Literature DB >> 26059229

The use of 'Omics technology to rationally improve industrial mammalian cell line performance.

Amanda M Lewis1, Nicholas R Abu-Absi2, Michael C Borys2, Zheng Jian Li2.   

Abstract

Biologics represent an increasingly important class of therapeutics, with 7 of the 10 top selling drugs from 2013 being in this class. Furthermore, health authority approval of biologics in the immuno-oncology space is expected to transform treatment of patients with debilitating and deadly diseases. The growing importance of biologics in the healthcare field has also resulted in the recent approvals of several biosimilars. These recent developments, combined with pressure to provide treatments at lower costs to payers, are resulting in increasing need for the industry to quickly and efficiently develop high yielding, robust processes for the manufacture of biologics with the ability to control quality attributes within narrow distributions. Achieving this level of manufacturing efficiency and the ability to design processes capable of regulating growth, death and other cellular pathways through manipulation of media, feeding strategies, and other process parameters will undoubtedly be facilitated through systems biology tools generated in academic and public research communities. Here we discuss the intersection of systems biology, 'Omics technologies, and mammalian bioprocess sciences. Specifically, we address how these methods in conjunction with traditional monitoring techniques represent a unique opportunity to better characterize and understand host cell culture state, shift from an empirical to rational approach to process development and optimization of bioreactor cultivation processes. We summarize the following six key areas: (i) research applied to parental, non-recombinant cell lines; (ii) systems level datasets generated with recombinant cell lines; (iii) datasets linking phenotypic traits to relevant biomarkers; (iv) data depositories and bioinformatics tools; (v) in silico model development, and (vi) examples where these approaches have been used to rationally improve cellular processes. We critically assess relevant and state of the art research being conducted in academic, government and industrial laboratories. Furthermore, we apply our expertise in bioprocess to define a potential model for integration of these systems biology approaches into biologics development.
© 2015 Wiley Periodicals, Inc.

Entities:  

Keywords:  CHO; bioprocess; metabolomics; proteomics; rational optimization; transcriptomics

Mesh:

Substances:

Year:  2015        PMID: 26059229     DOI: 10.1002/bit.25673

Source DB:  PubMed          Journal:  Biotechnol Bioeng        ISSN: 0006-3592            Impact factor:   4.530


  9 in total

1.  Monitoring of Microphysiological Systems: Integrating Sensors and Real-Time Data Analysis toward Autonomous Decision-Making.

Authors:  Ashlyn T Young; Kristina R Rivera; Patrick D Erb; Michael A Daniele
Journal:  ACS Sens       Date:  2019-04-19       Impact factor: 7.711

Review 2.  Leveraging advances in biology to design biomaterials.

Authors:  Max Darnell; David J Mooney
Journal:  Nat Mater       Date:  2017-11-24       Impact factor: 43.841

3.  Multi-Omics Reveals Impact of Cysteine Feed Concentration and Resulting Redox Imbalance on Cellular Energy Metabolism and Specific Productivity in CHO Cell Bioprocessing.

Authors:  Amr S Ali; Rachel Chen; Ravali Raju; Rashmi Kshirsagar; Alan Gilbert; Li Zang; Barry L Karger; Alexander R Ivanov
Journal:  Biotechnol J       Date:  2020-04-03       Impact factor: 4.677

4.  A Systematic Approach to Time-series Metabolite Profiling and RNA-seq Analysis of Chinese Hamster Ovary Cell Culture.

Authors:  Han-Hsiu Hsu; Michihiro Araki; Masao Mochizuki; Yoshimi Hori; Masahiro Murata; Prihardi Kahar; Takanobu Yoshida; Tomohisa Hasunuma; Akihiko Kondo
Journal:  Sci Rep       Date:  2017-03-02       Impact factor: 4.379

5.  Real-time quantification and supplementation of bioreactor amino acids to prolong culture time and maintain antibody product quality.

Authors:  David N Powers; Yifan Wang; Erica J Fratz-Berilla; Sai Rashmika Velugula-Yellela; Brittany Chavez; Phillip Angart; Nicholas Trunfio; Seongkyu Yoon; Cyrus Agarabi
Journal:  Biotechnol Prog       Date:  2019-08-28

6.  Multivariate data analysis of growth medium trends affecting antibody glycosylation.

Authors:  David N Powers; Nicholas Trunfio; Sai R Velugula-Yellela; Phillip Angart; Anneliese Faustino; Cyrus Agarabi
Journal:  Biotechnol Prog       Date:  2019-10-18

7.  Understanding and Controlling Sialylation in a CHO Fc-Fusion Process.

Authors:  Amanda M Lewis; William D Croughan; Nelly Aranibar; Alison G Lee; Bethanne Warrack; Nicholas R Abu-Absi; Rutva Patel; Barry Drew; Michael C Borys; Michael D Reily; Zheng Jian Li
Journal:  PLoS One       Date:  2016-06-16       Impact factor: 3.240

8.  A comprehensive CHO SWATH-MS spectral library for robust quantitative profiling of 10,000 proteins.

Authors:  Kae Hwan Sim; Lillian Chia-Yi Liu; Hwee Tong Tan; Kelly Tan; Daniel Ng; Wei Zhang; Yuansheng Yang; Stephen Tate; Xuezhi Bi
Journal:  Sci Data       Date:  2020-08-11       Impact factor: 6.444

9.  Sub-nanoliter metabolomics via mass spectrometry to characterize volume-limited samples.

Authors:  Yafeng Li; Marcos Bouza; Changsheng Wu; Hengyu Guo; Danning Huang; Gilad Doron; Johnna S Temenoff; Arlene A Stecenko; Zhong Lin Wang; Facundo M Fernández
Journal:  Nat Commun       Date:  2020-11-06       Impact factor: 14.919

  9 in total

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