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1910 Genetics Start-Up Raises $22M to Use AI to Accelerate Drug Discovery


Backed by M12 – Microsoft’s Venture Fund and Playground Global, 1910 Genetics will scale its AI and biological automation platforms, build its world-class team, expand partnerships with biopharma companies and advance its pipeline of therapeutic programs

1910 Genetics, a biotechnology company integrating artificial intelligence (AI), computation and biological automation to improve drug development, launched on March 23, 2021 after closing its $22M Series A funding round. The company’s core mission is to decrease the timeline and cost of drug development, while improving the success rate of getting medicines to patients. 1910 Genetics has two drug discovery engines that enable the design of both small molecule and protein therapeutics, an unmatched capability in the AI drug discovery space. The Series A financing is co-led by M12 – Microsoft’s Venture Fund and Playground Global.

This new round of financing follows 1910 Genetics’ previously unannounced $4.1M Seed round, which was led by Sam Altman, CEO of OpenAI and former President of Y Combinator, with participation from FoundersX Ventures, Y Combinator, Scientia Ventures, Emles Advisors, Tuck Lye Koh of Shunwei Capital, and other notable investors.

1910 Genetics’ end-to-end technology powers the early drug discovery process, from novel hit discovery to hit to lead and lead optimization. With a powerful combination of biology expertise, a focus on targets with real disease validation and a fully integrated process that includes in-house automated wet labs, 1910 Genetics is solving the time, cost and productivity challenges impeding the current pharmaceutical R&D model. The breadth of 1910 Genetics’ integrated AI and biological automation platforms empowers the company to be therapeutic area-agnostic with applications in a wide range of diseases with significant unmet medical needs.

“Typically, drugs have been discovered via a sequential trial-and-error process, rather than being designed by a repeatable framework that learns from data, pursues multiple paths simultaneously and, ultimately, increases the number of drugs that achieve FDA approval,” said Dr. Jen Nwankwo, Founder and Chief Executive Officer of 1910 Genetics. “I wanted to create a biopharmaceutical company that was built from the ground up with AI, computation and biological automation rather than adding technology as a cherry on top of an archaic process. As a biologist by training, I believe that computational technologies are only impactful in drug discovery when driven by biology. This is our North Star at 1910 Genetics.”

In keeping with its mission, 1910 Genetics’ name pays homage to the year in which Sickle Cell Disease (SCD) was first discovered in the U.S. by James B. Herrick. For each drug design campaign, the 1910 Genetics team begins by understanding the molecular basis of the disease to the granularity at which the world understands SCD. This understanding drives the company’s drug discovery engines, ELVIS™ for small molecules and ROSALYND™ for proteins, to rapidly design therapeutics by integrating AI, big data, cloud computing, computational chemistry, quantum simulation and biological automation.

Having proven its technology against difficult targets in neuroscience, 1910 Genetics identified the COVID-19 pandemic as another opportunity to demonstrate the full capability of its drug discovery engine to accelerate small molecule drug design. 1910 Genetics successfully deployed two of its platforms to design small molecule candidates that block SARS-CoV-2 entry into host cells.  SUEDE™ screened a virtual library of one billion small molecules in a few hours and identified promising hit candidates, while BAGEL™ generated de novo small molecule drug candidates. After rapidly manufacturing both sets of molecules, 1910 Genetics tested them in-house using its automated wet lab platform, which validated the potency of two novel candidates in blocking…



Read More: 1910 Genetics Start-Up Raises $22M to Use AI to Accelerate Drug Discovery

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