Startup nference has closed a $60 million Series B financing round to expand the use of its augmented intelligence platform in clinical research and drug development.
Mayo Clinic and NTT Venture Capital joined previous investors Matrix Partners and Matrix Capital Management, which participated in the Cambridge, MA-based company’s Series A round in 2018.
The relationship with Mayo Clinic is not new, however, as the research group in 2017 launched a startup with nference—dubbed Qrativ—to help match drugs with diseases they might be able to treat. Also familiar faces, Matrix Capital Management and Matrix Partners, in addition to Mayo, participated in Qrativ’s Series A financing, which brought in $8.3 million.
Venky Soundararajan, founder and chief scientific officer of nference, says the company addresses the need to make biomedical knowledge computable, as most data are in an unstructured form and “not amenable for machines to compute on.”
Proceeds from the latest financing will go toward expanding the company’s partnerships and workforce, which currently includes around 150 data scientists largely from Harvard Medical School and MIT. By the end of this year, Soundararajan said he expects both the platform and workforce will have grown “significantly.”
Building on the financing round, the company this week also announced a new project with Mayo Clinic. The first venture is part of the health center’s “Mayo Clinic Platform” initiative, which it kicked off last year. The goal is to accelerate drug discovery and development using nference’s augmented intelligence platform.
The organizations will develop a “Clinical Data Analytics Platform” to apply advanced analytics to deidentified data from Mayo Clinic and other sources, such as scientific literature. The company says it will focus on disease target and biomarker identification; matching patients with treatment; and other areas that would benefit from access to real-world data, such as label expansion and post-marketing surveillance.
“We are not the first company to attempt to automate the curation and also the synthesis of unstructured biomedical knowledge, but the scale at which nference is doing so is unprecedented,” Soundararajan tells Xconomy.
“Because biopharma R&D heavily depends on extracting and curating insights from this unstructured ocean of knowledge, there is a need to develop technology,” he adds, “and this is the right time to do so because there is a renaissance in computer science.”
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