Process analytical technology as key-enabler for digital twins in continuous biomanufacturing

被引:19
|
作者
Schmidt, Axel [1 ]
Helgers, Heribert [1 ]
Lohmann, Lara Julia [1 ]
Vetter, Florian [1 ]
Juckers, Alex [1 ]
Mouellef, Mourad [1 ]
Zobel-Roos, Steffen [1 ]
Strube, Jochen [1 ]
机构
[1] Tech Univ Clausthal, Inst Separat & Proc Technol, D-38678 Clausthal Zellerfeld, Germany
关键词
biotechnology; modelling; process control; simulation; biochemical engineering; SECONDARY STRUCTURE; IMPLEMENTATION; CHROMATOGRAPHY; OPERATION; UPSTREAM; CAPTURE; QUALITY; DESIGN; PAT;
D O I
10.1002/jctb.7008
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Over the last few years rapid progress has been made in adopting well-known process modeling techniques from chemicals to biologics manufacturing. The main challenge has been analytical methods as engineers need quantitative data for their workflow. Industrialization 4.0, Internet of Things, artificial intelligence and machine learning activities up to big data analysis have taken their share in solving fundamental problems like component- or at least group-specific evaluation of spectroscopic data. Besides, concerning inline analytics methods included in process analytical technology concepts the key technology has been the generation of decisive validated digital twins based on process models. This review aims to summarize the methodology to achieve a holistic understanding of process models, control and optimization by means of digital twins using the example of recent work published in this field. (c) 2021 The Authors. Journal of Chemical Technology and Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry (SCI).
引用
收藏
页码:2336 / 2346
页数:11
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