An Efficient Experimental Design Strategy for Modelling and Characterization of Processes

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Designing robust, efficient and economic processes is a main challenge for the biotech industries. To achieve a well-designed bioprocess, understanding the ongoing phenomena and the involved reaction kinetics is crucial. By development of advanced miniaturized reactors, a promising opportunity arises for parallel screening of multiple processes in reduced volumes within high throughput platforms. However, the level of accessible information from each set of experimental design remains to be one of the main issues particularly in the case of complex biosystems. This work introduces a novel generic Model-based Design of Experiments (M-DoE) routine with its main target being model development and system characterization. With the new M-DoE strategy, an improved set of informative experiments are suggested, which consequently reduces the demand for physical resources and analysis. The routine proposes a set of optimum experimental settings to support structural model definition, kinetic order estimation and parameter estimation during a model building procedure and process characterization.
Original languageEnglish
Title of host publicationProceedings of the 27th European Symposium on Computer Aided Process Engineering (ESCAPE 27)
EditorsAntonio Espuña, Moisès Graells, Luis Puigjaner
Volume40
PublisherElsevier
Publication date2017
Edition1
Pages2827-2832
ISBN (Print)9780444639653
ISBN (Electronic)9780444639707
DOIs
Publication statusPublished - 2017
Event27th European Symposium on Computer Aided Process Engineering - Barcelona, Spain
Duration: 1 Oct 20175 Oct 2017
Conference number: 27
https://www.elsevier.com/books/27th-european-symposium-on-computer-aided-process-engineering/espuna/978-0-444-63965-3

Conference

Conference27th European Symposium on Computer Aided Process Engineering
Number27
CountrySpain
CityBarcelona
Period01/10/201705/10/2017
Internet address

Keywords

  • Model based Design of Experiments
  • Parallel experimental design
  • Model development
  • Electrochemical biosensor characterization

Cite this

Tajsoleiman, T., Semenova, D., Oliveira Fernandes, A. C., Huusom, J. K., Gernaey, K. V., & Krühne, U. (2017). An Efficient Experimental Design Strategy for Modelling and Characterization of Processes. In A. Espuña, M. Graells, & L. Puigjaner (Eds.), Proceedings of the 27th European Symposium on Computer Aided Process Engineering (ESCAPE 27) (1 ed., Vol. 40, pp. 2827-2832). Elsevier. https://doi.org/10.1016/B978-0-444-63965-3.50473-6
Tajsoleiman, Tannaz ; Semenova, Daria ; Oliveira Fernandes, Ana Carolina ; Huusom, Jakob Kjøbsted ; Gernaey, Krist V. ; Krühne, Ulrich. / An Efficient Experimental Design Strategy for Modelling and Characterization of Processes. Proceedings of the 27th European Symposium on Computer Aided Process Engineering (ESCAPE 27). editor / Antonio Espuña ; Moisès Graells ; Luis Puigjaner. Vol. 40 1. ed. Elsevier, 2017. pp. 2827-2832
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abstract = "Designing robust, efficient and economic processes is a main challenge for the biotech industries. To achieve a well-designed bioprocess, understanding the ongoing phenomena and the involved reaction kinetics is crucial. By development of advanced miniaturized reactors, a promising opportunity arises for parallel screening of multiple processes in reduced volumes within high throughput platforms. However, the level of accessible information from each set of experimental design remains to be one of the main issues particularly in the case of complex biosystems. This work introduces a novel generic Model-based Design of Experiments (M-DoE) routine with its main target being model development and system characterization. With the new M-DoE strategy, an improved set of informative experiments are suggested, which consequently reduces the demand for physical resources and analysis. The routine proposes a set of optimum experimental settings to support structural model definition, kinetic order estimation and parameter estimation during a model building procedure and process characterization.",
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author = "Tannaz Tajsoleiman and Daria Semenova and {Oliveira Fernandes}, {Ana Carolina} and Huusom, {Jakob Kj{\o}bsted} and Gernaey, {Krist V.} and Ulrich Kr{\"u}hne",
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Tajsoleiman, T, Semenova, D, Oliveira Fernandes, AC, Huusom, JK, Gernaey, KV & Krühne, U 2017, An Efficient Experimental Design Strategy for Modelling and Characterization of Processes. in A Espuña, M Graells & L Puigjaner (eds), Proceedings of the 27th European Symposium on Computer Aided Process Engineering (ESCAPE 27). 1 edn, vol. 40, Elsevier, pp. 2827-2832, 27th European Symposium on Computer Aided Process Engineering, Barcelona, Spain, 01/10/2017. https://doi.org/10.1016/B978-0-444-63965-3.50473-6

An Efficient Experimental Design Strategy for Modelling and Characterization of Processes. / Tajsoleiman, Tannaz; Semenova, Daria; Oliveira Fernandes, Ana Carolina; Huusom, Jakob Kjøbsted; Gernaey, Krist V.; Krühne, Ulrich.

Proceedings of the 27th European Symposium on Computer Aided Process Engineering (ESCAPE 27). ed. / Antonio Espuña; Moisès Graells; Luis Puigjaner. Vol. 40 1. ed. Elsevier, 2017. p. 2827-2832.

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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T1 - An Efficient Experimental Design Strategy for Modelling and Characterization of Processes

AU - Tajsoleiman, Tannaz

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AU - Huusom, Jakob Kjøbsted

AU - Gernaey, Krist V.

AU - Krühne, Ulrich

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AB - Designing robust, efficient and economic processes is a main challenge for the biotech industries. To achieve a well-designed bioprocess, understanding the ongoing phenomena and the involved reaction kinetics is crucial. By development of advanced miniaturized reactors, a promising opportunity arises for parallel screening of multiple processes in reduced volumes within high throughput platforms. However, the level of accessible information from each set of experimental design remains to be one of the main issues particularly in the case of complex biosystems. This work introduces a novel generic Model-based Design of Experiments (M-DoE) routine with its main target being model development and system characterization. With the new M-DoE strategy, an improved set of informative experiments are suggested, which consequently reduces the demand for physical resources and analysis. The routine proposes a set of optimum experimental settings to support structural model definition, kinetic order estimation and parameter estimation during a model building procedure and process characterization.

KW - Model based Design of Experiments

KW - Parallel experimental design

KW - Model development

KW - Electrochemical biosensor characterization

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DO - 10.1016/B978-0-444-63965-3.50473-6

M3 - Article in proceedings

SN - 9780444639653

VL - 40

SP - 2827

EP - 2832

BT - Proceedings of the 27th European Symposium on Computer Aided Process Engineering (ESCAPE 27)

A2 - Espuña, Antonio

A2 - Graells, Moisès

A2 - Puigjaner, Luis

PB - Elsevier

ER -

Tajsoleiman T, Semenova D, Oliveira Fernandes AC, Huusom JK, Gernaey KV, Krühne U. An Efficient Experimental Design Strategy for Modelling and Characterization of Processes. In Espuña A, Graells M, Puigjaner L, editors, Proceedings of the 27th European Symposium on Computer Aided Process Engineering (ESCAPE 27). 1 ed. Vol. 40. Elsevier. 2017. p. 2827-2832 https://doi.org/10.1016/B978-0-444-63965-3.50473-6