Data is unlocking opportunities across various industries, and now armed with $80 million in Series B funding, TetraScience aims to be the one to unlock experimental data for scientific and drug discovery.
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The Boston-based company is developing what it touts as the “world’s only cloud-native and open R&D data cloud for scientific discovery,” said Patrick Grady, chairman and CEO of TetraScience.
Insight Partners and Alkeon Capital co-led the investment, which gives TetraScience a total of $92.5 million in funding since 2019, Grady told Crunchbase News.
Although the company was founded in 2014, today’s TetraScience is a different one than originally started by Alok Tayi, Salvatore Savo and Siping Wang. Grady met the founders in 2017 during what he called “Tetra 1.0.” The company was developing a way to digitize scientific laboratories, an environment that in some cases still uses pen and paper, he said.
“The initial product focus was on the Internet of Things, which was a hot place to be at the time, as VCs feared missing out,” Grady added. “Hardware is hard, and in some ways, they were ahead of their time, but I thought they should listen to the customers who said that they could not get access to the data needed to run experiments.”
Two years later, Grady got a call from Wang who told him that the company was now focused on the R&D data cloud, but needed assistance getting it off the ground.
Today, TetraScience is taking on the $300 billion experimental data cloud market with a resource that provides life sciences companies with the flexibility, scalability and data-centric capabilities to enable easy access to scientific data they can use across enterprise pharma and biotech organizations to accelerate health breakthroughs.
Nikhil Sachdev, managing director at Insight Partners, said in an interview that these capabilities are why Insight was attracted to TetraScience. The firm typically invests in software, fintech and enterprise companies and saw in the company “a great innovator and builder of a large defining category,” Sachdev added.
“We believe TetraScience is to Snowflake, what Veeva was to Salesforce1,” he said. “They are creating a plug-and-play system and enabling new data science applications. They have a big vision and experienced 10x revenue growth in the past year, as well as adoption by blue-chip customers.”
The company will use the funds for technology development, go-to-market capabilities and to grow its team both on the Ph.D. side and across its business, Grady said.
TetraScience is already working with approximately 12 large pharmaceutical companies and would like to bring on the other 88 of the top 100 companies before targeting mid-sized pharma companies and the biotechnology sector.
“This is a non-standard Series B for essentially what is a 23-month-old company,” Grady added. “When we closed on the $80 million, we still had $9 million of our Series A on the balance sheet, so we are showing good capital efficiency. The next part of our data engineering is to get ready for artificial intelligence and machine learning.”
Inset photo courtesy of TetraScience.
Illustration: iStock
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