In addition to drastically reducing the time it takes to analyze genetic data, Omecu intends to bring its benefits to a much wider audience.
University of Edinburgh spin-out Omecu recently emerged from stealth and revealed its development of a powerful computing platform that simplifies and speeds up the analysis of genetic and epidemiological datasets. The company says its technology can reduce the time researchers spend preparing and analyzing this genetic data from days to seconds. It also aims to make this type of analysis accessible to researchers and clinicians who do not previously have the technical skills necessary to conduct it. While the platform is yet to be released, the founders of Omecu plan to launch the product before the end of the year.
Longevity.Tech: As interest and investment in the longevity industry continues to grow, there is growing demands for more basic research in ageing. This research can now be supported by the huge growth in genomic and genetic data being generated. But accessing and analyzing this data is both complex and time-consuming. With its goal of democratizing the analysis of genetic data, Omecu could offer an avenue to help scale up basic research being conducted in the field of longevity. We caught up with co-founders Dr. Oriol Canela-Xandri and CEO Les Gaw to find out more.
Working in the MRC’s Human Genetics Unit, and previously at the Roslin Institute, University of Edinburgh, Canela-Xandri focused on the challenge of extracting insights from genetic data and large datasets (such as those provided by the UK Biobank) for over eight years.
“There are a lot of challenges, whether it’s accessing the data or having the skills to extract the relevant data,” he says. “For example, scientists working on longevity or a specific disease often don’t have access to these kinds of resources, or the expertise to use them.”
Over the years, Canela-Xandri and her colleagues have tried various approaches to solving these problems, first using a supercomputer to analyze the data, then creating pre-computed results to aid in data exploration.
“All of these approaches created other challenges,” he says. “So we set out to create a platform that, on the one hand, vastly simplifies the interaction between data owners and data users by protecting the data – even from the analyst – thereby removing barriers such as data privacy and economic interest.On the other hand, we wanted to create a platform powerful enough to allow interaction with large data sets in real time using relatively inexpensive commercial-grade hardware assets.
Democratize the analysis of genetic data
Over the past three years, the team has been working on the algorithms, mathematical calculations and hardware that would underpin such a platform.
“We initially created a web interface to allow anyone to easily explore some pre-calculated results on UK Biobank data, and we received lots of feedback from around the world,” says Canela-Xandri. “Most interestingly, we heard from clinicians and people interested in specific traits and diseases who didn’t have the usual expertise, team, or IT resources to perform this type of analysis.
The development team also heard from researchers interested in the data presented but wanting to be able to interrogate the datasets in greater depth and in more flexible ways. For example, removing certain subsets of individuals, such as those taking a certain drug, removing individuals with a particular variant, or changing the definition of a disease.
“After two more years of research, we were able to create the basic calculation engine capable of performing this type of calculation on huge datasets in a second or two,” says Canela-Xandri. “And we were also able to provide the ability to query data through a web interface, allowing users to query data and change settings, while simultaneously ensuring data protection. At no time does any of the data leave the donor source. »
Spectacular time savings for researchers
The work has now reached the point where it is ready for commercialization – and thus Omecu was born.
“The lengthy process of retrieving the data, processing the data, and performing the analysis is estimated to take 80 or 90 percent of the time of highly skilled people,” Canela-Xandri says. “We estimate that our approach could reduce that to just 10% of their time, leaving them much more time to explore the data and find results.”
In terms of specific target users, Canela-Xandri says the Omecu is for anyone interested in simplifying the extraction of value from genomic and genetic data.
“Today there are many ways to query data, and many different people in different fields are interested in making such queries,” he says. “We have attracted interest from clinicians working in clinical practice to wet lab researchers. For example, one researcher we spoke to is interested in senescent cells and wants to see how he can explore UK Biobank data in this area.
While the time-saving improvement is in many ways an “easy sell” to researchers already involved in this type of analysis, the bigger goal, says Gaw, is the ability to reach a different audience.
“For those who are already using this data, they know what is needed now, so if we can demonstrate how we can do it faster, it’s an easy concept for them. But if you’re a clinician who doesn’t even know it’s possible, then you’re harder to reach, so the democratization aspect is probably our most ambitious goal.
Gaw acknowledges that the platform is not yet fully ready for market, but says that all capabilities are in place and that Omecu plans to “launch commercially within the next nine months”. To date, the company has been funded through grants, but Gaw is also starting to speak to investors about closing a seed funding round of between £500,000 and $1m by the end of June.
