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Chromatographic parameter determination for complex biological feedstocks
The application of mechanistic models for chromatography requires accurate model parameters. Especially for complex feedstocks such as a clarified cell harvest, this can still be an obstacle limiting the use of mechanistic models. Another commonly encountered obstacle is a limited amount of sample m...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6175100/ https://www.ncbi.nlm.nih.gov/pubmed/29693326 http://dx.doi.org/10.1002/btpr.2642 |
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author | Pirrung, Silvia M. Parruca da Cruz, Diogo Hanke, Alexander T. Berends, Carmen Van Beckhoven, Ruud F.W.C. Eppink, Michel H.M. Ottens, Marcel |
author_facet | Pirrung, Silvia M. Parruca da Cruz, Diogo Hanke, Alexander T. Berends, Carmen Van Beckhoven, Ruud F.W.C. Eppink, Michel H.M. Ottens, Marcel |
author_sort | Pirrung, Silvia M. |
collection | PubMed |
description | The application of mechanistic models for chromatography requires accurate model parameters. Especially for complex feedstocks such as a clarified cell harvest, this can still be an obstacle limiting the use of mechanistic models. Another commonly encountered obstacle is a limited amount of sample material and time to determine all needed parameters. Therefore, this study aimed at implementing an approach on a robotic liquid handling system that starts directly with a complex feedstock containing a monoclonal antibody. The approach was tested by comparing independent experimental data sets with predictions generated by the mechanistic model using all parameters determined in this study. An excellent agreement between prediction and experimental data was found verifying the approach. Thus, it can be concluded that RoboColumns with a bed volume of 200 μL can well be used to determine isotherm parameters for predictions of larger scale columns. Overall, this approach offers a new way to determine crucial model input parameters for mechanistic modelling of chromatography for complex biological feedstocks. © 2018 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 34:1006–1018, 2018 |
format | Online Article Text |
id | pubmed-6175100 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-61751002018-10-15 Chromatographic parameter determination for complex biological feedstocks Pirrung, Silvia M. Parruca da Cruz, Diogo Hanke, Alexander T. Berends, Carmen Van Beckhoven, Ruud F.W.C. Eppink, Michel H.M. Ottens, Marcel Biotechnol Prog RESEARCH ARTICLES The application of mechanistic models for chromatography requires accurate model parameters. Especially for complex feedstocks such as a clarified cell harvest, this can still be an obstacle limiting the use of mechanistic models. Another commonly encountered obstacle is a limited amount of sample material and time to determine all needed parameters. Therefore, this study aimed at implementing an approach on a robotic liquid handling system that starts directly with a complex feedstock containing a monoclonal antibody. The approach was tested by comparing independent experimental data sets with predictions generated by the mechanistic model using all parameters determined in this study. An excellent agreement between prediction and experimental data was found verifying the approach. Thus, it can be concluded that RoboColumns with a bed volume of 200 μL can well be used to determine isotherm parameters for predictions of larger scale columns. Overall, this approach offers a new way to determine crucial model input parameters for mechanistic modelling of chromatography for complex biological feedstocks. © 2018 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 34:1006–1018, 2018 John Wiley and Sons Inc. 2018-07-01 2018 /pmc/articles/PMC6175100/ /pubmed/29693326 http://dx.doi.org/10.1002/btpr.2642 Text en © 2018 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | RESEARCH ARTICLES Pirrung, Silvia M. Parruca da Cruz, Diogo Hanke, Alexander T. Berends, Carmen Van Beckhoven, Ruud F.W.C. Eppink, Michel H.M. Ottens, Marcel Chromatographic parameter determination for complex biological feedstocks |
title | Chromatographic parameter determination for complex biological feedstocks |
title_full | Chromatographic parameter determination for complex biological feedstocks |
title_fullStr | Chromatographic parameter determination for complex biological feedstocks |
title_full_unstemmed | Chromatographic parameter determination for complex biological feedstocks |
title_short | Chromatographic parameter determination for complex biological feedstocks |
title_sort | chromatographic parameter determination for complex biological feedstocks |
topic | RESEARCH ARTICLES |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6175100/ https://www.ncbi.nlm.nih.gov/pubmed/29693326 http://dx.doi.org/10.1002/btpr.2642 |
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