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Closed-loop optimization of chromatography column sizing strategies in biopharmaceutical manufacture

BACKGROUND: This paper considers a real-world optimization problem involving the identification of cost-effective equipment sizing strategies for the sequence of chromatography steps employed to purify biopharmaceuticals. Tackling this problem requires solving a combinatorial optimization problem su...

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Autores principales: Allmendinger, Richard, Simaria, Ana S, Turner, Richard, Farid, Suzanne S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Ltd 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4258073/
https://www.ncbi.nlm.nih.gov/pubmed/25506115
http://dx.doi.org/10.1002/jctb.4267
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author Allmendinger, Richard
Simaria, Ana S
Turner, Richard
Farid, Suzanne S
author_facet Allmendinger, Richard
Simaria, Ana S
Turner, Richard
Farid, Suzanne S
author_sort Allmendinger, Richard
collection PubMed
description BACKGROUND: This paper considers a real-world optimization problem involving the identification of cost-effective equipment sizing strategies for the sequence of chromatography steps employed to purify biopharmaceuticals. Tackling this problem requires solving a combinatorial optimization problem subject to multiple constraints, uncertain parameters, and time-consuming fitness evaluations. RESULTS: An industrially-relevant case study is used to illustrate that evolutionary algorithms can identify chromatography sizing strategies with significant improvements in performance criteria related to process cost, time and product waste over the base case. The results demonstrate also that evolutionary algorithms perform best when infeasible solutions are repaired intelligently, the population size is set appropriately, and elitism is combined with a low number of Monte Carlo trials (needed to account for uncertainty). Adopting this setup turns out to be more important for scenarios where less time is available for the purification process. Finally, a data-visualization tool is employed to illustrate how user preferences can be accounted for when it comes to selecting a sizing strategy to be implemented in a real industrial setting. CONCLUSION: This work demonstrates that closed-loop evolutionary optimization, when tuned properly and combined with a detailed manufacturing cost model, acts as a powerful decisional tool for the identification of cost-effective purification strategies. © 2013 The Authors. Journal of Chemical Technology & Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
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spelling pubmed-42580732014-12-11 Closed-loop optimization of chromatography column sizing strategies in biopharmaceutical manufacture Allmendinger, Richard Simaria, Ana S Turner, Richard Farid, Suzanne S J Chem Technol Biotechnol Research Articles BACKGROUND: This paper considers a real-world optimization problem involving the identification of cost-effective equipment sizing strategies for the sequence of chromatography steps employed to purify biopharmaceuticals. Tackling this problem requires solving a combinatorial optimization problem subject to multiple constraints, uncertain parameters, and time-consuming fitness evaluations. RESULTS: An industrially-relevant case study is used to illustrate that evolutionary algorithms can identify chromatography sizing strategies with significant improvements in performance criteria related to process cost, time and product waste over the base case. The results demonstrate also that evolutionary algorithms perform best when infeasible solutions are repaired intelligently, the population size is set appropriately, and elitism is combined with a low number of Monte Carlo trials (needed to account for uncertainty). Adopting this setup turns out to be more important for scenarios where less time is available for the purification process. Finally, a data-visualization tool is employed to illustrate how user preferences can be accounted for when it comes to selecting a sizing strategy to be implemented in a real industrial setting. CONCLUSION: This work demonstrates that closed-loop evolutionary optimization, when tuned properly and combined with a detailed manufacturing cost model, acts as a powerful decisional tool for the identification of cost-effective purification strategies. © 2013 The Authors. Journal of Chemical Technology & Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. John Wiley & Sons, Ltd 2014-10 2013-12-26 /pmc/articles/PMC4258073/ /pubmed/25506115 http://dx.doi.org/10.1002/jctb.4267 Text en © 2013 The Authors. Journal of Chemical Technology & Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. http://creativecommons.org/licenses/by/3.0/ This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Allmendinger, Richard
Simaria, Ana S
Turner, Richard
Farid, Suzanne S
Closed-loop optimization of chromatography column sizing strategies in biopharmaceutical manufacture
title Closed-loop optimization of chromatography column sizing strategies in biopharmaceutical manufacture
title_full Closed-loop optimization of chromatography column sizing strategies in biopharmaceutical manufacture
title_fullStr Closed-loop optimization of chromatography column sizing strategies in biopharmaceutical manufacture
title_full_unstemmed Closed-loop optimization of chromatography column sizing strategies in biopharmaceutical manufacture
title_short Closed-loop optimization of chromatography column sizing strategies in biopharmaceutical manufacture
title_sort closed-loop optimization of chromatography column sizing strategies in biopharmaceutical manufacture
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4258073/
https://www.ncbi.nlm.nih.gov/pubmed/25506115
http://dx.doi.org/10.1002/jctb.4267
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