Evidence map›Paper›PMID 33346864›Full record

ArticleAdvances in biochemical engineering/biotechnology2021

Usage of Digital Twins Along a Typical Process Development Cycle.

Peter Sinner, Sven Daume, Christoph Herwig, Julian Kager

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Article in Advances in biochemical engineering/biotechnology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Peter SinnerInstitute of Chemical, Environmental and Bioscience Engineering, Technische Universität Wien, Vienna, Austria.
Sven DaumeInstitute of Chemical, Environmental and Bioscience Engineering, Technische Universität Wien, Vienna, Austria.
Christoph HerwigInstitute of Chemical, Environmental and Bioscience Engineering, Technische Universität Wien, Vienna, Austria.
Julian KagerInstitute of Chemical, Environmental and Bioscience Engineering, Technische Universität Wien, Vienna, Austria. julian.kager@tuwien.ac.at.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

SoftwareHumansBioprocess developmentControlDigital twinDynamic modelingProcess systems engineeringReal-time monitoring

Identifiers

PMID33346864

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.