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Integrated Process Model Applications Linking Bioprocess Development to Quality by Design Milestones
Maximizing the value of each available data point in bioprocess development is essential in order to reduce the time-to-market, lower the number of expensive wet-lab experiments, and maximize process understanding. Advanced in silico methods are increasingly being investigated to accomplish these go...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8614990/ https://www.ncbi.nlm.nih.gov/pubmed/34821722 http://dx.doi.org/10.3390/bioengineering8110156 |
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author | Taylor, Christopher Marschall, Lukas Kunzelmann, Marco Richter, Michael Rudolph, Frederik Vajda, Judith Presser, Beate Zahel, Thomas Studts, Joey Herwig, Christoph |
author_facet | Taylor, Christopher Marschall, Lukas Kunzelmann, Marco Richter, Michael Rudolph, Frederik Vajda, Judith Presser, Beate Zahel, Thomas Studts, Joey Herwig, Christoph |
author_sort | Taylor, Christopher |
collection | PubMed |
description | Maximizing the value of each available data point in bioprocess development is essential in order to reduce the time-to-market, lower the number of expensive wet-lab experiments, and maximize process understanding. Advanced in silico methods are increasingly being investigated to accomplish these goals. Within this contribution, we propose a novel integrated process model procedure to maximize the use of development data to optimize the Stage 1 process validation work flow. We generate an integrated process model based on available data and apply two innovative Monte Carlo simulation-based parameter sensitivity analysis linearization techniques to automate two quality by design activities: determining risk assessment severity rankings and establishing preliminary control strategies for critical process parameters. These procedures are assessed in a case study for proof of concept on a candidate monoclonal antibody bioprocess after process development, but prior to process characterization. The evaluation was successful in returning results that were used to support Stage I process validation milestones and demonstrated the potential to reduce the investigated parameters by up to 24% in process characterization, while simultaneously setting up a strategy for iterative updates of risk assessments and process controls throughout the process life-cycle to ensure a robust and efficient drug supply. |
format | Online Article Text |
id | pubmed-8614990 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-86149902021-11-26 Integrated Process Model Applications Linking Bioprocess Development to Quality by Design Milestones Taylor, Christopher Marschall, Lukas Kunzelmann, Marco Richter, Michael Rudolph, Frederik Vajda, Judith Presser, Beate Zahel, Thomas Studts, Joey Herwig, Christoph Bioengineering (Basel) Article Maximizing the value of each available data point in bioprocess development is essential in order to reduce the time-to-market, lower the number of expensive wet-lab experiments, and maximize process understanding. Advanced in silico methods are increasingly being investigated to accomplish these goals. Within this contribution, we propose a novel integrated process model procedure to maximize the use of development data to optimize the Stage 1 process validation work flow. We generate an integrated process model based on available data and apply two innovative Monte Carlo simulation-based parameter sensitivity analysis linearization techniques to automate two quality by design activities: determining risk assessment severity rankings and establishing preliminary control strategies for critical process parameters. These procedures are assessed in a case study for proof of concept on a candidate monoclonal antibody bioprocess after process development, but prior to process characterization. The evaluation was successful in returning results that were used to support Stage I process validation milestones and demonstrated the potential to reduce the investigated parameters by up to 24% in process characterization, while simultaneously setting up a strategy for iterative updates of risk assessments and process controls throughout the process life-cycle to ensure a robust and efficient drug supply. MDPI 2021-10-24 /pmc/articles/PMC8614990/ /pubmed/34821722 http://dx.doi.org/10.3390/bioengineering8110156 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Taylor, Christopher Marschall, Lukas Kunzelmann, Marco Richter, Michael Rudolph, Frederik Vajda, Judith Presser, Beate Zahel, Thomas Studts, Joey Herwig, Christoph Integrated Process Model Applications Linking Bioprocess Development to Quality by Design Milestones |
title | Integrated Process Model Applications Linking Bioprocess Development to Quality by Design Milestones |
title_full | Integrated Process Model Applications Linking Bioprocess Development to Quality by Design Milestones |
title_fullStr | Integrated Process Model Applications Linking Bioprocess Development to Quality by Design Milestones |
title_full_unstemmed | Integrated Process Model Applications Linking Bioprocess Development to Quality by Design Milestones |
title_short | Integrated Process Model Applications Linking Bioprocess Development to Quality by Design Milestones |
title_sort | integrated process model applications linking bioprocess development to quality by design milestones |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8614990/ https://www.ncbi.nlm.nih.gov/pubmed/34821722 http://dx.doi.org/10.3390/bioengineering8110156 |
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