Applying Machine Learning to Increase Clinical Trial Efficiency: A Regulatory Journey

In March 2022, Unlearn reached a historic milestone with the European Medicines Agency (EMA) releasing a draft qualification opinion on their 3-step PROCOVA™ procedure for Phase 2 and 3 trials. In light of this achievement, Charles Fisher, founder and CEO of Unlearn, reflects on the origin and evolution of ideas that shaped Unlearn’s groundbreaking TwinRCT™ solution—delivering on the promises methods like synthetic control arms had failed to keep of making clinical trials smaller, faster, and suitable for supporting regulatory decisions. Hear from Charles about the many twists and turns along the way as his team iterated on using digital twins in clinical trials and the journey towards their recent draft qualification opinion—proving success is never a straight line.


  • Recounting the origin and evolution of ideas that shaped Unlearn’s technology from its founding through today
  • Discussing some of the early experiments that led to the development of the TwinRCT™ solution and PROCOVA™
  • Reviewing Unlearn’s recent draft qualification opinion from the EMA


  • Academia, biotech, and pharma 
  • Biostatisticians 
  • Chief Medical Officers/Medical Directors 
  • Chief Innovation Officers/Head of Innovation 
  • Clinical Operations
  • Regulatory Affairs
  • