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Lifebit's Updated CloudOS Looks to Alleviate Bottlenecks in Population-Level Data Analyses


CHICAGO – A month ago, Lifebit Biotech announced that it had closed a £6 million ($7.4 million) Series A funding round. Idinvest Partners led the round, with participation from previous investors Pentech Ventures, Beacon Capital, and Connect Ventures. 

London-based Lifebit said that it will use the cash infusion for continued product development, and to expand its global reach. Now, the company mostly has clients in Europe and the US.

"The idea is to expand further in US. That's where we are first targeting," Cofounder and CEO Maria Chatzou Dunford said.

The firm does not have a US office, but is looking to set up a stateside subsidiary after the COVID-19 pandemic eases, to increase the level of services and support it can offer its existing and prospective customers.

The same week as the funding news, the company released an update to Lifebit Cloud OS, its genomics operating system that functions as a managed service of individual clouds or high-performance computing centers to support analysis of bioinformatics data across sites and institutions. Notably, CloudOS version 2.0 integrates a new feature called Biobank Data Browser for querying large sets of structured omics, phenotypic, and clinical data from sources including the UK Biobank. 

Chatzou Dunford noted the "bottleneck" from researchers having to sort through large-scale datasets such as the UK Biobank with other bioinformatics tools. Lifebit built version 2.0 to the scale of 10 million people and more than 3 billion variants, the company said.

The data browser in Lifebit CloudOS 2.0 simplifies the building and comparison of cohorts and running analyses against biobank data, Chatzou Dunford said, even on the scale of hundreds of thousands or even millions of patients for population-level studies. The new release integrates with JupyterLab, a tool for developing Jupyter notebooks, code, and data.

Custom cohorts can be used as inputs for analysis, including genome-wide association studies and polygenic risk scores, according to Lifebit. Users also can bring their own data into Lifebit CloudOS for analysis.

In a way, CloudOS is an informatics platform that also offers managed services. "We've come very far from what was the initial prototype with Nextflow to what was Lifebit CloudOS is today," Chatzou Dunford said.

Chatzou Dunford and her other cofounder, Lifebit CTO Pablo Prieto Barja helped create the Nextflow open-source programming framework when they were working on their respective PhDs at the Centre for Genomic Regulation in Barcelona, Spain, in 2012. The two had noticed that they were spending about 80 percent of their time on computational tasks rather than on conducting research or understanding results.

Nextflow quickly gained reputation for making bioinformatics processes more efficient and picked up a strong user base worldwide, but the free software had limitations.

"What we actually soon realized is that all of these people using Nextflow, they still need to build on top of it custom software and hardware solutions in order to be able to further analyze this data and get insight," Chatzou Dunford told GenomeWeb in 2017. That requires programmers and bioinformaticians.

"The second problem is that in order to use Nextflow, you need to be able to program and you need to be a bioinformatician. That means that only about 20,000 people on this planet can really use Nextflow. That's a huge barrier."

Chatzou Dunford and Prieto Barja thus founded Lifebit in 2017 to build services and components on top of the open-source Nextflow framework, combining high-performance computing with artificial intelligence

In 2017, high-tech business accelerator Techstars chose Lifebit for a three-month program in London, which came with a €120,000 ($132,000) award and the opportunity to present its technology to potential investors. During that program, Lifebit cut monthlong DNA analyses down to about one day and lowered computational costs from $10 to $1 per sample.

The firm raised $3 million in seed funding a year later.

Chatzou Dunford compared the new integrated browser to copying photos between folders on a laptop computer. It takes a few seconds or even minutes to copy a group of images to a USB stick, but the operation is almost instant when dragging the files to the desktop. That is because the movement to the desktop is virtual, just a visual pointer to the real file location on the hard drive rather than an actual duplication of files.

"Now imagine genomics and big multiomics and biomedical data living on different areas of the cloud, on different storage locations across the cloud, on different multi-cloud systems," Chatzou Dunford said. Lifebit Cloud OS creates visual pointers to the files.

"You can move these data instantly around. You can combine them, you can delete them, you can duplicate them instantly. All of these are virtualized links, virtual copies of your actual data on your cloud," Chatzou Dunford said.

This allows users to analyze data even if the actual files are on different cloud platforms.

