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2023-06-01XtalPi Announces Collaboration with Lilly, Using AI + Robotics to Uncover First-in-class TherapeuticsCombining mutually informative AI "dry lab" algorithms with large-scale "wet lab" robotics to empower pharmaceutical innovationRead More
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2023-01-11XtalPi Names New COO for U.S. Operations, Bringing Its Autonomous Labs to Boston in Continued Global ExpansionShenzhen, CHINA – January 11th , 2023 – XtalPi, Inc., a pioneering pharmaceutical technology company powered by artificial intelligence (AI) and automation, announced that Dr. Sarah Trice has joined...Read More
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2022-10-27XtalPi Announces Research Collaboration with JanssenXtalPi, Inc. announced a research collaboration with Janssen Pharmaceutica NV to deliver chemical matter with validated binding affinities and desirable property profiles.Read More
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2022-03-07Fierce Medtech names XtalPi as one of its “Fierce 15” Med Tech Companies of 2021Cambridge, MA and Shenzhen, China – March 7, 2022 – XtalPi, a pioneering artificial intelligence (AI) drug research and development (R&D) company today announced that it has been named by Fierce Medtech as one of 2021's Fierce 15 med tech companies, designating it as one of the most promising private med tech companies in the industry.Read More
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2021-10-27XtalPi and Signet Expand AI Drug Discovery Collaboration to Novel Cancer TargetSHENZHEN, China & BOSTON - Signet Therapeutics and XtalPi Inc., a physics-based, AI-powered drug R&D company, announced the expansion of their AI drug discovery collaboration to include a new first-in-class program against a novel cancer target identified by Signet.Read More
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2021-09-28Research Collaboration between XtalPi Inc and Acerand Therapeutics to develop potential novel anti-cancer therapies using High-precision Physics-based model and Machine LearningXtalPi, a leading AI drug discovery company, announces a research collaboration with Acerand Therapeutics, a biotechnology company specialized in developing best-in-class and or first-in-class drugs. The partnership will leverage XtalPi's highly accurate physics-based models and machine learning models to develop potential novel chemical entities for a cancer target.Read More