Seqera Labs grabs $5.5M to help sequence Covid-19 variants and other

Bringing order and understanding to unstructured information housed in isolated silos has been one of the more significant successes of the big data era, and today a European startup has sought to help address this challenge, particularly in the life sciences. A platform has been created – and is, in particular, used by laboratories to sequence and identify two major COVID-19 variants so far – to continue building their tools for a broader set of use cases. and is announcing some funding to expand into North America.

Secera Labs, a Barcelona-based data orchestration and workflow platform designed to help scientists and engineers order and gain insights from cloud-based genomic data troves, as well as tackle other life science applications , which involves accessing complex data from multiple locations. $5.5 million in seed funding.

talis capital And speedinvest Also co-led this round, with participation from previous backers BoxOne Ventures and grant from Chan Zuckerberg Initiative, Mark Zuckerberg and Dr. Priscilla Chan’s effort to support open source software projects for science applications.

Seqera – a portmanteau of “sequence” and “era”, the age of sequencing data, originally – previously raised less than $1 million, and quietly, it is already generating revenue, the world’s five largest drugstores. Shares of its customer base with companies, along with biotech and other life sciences customers.

Secera was spun out of the Center for Genomic Regulation, a biomedical research center based out of Barcelona, ​​where it was created as a commercial application of NextFlow, the open-source workflow and data orchestration software that originally originated from Secera, was created by the founders of Ivan Floden and. In Paolo Di Tomaso, Cgr.

Secera CEO Flodden told that he and Di Tomaso were expected to move to 2018 after NextFlow gained a lot of traction in the life sciences community, and subsequently received a lot of repeated requests for further customizations and features. I was inspired to create Secera. Both NextFlow and Secera have seen a lot of usage: The NextFlow runtime has been downloaded more than 2 million times, the company said, while Secera’s commercial cloud offering has now processed more than 5 billion tasks.

The COVID-19 pandemic is a classic example of the acute challenge that Secera (and by association NextFlow) has to address in the scientific community. With the outbreak of COVID-19 occurring globally, live genetic samples of the virus are collected every time a test for COVID-19 is processed in a laboratory. Taken together, these millions of tests represent a goldmine of information about the coronavirus and how it mutates, and when and where it is doing so. For a new virus that is little understood and still persists, that is invaluable data.

So the problem is not that the data exists for better insight (it does); is that it is nearly impossible to use more legacy tools to view that data as a composite body. It’s in a lot of places, and there’s a lot more, and it’s growing every day (and changing every day), which means it’s just a matter of running analysis over traditional methods of porting data to one centralized location. Wouldn’t be efficient, and would cost a fortune to execute.

That’s where Segera comes in. The company’s technology treats each source of data as a major pipeline across different clouds that can be merged and analyzed as a single entity, without leaving the limitations of the data infrastructure where it already exists. . Optimized to focus on genomic troves, scientists can then query that information for more information. Secera was central to the discovery of both alpha and delta forms of the virus, and work is still ongoing as COVID-19 continues to affect the world.

Seqera is being used in other types of medical applications, such as within the realm of so-called “precision medicine”. This is emerging as a huge opportunity in complex fields such as oncology: cancers mutate and behave differently depending on many factors, including the genetic differences of the patients themselves, meaning that treatments are less effective. If they are “one size fits all.” Increasingly, we are seeing approaches that leverage machine learning and big data analytics to better understand individual cancers and subsequently how they evolve for different populations to create more personalized treatments, And Secera comes in as a way to index that kind of data.

It also highlights something else notable about the Seqera platform: it is used directly by the people who are analyzing the data – that is, the researchers and the scientists themselves, without the need for data experts to be involved. It was a practical priority for the company, Floden told me, but still, it’s an interesting detail as to how the platform is inadvertently part of a larger trend of “no-code/low-code” software that has been developed through highly technical processes. designed to be usable. by non-technical people.

It’s both the current opportunities, and how Secera can be implemented in other types of data that live in the cloud in the future, that makes it an interesting company, and it seems like an interesting investment as well.

“Advances in machine learning, and the proliferation of volumes and types of data, are leading to more and more applications of computer science in the life sciences and biology,” Talis Capital principal Kirill Tasilov said in a statement. “While this is incredibly exciting from a humanitarian point of view, it is driving up the cost of experiments, sometimes up to millions of dollars per project as they become computer-heavy and complex to run. NextFlow is already in this area. is an all-encompassing solution and Seqera is driving those capabilities at an enterprise level – and in doing so, bringing the entire life sciences industry into the modern era. We are thrilled to be part of Seqera’s journey.”

“With the explosion of biological data from cheap, commercial DNA sequencing, there is a critical need to analyze an ever-increasing and complex amount of data,” said Arnaud Bakker, principal at SpeedInvest. “Secera’s open and cloud-first framework provides an advanced tooling kit that allows organizations to scale complex deployments of data analysis and enable data-driven life science solutions.”

Although medicine and the life sciences are probably the most obvious and timely applications of Secera today, the framework, originally designed for genetics and biology, can be applied to many other fields: AI training, image analysis and astronomy. There are early use cases, Floden said. Astronomy is probably very fitting, as it seems that the sky is the limit.

“We think we are in the century of biology,” Floden said. “It’s a hub of activity and it’s becoming data-centric, and we’re here to build services around that.”

Secera is not disclosing its valuation.

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