Literature DB >> 33346865

Digital Twins in Biomanufacturing.

Steffen Zobel-Roos1, Axel Schmidt1, Lukas Uhlenbrock1, Reinhard Ditz1, Dirk Köster1, Jochen Strube2.   

Abstract

In recent years process modelling has become an established method which generates digital twins of manufacturing plant operation with the aid of numerically solved process models. This article discusses the benefits of establishing process modelling, in-house or by cooperation, in order to support the workflow from process development, piloting and engineering up to manufacturing. The examples are chosen from the variety of botanicals and biologics manufacturing thus proving the broad applicability from variable feedstock of natural plant extracts of secondary metabolites to fermentation of complex molecules like mAbs, fragments, proteins and peptides.Consistent models and methods to simulate whole processes are available. To determine the physical properties used as model parameters, efficient laboratory-scale experiments are implemented. These parameters are case specific since there is no database for complex molecules of biologics and botanicals in pharmaceutical industry, yet.Moreover, Quality-by-Design approaches, demanded by regulatory authorities, are integrated within those predictive modelling procedures. The models could be proven to be valid and predictive under regulatory aspects. Process modelling does earn its money from the first day of application. Process modelling is a key-enabling tool towards cost-efficient digitalization in chemical-pharmaceutical industries.

Keywords:  Chemical-pharmaceutical industry; Digital twin; Digitalization; Industry 4.0; Process modelling

Year:  2021        PMID: 33346865     DOI: 10.1007/10_2020_146

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


  35 in total

1.  Fingerprint detection and process prediction by multivariate analysis of fed-batch monoclonal antibody cell culture data.

Authors:  Michael Sokolov; Miroslav Soos; Benjamin Neunstoecklin; Massimo Morbidelli; Alessandro Butté; Riccardo Leardi; Thomas Solacroup; Matthieu Stettler; Hervé Broly
Journal:  Biotechnol Prog       Date:  2015-10-07

Review 2.  Data science tools and applications on the way to Pharma 4.0.

Authors:  Valentin Steinwandter; Daniel Borchert; Christoph Herwig
Journal:  Drug Discov Today       Date:  2019-06-14       Impact factor: 7.851

Review 3.  Advances in downstream processing of biologics - Spectroscopy: An emerging process analytical technology.

Authors:  Matthias Rüdt; Till Briskot; Jürgen Hubbuch
Journal:  J Chromatogr A       Date:  2016-11-15       Impact factor: 4.759

4.  Enhanced process understanding and multivariate prediction of the relationship between cell culture process and monoclonal antibody quality.

Authors:  Michael Sokolov; Jonathan Ritscher; Nicola MacKinnon; Jonathan Souquet; Hervé Broly; Massimo Morbidelli; Alessandro Butté
Journal:  Biotechnol Prog       Date:  2017-06-21

5.  Prediction uncertainty assessment of chromatography models using Bayesian inference.

Authors:  Till Briskot; Ferdinand Stückler; Felix Wittkopp; Christopher Williams; Jessica Yang; Susanne Konrad; Katharina Doninger; Jan Griesbach; Moritz Bennecke; Stefan Hepbildikler; Jürgen Hubbuch
Journal:  J Chromatogr A       Date:  2018-11-29       Impact factor: 4.759

6.  Model-based design space determination of peptide chromatographic purification processes.

Authors:  David Gétaz; Alessandro Butté; Massimo Morbidelli
Journal:  J Chromatogr A       Date:  2013-02-08       Impact factor: 4.759

7.  Modeling of mixed-mode chromatography of peptides.

Authors:  Susanna Bernardi; David Gétaz; Nicola Forrer; Massimo Morbidelli
Journal:  J Chromatogr A       Date:  2013-01-22       Impact factor: 4.759

8.  A versatile noninvasive method for adsorber quantification in batch and column chromatography based on the ionic capacity.

Authors:  Thiemo C Huuk; Till Briskot; Tobias Hahn; Jürgen Hubbuch
Journal:  Biotechnol Prog       Date:  2016-02-26

9.  Robust factor selection in early cell culture process development for the production of a biosimilar monoclonal antibody.

Authors:  Michael Sokolov; Jonathan Ritscher; Nicola MacKinnon; Jean-Marc Bielser; David Brühlmann; Dominik Rothenhäusler; Gian Thanei; Miroslav Soos; Matthieu Stettler; Jonathan Souquet; Hervé Broly; Massimo Morbidelli; Alessandro Butté
Journal:  Biotechnol Prog       Date:  2016-10-31

10.  Workflow for Target-Oriented Parametrization of an Enhanced Mechanistic Cell Culture Model.

Authors:  Sophia Ulonska; Paul Kroll; Jens Fricke; Christoph Clemens; Raphael Voges; Markus M Müller; Christoph Herwig
Journal:  Biotechnol J       Date:  2017-12-08       Impact factor: 4.677

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