A roadmap for model-based bioprocess development

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dc.contributor.authorMu’azzam, Khadija
dc.contributor.authorda Silva, Francisco Vitor Santos
dc.contributor.authorMurtagh, Jason
dc.contributor.authorSousa Gallagher, Maria Jose
dc.date.accessioned2024-06-05T06:03:41Z
dc.date.available2024-05-30T18:14:49Zen
dc.date.available2024-06-05T06:03:41Z
dc.date.issued2024-05-22
dc.date.updated2024-05-30T17:14:53Zen
dc.description.abstractThe bioprocessing industry is undergoing a significant transformation in its approach to quality assurance, shifting from the traditional Quality by Testing (QbT) to Quality by Design (QbD). QbD, a systematic approach to quality in process development, integrates quality into process design and control, guided by regulatory frameworks. This paradigm shift enables increased operational efficiencies, reduced market time, and ensures product consistency. The implementation of QbD is framed around key elements such as defining the Quality Target Product Profile (QTPPs), identifying Critical Quality Attributes (CQAs), developing Design Spaces (DS), establishing Control Strategies (CS), and maintaining continual improvement. The present critical analysis delves into the intricacies of each element, emphasizing their role in ensuring consistent product quality and regulatory compliance. The integration of Industry 4.0 and 5.0 technologies, including Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), and Digital Twins (DTs), is significantly transforming the bioprocessing industry. These innovations enable real-time data analysis, predictive modelling, and process optimization, which are crucial elements in QbD implementation. Among these, the concept of DTs is notable for its ability to facilitate bi-directional data communication and enable real-time adjustments and therefore optimize processes. DTs, however, face implementation challenges such as system integration, data security, and hardware-software compatibility. These challenges are being addressed through advancements in AI, Virtual Reality/ Augmented Reality (VR/AR), and improved communication technologies. Central to the functioning of DTs is the development and application of various models of differing types – mechanistic, empirical, and hybrid. These models serve as the intellectual backbone of DTs, providing a framework for interpreting and predicting the behaviour of their physical counterparts. The choice and development of these models are vital for the accuracy and efficacy of DTs, enabling them to mirror and predict the real-time dynamics of bioprocessing systems. Complementing these models, advancements in data collection technologies, such as free-floating wireless sensors and spectroscopic sensors, enhance the monitoring and control capabilities of DTs, providing a more comprehensive and nuanced understanding of the bioprocessing environment. This review offers a critical analysis of the prevailing trends in model-based bioprocessing development within the sector.en
dc.description.statusPeer revieweden
dc.description.versionPublished Version
dc.format.mimetypeapplication/pdfen
dc.identifier.articleid108378
dc.identifier.citationMu'azzam, K., da Silva, F. V. S., Murtagh, J. and Sousa Gallagher, M. J. (2024) 'A roadmap for model-based bioprocess development', Biotechnology Advances, 73, 108378 (11pp). https://doi.org/10.1016/j.biotechadv.2024.108378en
dc.identifier.doihttps://doi.org/10.1016/j.biotechadv.2024.108378en
dc.identifier.eissn1873-1899
dc.identifier.endpage11
dc.identifier.issn0734-9750
dc.identifier.journaltitleBiotechnology Advances
dc.identifier.startpage1
dc.identifier.urihttps://hdl.handle.net/10468/15980
dc.identifier.volume73
dc.language.isoenen
dc.publisherElsevier Inc.
dc.rights© 2024, the Authors. Published by Elsevier Inc. This is an open access article under the CC BY license.en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectQuality by design
dc.subjectDesign space
dc.subjectIndustry 4.0
dc.subjectIndustry 5.0
dc.subjectDigital twins
dc.subjectProcess modelling
dc.subjectProcess simulation
dc.subjectBiopharmaceutical manufacturing
dc.titleA roadmap for model-based bioprocess developmenten
dc.typeArticle (peer-reviewed)
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