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Details of Grant 

EPSRC Reference: EP/R031649/1
Title: Developing Efficient Models to Define Economic and Low Risk High Value Manufacture of Cell Based Products
Principal Investigator: Thomas, Professor RJ
Other Investigators:
Dickson, Professor AJ
Researcher Co-Investigators:
Project Partners:
Department: Wolfson Sch of Mech, Elec & Manufac Eng
Organisation: Loughborough University
Scheme: Standard Research
Starts: 01 December 2018 Ends: 30 November 2021 Value (£): 406,203
EPSRC Research Topic Classifications:
Bioprocess Engineering Macro-molecular delivery
Manufacturing Machine & Plant
EPSRC Industrial Sector Classifications:
Manufacturing Healthcare
Related Grants:
Panel History:
Panel DatePanel NameOutcome
22 Feb 2018 Manufacturing Prioritisation Panel - Feb 2018 Announced
Summary on Grant Application Form
New treatments for disease are increasingly made from biological materials rather than the chemicals in conventional drugs. The most advanced of these treatments use humans cells as treatments for serious and incurable diseases. Recent successes include dramatic long term remission of previously untreatable blood cancers. However, the manufacturing of such products is highly complex compared to a conventional drug. Products have to be 'grown', sometime over weeks or months, rather than quickly synthesised in a chemical reactor. This creates many challenges for manufacture. In particular there are many opportunities for the manufacturing environment to move outside an acceptable range. This can mean the product grows into the wrong number or type of cells. Further, cells talk to each other through the release of small signalling agents and deplete things from the environment around them. This creates a complex system that evolves over time, and a potentially very expensive system to handle for a manufacturer. Many current manufacturing processes for these new treatments are exceedingly inefficient and high risk due to a poor understanding of these issues.

We propose to create mathematical models of these relationships so that manufacturers can create their products at lower cost and with lower risk of process failure. We propose to use different types of modelling for optimum efficiency. The first will efficiently screen for things that affect the cells being grown. The second is a specific type of modelling that describes a system in terms of the rate of change of its components and is therefore good for modelling systems that evolve with time. These models will help us understand how to control manufacture for maximum efficiency and acceptable risk.

Avoiding process failure is very important because some of these products could be dangerous if the wrong cells are produced. Furthermore if a patient's own cells are being grown to treat them there is no replacement product available if manufacture fails. If we succeed it will help the UK see more ground breaking therapies at market as well as supporting a high value manufacturing industry contributing to UK economic growth.

Key Findings
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Potential use in non-academic contexts
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Date Materialised
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Further Information:  
Organisation Website: http://www.lboro.ac.uk