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Model-Based Methods in the Biopharmaceutical Process Lifecycle
Model-based methods are increasingly used in all areas of biopharmaceutical process technology. They can be applied in the field of experimental design, process characterization, process design, monitoring and control. Benefits of these methods are lower experimental effort, process transparency, cl...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5736780/ https://www.ncbi.nlm.nih.gov/pubmed/29168076 http://dx.doi.org/10.1007/s11095-017-2308-y |
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author | Kroll, Paul Hofer, Alexandra Ulonska, Sophia Kager, Julian Herwig, Christoph |
author_facet | Kroll, Paul Hofer, Alexandra Ulonska, Sophia Kager, Julian Herwig, Christoph |
author_sort | Kroll, Paul |
collection | PubMed |
description | Model-based methods are increasingly used in all areas of biopharmaceutical process technology. They can be applied in the field of experimental design, process characterization, process design, monitoring and control. Benefits of these methods are lower experimental effort, process transparency, clear rationality behind decisions and increased process robustness. The possibility of applying methods adopted from different scientific domains accelerates this trend further. In addition, model-based methods can help to implement regulatory requirements as suggested by recent Quality by Design and validation initiatives. The aim of this review is to give an overview of the state of the art of model-based methods, their applications, further challenges and possible solutions in the biopharmaceutical process life cycle. Today, despite these advantages, the potential of model-based methods is still not fully exhausted in bioprocess technology. This is due to a lack of (i) acceptance of the users, (ii) user-friendly tools provided by existing methods, (iii) implementation in existing process control systems and (iv) clear workflows to set up specific process models. We propose that model-based methods be applied throughout the lifecycle of a biopharmaceutical process, starting with the set-up of a process model, which is used for monitoring and control of process parameters, and ending with continuous and iterative process improvement via data mining techniques. |
format | Online Article Text |
id | pubmed-5736780 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-57367802017-12-26 Model-Based Methods in the Biopharmaceutical Process Lifecycle Kroll, Paul Hofer, Alexandra Ulonska, Sophia Kager, Julian Herwig, Christoph Pharm Res Expert Review Model-based methods are increasingly used in all areas of biopharmaceutical process technology. They can be applied in the field of experimental design, process characterization, process design, monitoring and control. Benefits of these methods are lower experimental effort, process transparency, clear rationality behind decisions and increased process robustness. The possibility of applying methods adopted from different scientific domains accelerates this trend further. In addition, model-based methods can help to implement regulatory requirements as suggested by recent Quality by Design and validation initiatives. The aim of this review is to give an overview of the state of the art of model-based methods, their applications, further challenges and possible solutions in the biopharmaceutical process life cycle. Today, despite these advantages, the potential of model-based methods is still not fully exhausted in bioprocess technology. This is due to a lack of (i) acceptance of the users, (ii) user-friendly tools provided by existing methods, (iii) implementation in existing process control systems and (iv) clear workflows to set up specific process models. We propose that model-based methods be applied throughout the lifecycle of a biopharmaceutical process, starting with the set-up of a process model, which is used for monitoring and control of process parameters, and ending with continuous and iterative process improvement via data mining techniques. Springer US 2017-11-22 2017 /pmc/articles/PMC5736780/ /pubmed/29168076 http://dx.doi.org/10.1007/s11095-017-2308-y Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Expert Review Kroll, Paul Hofer, Alexandra Ulonska, Sophia Kager, Julian Herwig, Christoph Model-Based Methods in the Biopharmaceutical Process Lifecycle |
title | Model-Based Methods in the Biopharmaceutical Process Lifecycle |
title_full | Model-Based Methods in the Biopharmaceutical Process Lifecycle |
title_fullStr | Model-Based Methods in the Biopharmaceutical Process Lifecycle |
title_full_unstemmed | Model-Based Methods in the Biopharmaceutical Process Lifecycle |
title_short | Model-Based Methods in the Biopharmaceutical Process Lifecycle |
title_sort | model-based methods in the biopharmaceutical process lifecycle |
topic | Expert Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5736780/ https://www.ncbi.nlm.nih.gov/pubmed/29168076 http://dx.doi.org/10.1007/s11095-017-2308-y |
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