Literature DB >> 29027766

Kinetic Modeling of Mammalian Cell Culture Bioprocessing: The Quest to Advance Biomanufacturing.

Sarantos Kyriakopoulos1, Kok Siong Ang1, Meiyappan Lakshmanan1, Zhuangrong Huang2, Seongkyu Yoon2, Rudiyanto Gunawan3, Dong-Yup Lee1,4.   

Abstract

Kinetic modeling is the most suitable framework to describe the dynamic behavior of mammalian cell culture although its industrial application is still in its infancy. Herein, the authors reviewed mammalian bioprocess relevant kinetic models, and found that the simple unstructured-unsegregated approach utilizing empirical Monod-type kinetics based on limiting substrates and inhibitory metabolites is commonly used due to its traceability and simple formalism. Notably, the available kinetic models are typically small to moderate in size, and the development of large-scale models is severely hampered by the scarcity of kinetic data and limitations in current parameter estimation methods. The recent availability of abundant high-throughput multi-omics datasets from mammalian cell cultures have now paved the way to improve parameterization of kinetic models, and integrate regulatory, signaling, and product quality related intracellular events, as well as cellular metabolism within the modeling framework. Ultimately, the authors foresee that multi-scale modeling is the way forward in building predictive kinetic models of mammalian cell culture to advance biomanufacturing.
© 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  bioprocessing; kinetic modeling; mammalian cell culture; parameter estimation

Mesh:

Year:  2017        PMID: 29027766     DOI: 10.1002/biot.201700229

Source DB:  PubMed          Journal:  Biotechnol J        ISSN: 1860-6768            Impact factor:   4.677


  7 in total

1.  Systematic development of temperature shift strategies for Chinese hamster ovary cells based on short duration cultures and kinetic modeling.

Authors:  Jianlin Xu; Peifeng Tang; Andrew Yongky; Barry Drew; Michael C Borys; Shijie Liu; Zheng Jian Li
Journal:  MAbs       Date:  2018-10-02       Impact factor: 5.857

Review 2.  Bioengineering Outlook on Cultivated Meat Production.

Authors:  Ivana Pajčin; Teodora Knežić; Ivana Savic Azoulay; Vanja Vlajkov; Mila Djisalov; Ljiljana Janjušević; Jovana Grahovac; Ivana Gadjanski
Journal:  Micromachines (Basel)       Date:  2022-02-28       Impact factor: 2.891

3.  Benchmarking optimization methods for parameter estimation in large kinetic models.

Authors:  Alejandro F Villaverde; Fabian Fröhlich; Daniel Weindl; Jan Hasenauer; Julio R Banga
Journal:  Bioinformatics       Date:  2019-03-01       Impact factor: 6.937

Review 4.  Harnessing the potential of machine learning for advancing "Quality by Design" in biomanufacturing.

Authors:  Ian Walsh; Matthew Myint; Terry Nguyen-Khuong; Ying Swan Ho; Say Kong Ng; Meiyappan Lakshmanan
Journal:  MAbs       Date:  2022 Jan-Dec       Impact factor: 5.857

5.  Modeling apoptosis resistance in CHO cells with CRISPR-mediated knockouts of Bak1, Bax, and Bok.

Authors:  Michael A MacDonald; Craig Barry; Teddy Groves; Verónica S Martínez; Peter P Gray; Kym Baker; Evan Shave; Stephen Mahler; Trent Munro; Esteban Marcellin; Lars K Nielsen
Journal:  Biotechnol Bioeng       Date:  2022-03-06       Impact factor: 4.395

6.  Mechanistic model for production of recombinant adeno-associated virus via triple transfection of HEK293 cells.

Authors:  Tam N T Nguyen; Sha Sha; Moo Sun Hong; Andrew J Maloney; Paul W Barone; Caleb Neufeld; Jacqueline Wolfrum; Stacy L Springs; Anthony J Sinskey; Richard D Braatz
Journal:  Mol Ther Methods Clin Dev       Date:  2021-04-16       Impact factor: 6.698

7.  High density bioprocessing of human pluripotent stem cells by metabolic control and in silico modeling.

Authors:  Felix Manstein; Kevin Ullmann; Christina Kropp; Caroline Halloin; Wiebke Triebert; Annika Franke; Clara-Milena Farr; Anais Sahabian; Alexandra Haase; Yannik Breitkreuz; Michael Peitz; Oliver Brüstle; Stefan Kalies; Ulrich Martin; Ruth Olmer; Robert Zweigerdt
Journal:  Stem Cells Transl Med       Date:  2021-03-04       Impact factor: 6.940

  7 in total

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