European Medicines Agency Qualifies Unlearn’s AI-powered Method for Running Smaller, Faster Clinical Trials
PROCOVA procedure outlines a clear regulatory-qualified framework for implementing AI-generated prognostic digital twins in clinical trials
Unlearn, the only artificial intelligence (AI) company developing prognostic digital twins to run smaller, faster clinical trials, announced that the European Medicines Agency (EMA) has released its final favorable qualification opinion providing a regulatory framework for the application of the company’s TwinRCT solution in Phase 2 and 3 clinical trials. The three-step PROCOVA procedure (patent-pending) is the foundation for TwinRCTs and describes how to use patient-specific prognostic scores derived from digital twins to reduce clinical trial sizes while controlling Type-1 error rates. This qualification opinion represents the first time a regulatory body has formally supported a machine learning-based method for reducing sample size in pivotal trials.
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“the proposed procedures could enable increases in power and/or decreases in sample size in phase 2 and 3 clinical trials with continuous outcomes.”
Unlearn was founded to pioneer AI to eliminate trial and error in medicine. Today, their TwinRCT solution reduces control arm sizes by up to 35%, giving more trial patients the opportunity to receive the experimental treatment. TwinRCTs significantly shorten timelines, helping to speed new lifesaving therapies to patients.
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“Since our founding, our team has focused on reshaping the future of medicine with digital twin technology. The EMA’s adoption of our novel PROCOVA procedure using digital twins is a historic milestone on the path toward achieving that ultimate goal,” said Charles Fisher, Ph.D., founder and CEO of Unlearn. “PROCOVA is a key part of our mission to innovate in regulatory-acceptable ways. With Unlearn’s guidance, our partners now have a framework that enables them to confidently implement TwinRCTs in alignment with the EMA’s rigorous standards.”
In their final opinion, the EMA stated that the Committee for Medicinal Products for Human Use (CHMP) “qualifies PROCOVA” and that “the proposed procedures could enable increases in power and/or decreases in sample size in phase 2 and 3 clinical trials with continuous outcomes.” The EMA’s validation of Unlearn’s cutting-edge technology signifies broader regulatory acceptance of AI in clinical development. Unlearn will continue to work with regulators while advancing machine learning to chart more efficient and patient-centric clinical pathways in the future.
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