University of Edinburgh spinout company Omecu Ltd is developing a high-performance genomics and health data analysis platform that promises to democratise analysis of genomic data and cut the time it takes to analyse millions of genetic records from days to seconds.
Estimates show that global human genomic data is doubling in size every seven months and could soon exceed other big data generators such as astronomy and the internet. This data has the potential to revolutionise medicine and lead to new therapeutics and diagnostics, but unlocking these innovations relies on the ability to access clinically actionable knowledge from the data – a very costly and time-consuming process that can often prevent the extraction of valuable information.
Democratising genomic data access
At the University of Edinburgh, scientists Dr Oriol Canela-Xandri at the MRC Human Genetics Unit, Institute of Genetics and Cancer, and Dr Konrad Rawlik and Professor Albert Tenesa at the Roslin Institute had spent over three years researching how useful knowledge could be extracted from large genomic datasets in a time- and cost-efficient manner, and without exposing the data itself – not even to the analyst.
The academic team has been supported by Edinburgh Innovations (EI) since 2019, and in 2021 they co-founded Omecu as a spinout company with CEO Les Gaw, an experienced entrepreneur, investor and adviser to early-stage technology companies, who was introduced to the research team by EI.
Faster, better insights for less
The Omecu team has developed a computation engine and web platform that are capable of powerful and highly sophisticated analyses, giving researchers the freedom to interactively query multiple federated genomic datasets and get the answers they need in seconds. And because the developed algorithms are highly efficient, Omecu reduces hardware and operating costs as well as processing time. The company’s proprietary high-performance algorithms are transforming how federated genomic and health data is securely accessed and efficiently analysed in medical research, and promise wide-ranging benefits in drug discovery and personalised medicine, while improving patient data security.
