MICA: Exploiting in silico modelling to address the translational bottleneck in regenerative medicine safety

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Stem cells have great potential in medicine as then can grow into many different cell types in the body. One way of treating damaged tissues and organs is to transplant stem cells or cells derived from stem cells into the damaged organ - this kind of treatment is know as a cell therapy and an example of this used today is bone marrow transplantation. Whilst this treatment is successful for many diseases, in some cases this treatment does not work and the cells do not grow well. To develop new treatments for patients we require research tools that look at the safety of using cell therapies as well as look at the "immune response" e.g. how our body naturally reacts when a cell therapy is introduced. It is also important to look at how safe and efficient a cell therapy is. Our project team want to develop a range of tools that will answer these questions and speed up the process for developing new treatments for patients who are currently suffering form untreatable diseases. For this project, the team are going to look at liver disease. There are many problems with giving a patient a cell therapy: (1) making sure that the new cells end up at the site of injury/damaged tissue; (2) will the body can end up "attacking" these cells as part of the body's natural immune system; (3) do the cells attach onto the injured organ; (4) do the cells carry out their role within the body.The project team are going to use a combination of maths and biology in order to answer these questions. The project has the potential to produce a framework that could be used to help get new treatments out of a laboratory situation and heading towards being used as a treatment for a patient. Whilst liver disease is being used as a disease example for this project, the same tools could be used for a range of different diseases.