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Monitoring of amino...
Monitoring of amino acids and antibody N-glycosylation in high cell density perfusion culture based on Raman spectroscopy
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- Schwarz, Hubert (författare)
- KTH,Industriell bioteknologi,Centre for Advanced BioProduction by Continuous Processing, AdBIOPRO
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- Mäkinen, Meeri (författare)
- KTH,Industriell bioteknologi,Centre for Advanced BioProduction by Continuous Processing, AdBIOPRO
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- Castan, Andreas (författare)
- KTH,Centre for Advanced BioProduction by Continuous Processing, AdBIOPRO,Cytiva, Uppsala, Sweden
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- Chotteau, Véronique, Docent, 1963- (författare)
- KTH,Industriell bioteknologi,Centre for Advanced BioProduction by Continuous Processing, AdBIOPRO
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(creator_code:org_t)
- Elsevier BV, 2022
- 2022
- Engelska.
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Ingår i: Biochemical engineering journal. - : Elsevier BV. - 1369-703X .- 1873-295X. ; 182, s. 108426-
- Relaterad länk:
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https://doi.org/10.1...
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https://kth.diva-por... (primary) (Raw object)
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Raman spectrum based predictive models provide a process analytical technology (PAT) tool for monitoring and control of culture parameters in bioprocesses. Steady-state perfusion cultures generate a relatively stable metabolite profile, which is not conducive to modeling due to the absence of variations of culture parameters. Here we present an approach where different steady-states obtained by variation of the cell specific perfusion rate (CSPR) between 10 and 40 pL/(cell * day) with cell densities up to 100 × 106 cells/mL during the process development provided a dynamic culture environment, favorable for the model calibration. The cell density had no effect on the culture performance at similar CSPR, however a variation in the CSPR had a strong influence on the metabolism, mAb productivity and N-glycosylation. Predictive models were developed for multiple culture parameters, including cell density, lactate, ammonium and amino acids; and then validated with new runs performed at multiple or single steady-states, showing high prediction accuracy. The relationship of amino acids and antibody N-glycosylation was modeled to predict the glycosylation pattern of the product in real time. The present efficient process development approach with integration of Raman spectroscopy provides a valuable PAT tool for later implementation in steady-state perfusion production processes.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Industriell bioteknik -- Bioprocessteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Industrial Biotechnology -- Bioprocess Technology (hsv//eng)
Nyckelord
- CHO cells
- Monoclonal antibody
- Perfusion process
- PLS model
- Process analytical technology
- Raman spectroscopy
- Biotechnology
- Bioteknologi
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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