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  • 1.
    Schwarz, Hubert
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Industrial Biotechnology. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Centres, Centre for Advanced BioProduction by Continuous Processing, AdBIOPRO.
    Zhang, Ye
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Industrial Biotechnology. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Centres, Centre for Advanced BioProduction by Continuous Processing, AdBIOPRO.
    Zhan, Caijuan
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Industrial Biotechnology.
    Malm, Magdalena
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.
    Field, Raymond
    AstraZeneca, BioPharmaceut Dev, Cambridge, England..
    Turner, Richard
    AstraZeneca, BioPharmaceut Dev, Cambridge, England..
    Sellick, Christopher
    AstraZeneca, BioPharmaceut Dev, Cambridge, England.;Kymab, Cambridge, England..
    Varley, Paul
    AstraZeneca, BioPharmaceut Dev, Cambridge, England..
    Rockberg, Johan
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Protein Technology.
    Chotteau, Veronique
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Industrial Biotechnology. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Centres, Centre for Advanced BioProduction by Continuous Processing, AdBIOPRO.
    Small-scale bioreactor supports high density HEK293 cell perfusion culture for the production of recombinant Erythropoietin2020In: Journal of Biotechnology, ISSN 0168-1656, E-ISSN 1873-4863, Vol. 309, p. 44-52Article in journal (Refereed)
    Abstract [en]

    Process intensification in mammalian cell culture-based recombinant protein production has been achieved by high cell density perfusion exceeding 10(8) cells/mL in the recent years. As the majority of therapeutic proteins are produced in Chinese Hamster Ovary (CHO) cells, intensified perfusion processes have been mainly developed for this type of host cell line. However, the use of CHO cells can result in non-human posttranslational modifications of the protein of interest, which may be disadvantageous compared with human cell lines. In this study, we developed a high cell density perfusion process of Human Embryonic Kidney (HEK293) cells producing recombinant human Erythropoietin (rhEPO). Firstly, a small-scale perfusion system from commercial bench-top screening bioreactors was developed for < 250 mL working volume. Then, after the first trial runs with CHO cells, the system was modified for HEK293 cells (more sensitive than CHO cells) to achieve a higher oxygen transfer under mild aeration and agitation conditions. Steady states for medium (20 x 10(6) cells/mL) and high cell densities (80 x 10(6) cells/mL), normal process temperature (37 degrees C) and mild hypothermia (33 degrees C) as well as different cell specific perfusion rates (CSPR) from 10 to 60 pL/cell/day were applied to study the performance of the culture. The volumetric productivity was maximized for the high cell density steady state but decreased when an extremely low CSPR of 10 pL/cell/day was applied. The shift from high to low CSPR strongly reduced the nutrient uptake rates. The results from our study show that human cell lines, such as HEK293 can be used for intensified perfusion processes.

  • 2.
    Wang, Mingliang
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH, Centres, Centre for Advanced BioProduction by Continuous Processing, AdBIOPRO.
    Risuleo, Riccardo Sven
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Jacobsen, Elling W.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH, Centres, Centre for Advanced BioProduction by Continuous Processing, AdBIOPRO.
    Chotteau, Veronique
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Industrial Biotechnology. KTH, Centres, Centre for Advanced BioProduction by Continuous Processing, AdBIOPRO.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH, Centres, Centre for Advanced BioProduction by Continuous Processing, AdBIOPRO.
    Identification of nonlinear kinetics of macroscopic bio-reactions using multilinear Gaussian processes2020In: Computers and Chemical Engineering, ISSN 0098-1354, E-ISSN 1873-4375, Vol. 133, article id 106671Article in journal (Refereed)
    Abstract [en]

    In biological systems, nonlinear kinetic relationships between metabolites of interest are modeled for various purposes. Usually, little a priori knowledge is available in such models. Identifying the unknown kinetics is, therefore, a critical step which can be very challenging due to the problems of (i) model selection and (ii) nonlinear parameter estimation. In this paper, we aim to address these problems systematically in a framework based on multilinear Gaussian processes using a family of kernels tailored to typical behaviours of modulation effects such as activation and inhibition or combinations thereof. Using one such process as a model for each modulation effect leads to a much more flexible model than conventional parametric models, e.g., the Monod model. The resulting models of the modulation effects can also be used as a starting point for estimating parametric kinetic models. As each modulation effect is modeled separately, this task is greatly simplified compared to the conventional approach where the parameters in all modulation functions have to be estimated simultaneously. We also show how the type of modulation effect can be selected automatically by way of regularization, thus by-passing the model selection problem. The resulting parameter estimates can be used as initial estimates in the conventional approach where the full model is estimated. Numerical experiments, including fed-batch simulations, are conducted to demonstrate our methods.

  • 3.
    Zamani, Leila
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Industrial Biotechnology.
    Lundqvist, Magnus
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Protein Technology. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Centres, Centre for Advanced BioProduction by Continuous Processing, AdBIOPRO.
    Zhang, Ye
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Centres, Wallenberg Center for Protein Research.
    Aberg, Magnus
    Stockholm Univ, Dept Analyt Chem, S-10691 Stockholm, Sweden..
    Edfors, Fredrik
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Bidkhori, Gholamreza
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH).
    Lindahl, Anna
    Karolinska Inst, Dept Oncol Pathol, Sci Life Lab, S-17165 Solna, Sweden..
    Mie, Axel
    Karolinska Inst, Dept Clin Sci & Educ, S-11883 Solna, Sweden..
    Mardinoglu, Adil
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Field, Raymond
    MedImmune, Biopharmaceut Dev, Cambridge CB21 6GH, England..
    Turner, Richard
    MedImmune, Biopharmaceut Dev, Cambridge CB21 6GH, England..
    Rockberg, Johan
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Protein Technology. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Centres, Centre for Advanced BioProduction by Continuous Processing, AdBIOPRO.
    Chotteau, Véronique
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Industrial Biotechnology. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Centres, Centre for Advanced BioProduction by Continuous Processing, AdBIOPRO.
    High Cell Density Perfusion Culture has a Maintained Exoproteome and Metabolome2018In: Biotechnology Journal, ISSN 1860-6768, E-ISSN 1860-7314, Vol. 13, no 10, article id 1800036Article in journal (Refereed)
    Abstract [en]

    The optimization of bioprocesses for biopharmaceutical manufacturing by Chinese hamster ovary (CHO) cells can be a challenging endeavor and, today, heavily relies on empirical methods treating the bioreactor process and the cells as black boxes. Multi-omics approaches have the potential to reveal otherwise unknown characteristics of these systems and identify culture parameters to more rationally optimize the cultivation process. Here, the authors have applied both metabolomic and proteomic profiling to a perfusion process, using CHO cells for antibody production, to explore how cell biology and reactor environment change as the cell density reaches 200x10(6)cellsmL(-1). The extracellular metabolic composition obtained in perfusion mode shows a markedly more stable profile in comparison to fed-batch, despite a far larger range of viable cell densities in perfusion. This stable profile is confirmed in the extracellular proteosome. Furthermore, the proteomics data shows an increase of structural proteins as cell density increases, which could be due to a higher shear stress and explain the decrease in cell diameter at very high cell densities. Both proteomic and metabolic results shows signs of oxidative stress and changes in glutathione metabolism at very high cell densities. The authors suggest the methodology presented herein to be a powerful tool for optimizing processes of recombinant protein production.

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