Scientists at the MRC Human Genetics Unit of Edinburgh University and the Roslin Institute have launched a spinout company that aims to democratise genetic data access — and cut from days to minutes the time it takes to analyse millions of genetic record.
Omecu Ltd promises “wide-ranging benefits in drug discovery and personalised medicine, while improving patient data security.”
The company draws on three years of research led by Dr Oriol Canela-Xandri at the MRC Human Genetics Unit and Dr Konrad Rawlik at the university’s Roslin Institute.
It has been launched with the support of Edinburgh Innovations, the university’s commercialisation service.
It is estimated that global human genomic data is doubling in size every seven months and may soon exceed other big data generators such as astronomy and the internet.
Although this data has the potential to revolutionise medicine and lead to new therapeutics and diagnostics, these benefits rely on the ability to unlock clinically actionable knowledge from the data.
Obstacles to accessing such data can prevent valuable information being extracted, by making the process very costly and time-consuming.
The Omecu team has developed a computation engine and web platform that will transform how genomic data is securely accessed and efficiently analysed.
Canela-Xandri and Rawlik have been supported by Edinburgh Innovations since 2019.
They participated in the SETSquared ICURe programme in 2020, and received funding from Medical Research Council grants and the University’s Data-Driven Entrepreneurship Seed Fund and Fast Track Mentor initiatives, supported by the Scottish Funding Council.
They were recently awarded £288,000 from Innovate UK, which will allow Omecu to refine its prototype and progress commercial engagement.
Omecu is co-founded by Canela-Xandri and Rawlik alongside CEO Les Gaw, an experienced entrepreneur, investor and adviser to early-stage technology companies, who was introduced to the research team by Edinburgh Innovations.
“Our ambition is to create a paradigm shift where disease experts without a computer science background are able to easily query fragmented data sets, while cutting costs and without requiring the data-holding organisation to expose the data itself,” said Canela-Xandri.