Alphabet’s Verily teams up with Microsoft to power multi-cloud biomedical research

Verily, Alphabet’s research subsidiary focused on life sciences, has announced a strategic partnership with Microsoft and Broad Institute of MIT and Harvard to adopt a new multi-cloud approach to biomedical research.

The news comes less than a month after Verily raised a fresh $700 million in funding from parent Alphabet, Silver Lake, and Temasek. The round is a notable milestone for Verily, which is positioning itself as a more “open” business that isn’t tethered to sibling Google’s infrastructure. Alphabet CEO Sundar Pichai recently said that the company would take a more “disciplined” approach to its “other bets” businesses, using Verily as an example of how it has had to cede some control to ensure success down the road. This has included selling stakes to external investors and giving the unit its own board of directors. Embracing rival cloud services fits into those plans, giving its longer-term bets a greater aura of independence.

“Verily feels strongly that the open data ecosystem should be multi-cloud,” a spokesperson told VentureBeat.

Alphabet spun out its Google Life Sciences division as an independent unit back in 2015, rebranding it as Verily shortly afterward. In the years since, Verily has embarked on a number of health-focused projects, including a $500 million diabetes joint venture with Sanofi, a concept clinical smartwatch, and a four-year health data tracking program. Verily has also raised around $2.5 billion in funding along the way.

Terra firma

Back in 2019, Verily partnered with Broad Institute, a biomedical and genomic research center in Cambridge, Massachusetts, to launch Terra, a cloud-native platform for data analysis aimed at biomedical research into human disease.

Terra is setting out to foster collaborative biomedical research through an open source platform that connects researchers with each other and to the datasets, tools, and compute power they need to advance their studies. Datasets may include anything from genomics to medical imaging.

With “workspaces,” for example, researchers have a dedicated space to connect, access data, and run analyses with each other.

Above: Terra Workspaces

While the Terra platform itself is free to use, running cloud workflows and accessing/storing data incurs charges. As an Alphabet subsidiary, Terra has so far been restricted to Google’s cloud services, including storage, Compute Engine, and BigQuery, but that is changing with a new “multiyear partnership” that will bring Microsoft’s Azure cloud smarts to the mix. “This means a researcher can look forward to some major functional upgrades to the Terra platform infrastructure,” Verily said.

Ultimately, researchers will have more freedom and flexibility to use cloud infrastructure and tools that aren’t Google’s, including Azure Synapse Analytics, Azure Machine Learning, and Azure Cognitive Services. Moreover, the partnership will open Terra up to Microsoft’s existing network of 168,000 health and life sciences professionals who already use Azure.

“While adding Microsoft Azure support will provide more health experts with the ability to access the Terra platform, this partnership is broader than cloud usage,” Verily said. “This is a multi-year partnership which brings together advanced technologies, industry expertise, and scale to further develop and improve upon Terra to help health experts interpret an unprecedented amount of data and derive intelligent insights for the treatment of human diseases.”

Platforms such as Terra also highlight the role cloud computing can play in encouraging cross-organization collaboration. In this case, that means steering potentially life-changing research away from closed silos and into shared forums free from fragmented policies and approaches to leveraging research data.

“Part of the challenge for data scientists and researchers is getting large enough sample sizes to validate work or uncover new scientific discoveries,” Verily added. “By using a centralized platform for sharing data, researchers can leverage the work of others to build larger datasets, faster — all while trusting that they are using a safe and secure platform that is compliant for both biomedical and health care industries. Also, with a centralized platform instead of several, platforms’ energy consumption can be reduced for improved sustainability.”

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