Literature DB >> 33871051

Robotic integration enables autonomous operation of laboratory scale stirred tank bioreactors with model-driven process analysis.

Holger Morschett1, Niklas Tenhaef1, Johannes Hemmerich1, Laura Herbst1, Markus Spiertz1, Deniz Dogan1, Wolfgang Wiechert1,2, Stephan Noack1, Marco Oldiges1,3.   

Abstract

Given its geometric similarity to large-scale production plants and the excellent possibilities for precise process control and monitoring, the classic stirred tank bioreactor (STR) still represents the gold standard for bioprocess development at a laboratory scale. However, compared to microbioreactor technologies, bioreactors often suffer from a low degree of process automation and deriving key performance indicators (KPIs) such as specific rates or yields often requires manual sampling and sample processing. A widely used parallelized STR setup was automated by connecting it to a liquid handling system and controlling it with a custom-made process control system. This allowed for the setup of a flexible modular platform enabling autonomous operation of the bioreactors without any operator present. Multiple unit operations like automated inoculation, sampling, sample processing and analysis, and decision making, for example for automated induction of protein production were implemented to achieve such functionality. The data gained during application studies was used for fitting of bioprocess models to derive relevant KPIs being in good agreement with literature. By combining the capabilities of STRs with the flexibility of liquid handling systems, this platform technology can be applied to a multitude of different bioprocess development pipelines at laboratory scale.
© 2021 The Authors. Biotechnology and Bioengineering published by Wiley Periodicals LLC.

Entities:  

Keywords:  laboratory automation; maximum likelihood estimation; process control system; robotic integration; stirred tank bioreactor

Mesh:

Year:  2021        PMID: 33871051     DOI: 10.1002/bit.27795

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


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3.  Control of parallelized bioreactors I: dynamic scheduling software for efficient bioprocess management in high-throughput systems.

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  3 in total

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