Posted on 27 October 2014
The business is based on innovative computer modelling software developed with support from C2D2. This software can help drug developers predict the effects of new drugs on autoimmune diseases, such as Rheumatoid Arthritis, Type 1 Diabetes, and Multiple Sclerosis.
The creation of SimOmics is the result of eight years of collaborative research by the University of York and the Torrey Pines Institute for Molecular Studies (TPIMS) in the USA and aims to support the 3Rs agenda: replacement, refinement and reduction of animals in research.
Recently SimOmics won its first major contract as part of a consortium led by York’s Centre for Immunology and Infection (CII). The consortium has successfully secured a £1 million award to create a computer-based “virtual laboratory” to aid the search for new treatments for leishmaniasis, a worldwide parasitic disease associated with poverty.
Professor Jon Timmis, RAE Research Fellow in the University's Department of Electronics and Chief Executive of SimOmics said: “SimOmics is an exciting development for the Yorkshire region and demonstrates how research at York can have a direct impact on society as a whole. In the long-term our software will result in a more efficient drug pipeline, which will allow drug manufacturers to get drugs out to the people who need them more quickly and cheaply.”
The new modelling software is capable of integrating more data types than current systems and has two key areas of application in the field of immune and inflammatory diseases – therapeutic development and personalised medicine.
Autoimmune and inflammatory conditions, where the immune system attacks its own tissues, affect 10 per cent of the UK’s adult population and are a leading cause of death and disability.
Dr Mark Coles, Senior Lecturer in CII and Chief Scientific Officer, SimOmics said: “We are excited at the prospect of supporting the UK pharmaceutical and bio-tech industry and helping them to get their products from the lab to the marketplace more efficiently. Use of this technology is expected to significantly reduce the necessity for animal testing in therapeutic development and produce a better understanding of how patient heterogeneity and compliance affects clinical trial outcomes.”
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