Streamlined process development using the Micro24 Bioreactor system

Warr, Steve; Betts, John; Ahmad, Shahina; Newell, Katy V; Finka, Gary

doi:10.1186/1753-6561-7-s6-p36

Cited by 3 publications

(2 citation statements)

References 1 publication

(3 reference statements)

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“…The working volume for each micro-bioreactor is less than 10 mL. This system has proven to be a useful tool for both mammalian cell cultures and microbial fermentation, and its scalability has been well documented [15].…”

Section: Stirred Micro-bioreactorsmentioning

confidence: 99%

Advanced Bioprocess Development and Biomanufacturing Technologies and High Throughput Miniature Bioreactors

Jiao¹,

Chen²

2016

Chinese Journal of Engineering Science

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Section: Stirred Micro-bioreactorsmentioning

confidence: 99%

Advanced Bioprocess Development and Biomanufacturing Technologies and High Throughput Miniature Bioreactors

Jiao¹,

Chen²

2016

Chinese Journal of Engineering Science

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“…Deep well plates (DWP) with a volume of 0.5–2 mL also have HT capabilities however similar to MTPs can be affected by poor mixing as their shaking is not comparable to mixing performed by impellers ( Ben-Tchavtchavadze, Perrier, and Jolicoeur, 2007 ; Huang and Kwiatkowski, 2015 ). Additional automated systems have also been developed such as the SimCell™ microfluidic and micro-bioreactor systems; the Pall Micro24 system with a deep well design, each mini reactor has a standard baffled design and a working volume of up to 7 mL ( Warr et al, 2013 ; Huang and Kwiatkowski, 2015 ). These systems have control units that monitor cell culture process parameters and can successfully predict key product quality attributes; it has also shown potential for scale-up applications through media screening and process optimisation ( Ravindran et al, 2019 ; Huang and Kwiatkowski, 2015 ; Whitford, 2006 ).…”

Section: Introductionmentioning

confidence: 99%

Next-generation cell line selection methodology leveraging data lakes, natural language generation and advanced data analytics

Goldrick

Alosert

Lovelady

et al. 2023

Front. Bioeng. Biotechnol.

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Cell line development is an essential stage in biopharmaceutical development that often lies on the critical path. Failure to fully characterise the lead clone during initial screening can lead to lengthy project delays during scale-up, which can potentially compromise commercial manufacturing success. In this study, we propose a novel cell line development methodology, referenced as CLD4, which involves four steps enabling autonomous data-driven selection of the lead clone. The first step involves the digitalisation of the process and storage of all available information within a structured data lake. The second step calculates a new metric referenced as the cell line manufacturability index (MICL) quantifying the performance of each clone by considering the selection criteria relevant to productivity, growth and product quality. The third step implements machine learning (ML) to identify any potential risks associated with process operation and relevant critical quality attributes (CQAs). The final step of CLD4 takes into account the available metadata and summaries all relevant statistics generated in steps 1–3 in an automated report utilising a natural language generation (NLG) algorithm. The CLD4 methodology was implemented to select the lead clone of a recombinant Chinese hamster ovary (CHO) cell line producing high levels of an antibody-peptide fusion with a known product quality issue related to end-point trisulfide bond (TSB) concentration. CLD4 identified sub-optimal process conditions leading to increased levels of trisulfide bond that would not be identified through conventional cell line development methodologies. CLD4 embodies the core principles of Industry 4.0 and demonstrates the benefits of increased digitalisation, data lake integration, predictive analytics and autonomous report generation to enable more informed decision making.

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The role of high-throughput mini-bioreactors in process development and process optimization for mammalian cell culture

Huang¹,

Kwiatkowski²

2015

Pharmaceutical Bioprocessing

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Streamlined process development using the Micro24 Bioreactor system

Cited by 3 publications

References 1 publication

Advanced Bioprocess Development and Biomanufacturing Technologies and High Throughput Miniature Bioreactors

Advanced Bioprocess Development and Biomanufacturing Technologies and High Throughput Miniature Bioreactors

Next-generation cell line selection methodology leveraging data lakes, natural language generation and advanced data analytics

The role of high-throughput mini-bioreactors in process development and process optimization for mammalian cell culture

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