Tech spin-out to boost drug discovery with streamlined analysis of genomic data
A new University of Edinburgh spin-out company aims to transform how genomic data is securely accessed and analysed, with benefits for drug discovery and personalised medicine.
Omecu Ltd was developed following an Medical Research Council (MRC) Confidence in Concept project, part-funded by the Usher Institute Health and Social Care, a delivery hub within the Data-Driven Innovation Programme of the Edinburgh and South East Scotland City Region Deal.
A huge volume of human genomic data exists across the world, which could be harnessed to improve health and care. However, major barriers can limit the ability of researchers to analyse these complex datasets and extract the important information they hold, resulting in a lengthy and expensive process.
A new platform, developed by the Omecu team, aims to democratise genomic data access and cut from days to minutes the time it takes to analyse millions of genetic records. The technology enables significantly faster analysis, without the user requiring technical skills or access to individual-level data.
The concept was developed based on University of Edinburgh research from Dr Oriol Canela-Xandri at the MRC Human Genetics Unit within the Institute of Genetics and Cancer, and Dr Konrad Rawlik at the Roslin Institute.
Doctors Canela-Xandri and Rawlik were awarded an MRC Confidence in Concept (CiC) grant in 2020 to develop their platform, part-funded by the Health and Social Care Data-Driven Innovation Hub.
Omecu was formed as a spin-out company following the success of the project and has since gone on to receive additional funding from Innovate UK to refine its prototype and progress commercial engagement.
Dr Oriol Canela-Xandri, Chancellor’s Fellow, University of Edinburgh, said;” 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.
Our recent funding awards mean we can now accelerate the development of our prototype and move towards a commercial product.”