeting. The AI models, including but not limited to, neural network, support vector machines, linear regression, Gaussian process and regressor ensemble, work by predicting the training and experimental data sets to design and validate the protein structures thereby optimizing properties such as thermostability, catalytic activity, antibody affinity, and protein folding. This review focuses on, integrating systems engineering approaches and AI-based machine learning and deep learning algorithms in protein engineering and host engineering to augment protein production in plant systems to meet the ever-expanding therapeutics market.

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“…To assess the impact of timing on low MOI processes, several low MOI bioreactor infections with temperature shifts at different times post-infection were performed. In previous experiments with low MOI (0.01 TCID50/cell), complete baculovirus infection of all insect cells was observed around 40 hpi (Altenburg et al, 2022). Therefore, the temperature shift was conducted between 33-40 hpi.…”

Section: Scale-up To Bioreactors With High Moi Infectionmentioning

confidence: 99%

Process optimization of the baculovirus expression vector system for vaccine production

Altenburg

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Real‐time online monitoring of insect cell proliferation and baculovirus infection using digital differential holographic microscopy and machine learning

Cited by 6 publications

References 56 publications

Improvement of HEK293 Cell Growth by Adapting Hydrodynamic Stress and Predicting Cell Aggregate Size Distribution

Improvement of HEK293 Cell Growth by Adapting Hydrodynamic Stress and Predicting Cell Aggregate Size Distribution

Artificial intelligence-driven systems engineering for next-generation plant-derived biopharmaceuticals

Process optimization of the baculovirus expression vector system for vaccine production

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