Affiliations 

  • 1 Institute for Bioengineering, School of Engineering, University of Edinburgh, The King's Buildings, Edinburgh EH9 3DW, Scotland, United Kingdom
  • 2 Institute for Bioengineering, School of Engineering, University of Edinburgh, The King's Buildings, Edinburgh EH9 3DW, Scotland, United Kingdom; Centre for Synthetic and Systems Biology, University of Edinburgh, The King's Buildings, Edinburgh EH9 3DW, Scotland, United Kingdom
  • 3 Department of Bioprocess Technology, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia
  • 4 Institute for Bioengineering, School of Engineering, University of Edinburgh, The King's Buildings, Edinburgh EH9 3DW, Scotland, United Kingdom; Centre for Synthetic and Systems Biology, University of Edinburgh, The King's Buildings, Edinburgh EH9 3DW, Scotland, United Kingdom. Electronic address: leo.rios@ed.ac.uk
Biotechnol Adv, 2021 12 16;55:107888.
PMID: 34923075 DOI: 10.1016/j.biotechadv.2021.107888

Abstract

Advanced fed-batch microbioreactors mitigate scale up risks and more closely mimic industrial cultivation practices. Recently, high throughput microscale feeding strategies have been developed which improve the accessibility of microscale fed-batch cultivation irrespective of experimental budget. This review explores such technologies and their role in accelerating bioprocess development. Diffusion- and enzyme-controlled feeding achieve a continuous supply of substrate while being simple and affordable. More complex feed profiles and greater process control require additional hardware. Automated liquid handling robots may be programmed to predefined feed profiles and have the sensitivity to respond to deviations in process parameters. Microfluidic technologies have been shown to facilitate both continuous and precise feeding. Holistic approaches, which integrate automated high-throughput fed-batch cultivation with strategic design of experiments and model-based optimisation, dramatically enhance process understanding whilst minimising experimental burden. The incorporation of real-time data for online optimisation of feed conditions can further refine screening. Although the technologies discussed in this review hold promise for efficient, low-risk bioprocess development, the expense and complexity of automated cultivation platforms limit their widespread application. Future attention should be directed towards the development of open-source software and reducing the exclusivity of hardware.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.