AI helps manage and accelerate this data flow and reduce operating costs by flagging public-domain and local data that users might want to consider for specific analytics tasks, Chatzou Dunford said.

"For those patients now, you have the genomic data, you have the clinical data, you have the phenotypic data. You maybe have imaging data," Chatzou Dunford said. "The idea is, how can you have a very simple way [to] identify different individuals and different cloud cohorts in these big collections of cohorts or the general dataset that you have."

The technology is meant for research purposes; Lifebit is not directly selling to hospitals for clinical use, according to Chatzou Dunford, though the company does support clinical research as well as academic studies and drug discovery. Lifebit's client base mostly includes pharmaceutical and biotech companies, research labs including the Jackson Laboratory, and academic collaborations such the London-based Centre for Population Genomic Medicine.

Chatzou Dunford said that the company has two patents pending in the UK related to its artificial intelligence, and several more are in the works.

CloudOS is compatible with multiple cloud services, including the big three: Amazon Web Services, Google Cloud, and Microsoft Azure.

Jackson Lab connection

The Jackson Laboratory came on board after Anne Deslattes Mays, principal computational scientist at Jax's Farmington, Connecticut, location, met Chatzou Dunford and Prieto Barja at BioData World Congress in Basel, Switzerland in November 2018. Mays had presented on long-read RNA sequencing and how new measurement technologies affects data commons, a topic Mays said that Lifebit executives had not been all that familiar with.

A few months later, Mays was a leader of the FAIR Data Hackathon at the Bio-IT World Conference & Expo in Boston, and invited Lifebit to participate.

"That was the first time I was working to try to make data for Jax findable, accessible, interoperable, reuseable in a hackathon setting," Mays recalled. Participants followed World Wide Web Consortium standards for data access and exchange.

From that point, Jax formed a working relationship with Lifebit.

The New England research lab is transforming to community-based workflow languages, including the Broad Institute's Cromwell and Workflow Description Language (WDL), as well as Nextflow.

Lifebit's founders visited Jax last fall to give instruction to principal investigators and to doctoral and postdoctoral students about Nextflow and Jupyter notebooks.

"Where this is transformational is that we really do want to make our dry lab for the computational processes transparent, reproducible, and fair because Jax is on the mission for open science to make their work adhere to those principles," Mays said.

Jax is using Lifebit Cloud OS to access Genotype-Tissue Expression (GTEx), Sequence Read Archive, and Cancer Genome Atlas data to run Nextflow analyses.

During the COVID-19 pandemic, Jax has stepped up its education on Lifebit CloudOS so researchers who are not able to go into their labs can run computational processes remotely.

"We can't move some of that data," Mays said. TCGA and the International Cancer Genome Consortium's datasets are massive and much of the data is not allowed to leave its home countries due to privacy rules such as HIPAA in the US and the General Data Protection Regulation in the European Union.

"Having a federated platform to allow us to write one workflow that can work on multiple clouds is very important because we don't always have a choice where the data are," Mays said.

Jax also is using Jupyter notebooks to make reproducible figures to drive more citations for published works.

Jax is working with Lifebit to integrate Cloud OS with its other information systems, but Mays said that the initial focus has been to access resources from the cloud.

"There is an internal effort for making data also more integrated," she said. "Plans are to integrate both these efforts, but it wasn't necessary for the work that we're doing right now."

Chatzou Dunford has lofty expectations for her company. "When [people] think cloud-based bioinformatic analysis, we want them to be thinking Lifebit. When they think AI and bioinformatics, everything bioinformatics, everything that has to do with genomic analysis, we want them to automatically be thinking Lifebit," she said.

Chatzou Dunford said that the company has five key values: impact, growth, fun, and what she labeled "extreme ownership" and "extreme delivery."

In the short and medium term, Lifebit is concentrating on "extreme delivery," which is Chatzou Dunford's term for a high level of customer service, though she said that the definition is a work in progress. For now, that means advancing the technology and increasing support services by listening to customer needs.

"How can we work closer with our clients to help them have more impact, to help them grow faster, to help them achieve everything they want to be achieving?" Chatzou Dunford said.

"Transformation is hard work," Mays said. "There are no shortcuts, but the tools help make it easier and standards make it easier."