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Application of response surface methodology to maximize the productivity of scalable automated human embryonic stem cell manufacture

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journal contribution
posted on 18.09.2013, 14:15 by Elizabeth Ratcliffe, Paul Hourd, Juan-Jose Guijarro-Leach, Erin Rayment, David Williams, Rob Thomas
Aim: Commercial regenerative medicine will require large quantities of clinical-specification human cells. The cost and quality of manufacture is notoriously difficult to control due to highly complex processes with poorly defined tolerances. As a step to overcome this, we aimed to demonstrate the use of ‘quality-by-design’ tools to define the operating space for economic passage of a scalable human embryonic stem cell production method with minimal cell loss. Materials & methods: Design of experiments response surface methodology was applied to generate empirical models to predict optimal operating conditions for a unit of manufacture of a previously developed automatable and scalable human embryonic stem cell production method. Results & conclusion: Two models were defined to predict cell yield and cell recovery rate postpassage, in terms of the predictor variables of media volume, cell seeding density, media exchange and length of passage. Predicted operating conditions for maximized productivity were successfully validated. Such ‘quality-by-design’ type approaches to process design and optimization will be essential to reduce the risk of product failure and patient harm, and to build regulatory confidence in cell therapy manufacturing processes.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Citation

RATCLIFFE, E. ... et al, 2013. Application of response surface methodology to maximize the productivity of scalable automated human embryonic stem cell manufacture. Regenerative Medicine, 8 (1), pp. 39 - 48.

Publisher

© Future Medicine Ltd

Version

VoR (Version of Record)

Publication date

2013

Notes

This article was published in the journal, Regenerative Medicine [© Future Medicine Ltd] http://www.futuremedicine.com

ISSN

1746-0751

Language

en

Exports