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Details of Grant 

EPSRC Reference: EP/R041695/1
Principal Investigator: Marucci, Dr L
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Helmholtz Association
Department: Engineering Mathematics
Organisation: University of Bristol
Scheme: Standard Research - NR1
Starts: 01 February 2018 Ends: 30 April 2020 Value (£): 250,704
EPSRC Research Topic Classifications:
Control Engineering Microsystems
Synthetic biology
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:  
Summary on Grant Application Form
Stem cells are pluripotent cells that can both proliferate indefinitely producing cells identical to them, and specialise into more mature cells types. In adults, stem cells have a repair function in case of damage; adult stem cells are currently used in medical therapy. The major limitation of adult stem cells' medical applications is their low availability, and the difficulty to expand them in culture.

Such issues were thought to be overcome thanks to the astonishing discovery of reprogramming by the Nobel Prize-winning Shinya Yamanaka: differentiated (i.e. somatic) cells can be programmed back to a stem-like state, obtaining the so-called induced Pluripotent Stem Cells (iPSCs). iPSCs can be subsequently converted into any cell type, to be used for regenerative and personalised medicine purposes. In Japan, the first clinical trial using iPSC-derived cells in humans is on going to cure age-related macular degeneration.

iPSC therapy still faces, however, major challenges: it is difficult to reprogram somatic cells and maintain iPSCs in the pluripotent state; also, iPSC differentiation is often inefficient.

In this research, we aim at applying state-of-the-art Synthetic Biology and Control Engineering tools to automatize and optimise the manufacturing of iPSC-derived cells. We will prove, using mouse cell lines, that each of the 3 mentioned challenges can be addressed if, while providing inputs that trigger pluripotency or differentiation, cells are continuously observed and inputs are consequently "adjusted" to obtain the target phenotype. This closed-loop strategy will be implemented by means of microfluidics and microscopy, that allow monitoring in real-time living cells, comparing relevant cellular outputs to the target one and applying control algorithms that allow acting on the cells to minimise the error.

While proving that, by "closing the loop", it is possible to automatically control stem cell fate, we will provide a platform that allows, at the end of the experiment, to retrieve from the microfluidics device the desired cell type with high efficiency and reproducibility.

Key Findings
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Organisation Website: http://www.bris.ac.uk