Deep Genomics, an AI-driven predictive genomics company, closed a $180 million Series C financing round.
SoftBank Vision Fund 2 led the financing with participation from new investors, Canadian Pension Plan Investment Board (CPP Investments), Fidelity Management & Research Company, Alexandria Venture Investments, and existing investors Amplitude Ventures, Khosla Ventures, Magnetic Ventures, and True Ventures.
In connection with the financing, Elena Viboch, Investment Director at SoftBank Investment Advisers, will join Deep Genomics’ Board of Directors.
“This financing further validates the significant advances in our AI discovery platform and growth of our proprietary preclinical pipeline,” said Brendan Frey, Founder & CEO of Deep Genomics. “It is rewarding to work with investors who recognize the long-term potential of our AI platform as we continue to identify novel targets and develop transformative medicines for patients.”
Deep Genomics uses artificial intelligence and machine learning to program and prioritize transformational RNA therapies for almost any gene in any genetic condition, the company said.
According to Deep Genomics, its platform, called the AI Workbench, enables Deep Genomics to decode vast amounts of data on RNA biology, identify novel targets for genetically defined diseases, and produce therapeutic programs with a high success rate.
“RNA therapeutics are a digital sequence of nucleotides, which means medicines have become digital information. Our AI Workbench enables us to precisely program RNA therapeutics, much like computer code, to perform a wide range of functions,” said Frey. “This AI Workbench, paired with terabytes of proprietary data, enables us to tackle the enormous complexity of RNA biology and identify novel targets, mechanisms, and RNA therapeutics, which cannot be found without AI. We believe this will have a tremendous positive impact on patients’ lives.”
Healthcare Data Analytics companies raised $1.5 billion in the first half of 2021. Truveta, a digital health startup building a platform that researchers can use to analyze de-identified and normalized health data contributed by the member organizations, closed a $95 million Series A funding round.
