Using novel digital twins of clinical trial participants, Unlearn is accelerating clinical research to help bring new treatments to patients sooner
Unlearn, an AI company creating digital twins of clinical trial participants that enable smaller, faster studies, announced a $50M Series C round led by Altimeter Capital, joined by returning investors Radical Ventures, Wittington Ventures, Mubadala Capital, Epic Ventures, and Necessary Venture Capital. This round of funding was secured to propel the company’s mission to advance AI to eliminate trial and error in medicine by investing in its people, data, engineering capabilities, and longer-term R&D initiatives.
“Pharmaceutical companies are spending over $100 billion dollars a year on clinical research, yet the industry remains skeptical about new technology that has the power to truly transform research”
Founded in 2017 as an AI research company, Unlearn has always been at the forefront of developing innovative AI-based solutions for clinical trials. Now, seven years later, with over $130M raised, Unlearn’s technology addresses key clinical research challenges, such as long timelines, slow enrollment, and patients’ reluctance to participate over potentially receiving a placebo.
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Unlearn’s AI models generate an individual digital twin for every trial participant before they are randomized into the experimental or control arm. The participant’s digital twin forecasts their health outcomes under placebo, regardless of their actual assignment. Digital twins enable TwinRCTs,TM highly powered clinical trials with smaller control groups, allowing more patients to receive experimental treatment. TwinRCTs reduce the time it takes to bring new therapies to market, ultimately paving the way for improved health outcomes for all.
“Pharmaceutical companies are spending over $100 billion dollars a year on clinical research, yet the industry remains skeptical about new technology that has the power to truly transform research,” said Charles Fisher, Ph.D., founder and CEO of Unlearn. “Breaking down these barriers and proving the value of digital twin technology continues to be a main driver for us at Unlearn. And, this round of financing will allow us to not only grow our team but also expand our capabilities into more therapeutic areas to build awareness and prove the value.”
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Over the last decade, the clinical research industry has seen the introduction of advanced solutions to solve its most pressing problems – lack of diversity, years-long timelines from discovery to development, and increasing costs. However, working within regulatory constraints continues to create obstacles and limit progress. Understanding this, Unlearn has partnered with regulatory experts since its founding and now has a qualification from the European Medicines Agency for use as the primary analysis in phase 2 and 3 clinical trials with continuous outcomes as well as agreement from the U.S. Food and Drug Administration that the methodology does not deviate from current guidance.
“Unlearn is introducing powerful AI models to help make clinical research more streamlined and efficient,” said Pauline Yang, Partner at Altimeter Capital. “We’re excited to be a part of their journey to seek to reduce the number of participants needed for research, ultimately with hopes of reducing costs and improving outcomes for partners in the pharmaceutical industry.”
“Unlearn has built one of the most original and impactful applications of AI in the market today,” said Rob Toews, Partner at Radical Ventures. “The company’s platform is transforming clinical trials, using cutting-edge AI to help bring life-changing therapeutics to patients sooner.”
With this round of financing, Altimeter joins existing investors included in the round – Radical Ventures, Wittington Ventures, Mubadala Capital, Epic Ventures, Necessary Venture Capital – as well as Insight Partners, 8VC, DCVC, and DCVC Bio.
Unlearn partners with pharma sponsors, biotech companies, and academic institutions to streamline and optimize clinical trials, enabling researchers to assess the safety and efficacy of new treatments more quickly and accurately.
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