Literature DB >> 33346864

Usage of Digital Twins Along a Typical Process Development Cycle.

Peter Sinner1, Sven Daume1, Christoph Herwig1,2, Julian Kager3.   

Abstract

Digital methods for process design, monitoring, and control can convert classical trial-and-error bioprocess development to a quantitative engineering approach. By interconnecting hardware, software, data, and humans currently untapped process optimization potential can be accessed. The key component within such a framework is a digital twin interacting with its physical process counterpart. In this chapter, we show how digital twin guided process development can be applied on an exemplary microbial cultivation process. The usage of digital twins is described along a typical process development cycle, ranging from early strain characterization to real-time control applications. Along an illustrative case study on microbial upstream bioprocessing, we emphasize that digital twins can integrate entire process development cycles if the digital twin itself and the underlying models are continuously adapted to newly available data. Therefore, the digital twin can be regarded as a powerful knowledge management tool and a decision support system for efficient process development. Its full potential can be deployed in a real-time environment where targeted control actions can further improve process performance.

Entities:  

Keywords:  Bioprocess development; Control; Digital twin; Dynamic modeling; Process systems engineering; Real-time monitoring

Year:  2021        PMID: 33346864     DOI: 10.1007/10_2020_149

Source DB:  PubMed          Journal:  Adv Biochem Eng Biotechnol        ISSN: 0724-6145            Impact factor:   2.635


  19 in total

Review 1.  Application of mechanistic models to fermentation and biocatalysis for next-generation processes.

Authors:  Krist V Gernaey; Anna Eliasson Lantz; Pär Tufvesson; John M Woodley; Gürkan Sin
Journal:  Trends Biotechnol       Date:  2010-04-21       Impact factor: 19.536

Review 2.  New mass spectrometry technologies contributing towards comprehensive and high throughput omics analyses of single cells.

Authors:  Sneha P Couvillion; Ying Zhu; Gabe Nagy; Joshua N Adkins; Charles Ansong; Ryan S Renslow; Paul D Piehowski; Yehia M Ibrahim; Ryan T Kelly; Thomas O Metz
Journal:  Analyst       Date:  2019-01-28       Impact factor: 4.616

3.  Uncertainty analysis of penicillin V production using Monte Carlo simulation.

Authors:  Arno Biwer; Steve Griffith; Charles Cooney
Journal:  Biotechnol Bioeng       Date:  2005-04-20       Impact factor: 4.530

4.  Automatic identification of structured process models based on biological phenomena detected in (fed-)batch experiments.

Authors:  Sebastian Herold; Rudibert King
Journal:  Bioprocess Biosyst Eng       Date:  2013-12-10       Impact factor: 3.210

5.  Model-assisted Design of Experiments as a concept for knowledge-based bioprocess development.

Authors:  Johannes Möller; Kim B Kuchemüller; Tobias Steinmetz; Kirsten S Koopmann; Ralf Pörtner
Journal:  Bioprocess Biosyst Eng       Date:  2019-02-26       Impact factor: 3.210

6.  Fed-batch operation in special microtiter plates: a new method for screening under production conditions.

Authors:  Anja Wilming; Cornelia Bähr; Claudia Kamerke; Jochen Büchs
Journal:  J Ind Microbiol Biotechnol       Date:  2014-01-14       Impact factor: 3.346

Review 7.  Advances in analytical tools for high throughput strain engineering.

Authors:  Esteban Marcellin; Lars Keld Nielsen
Journal:  Curr Opin Biotechnol       Date:  2018-02-12       Impact factor: 9.740

Review 8.  Engineering biological systems using automated biofoundries.

Authors:  Ran Chao; Shekhar Mishra; Tong Si; Huimin Zhao
Journal:  Metab Eng       Date:  2017-06-07       Impact factor: 9.783

9.  Experimental and Model-Based Analysis to Optimize Microalgal Biomass Productivity in a Pilot-Scale Tubular Photobioreactor.

Authors:  Tobias Weise; Claudia Grewe; Michael Pfaff
Journal:  Front Bioeng Biotechnol       Date:  2020-05-13

10.  The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases.

Authors:  Ron Caspi; Richard Billington; Luciana Ferrer; Hartmut Foerster; Carol A Fulcher; Ingrid M Keseler; Anamika Kothari; Markus Krummenacker; Mario Latendresse; Lukas A Mueller; Quang Ong; Suzanne Paley; Pallavi Subhraveti; Daniel S Weaver; Peter D Karp
Journal:  Nucleic Acids Res       Date:  2015-11-02       Impact factor: 16.971

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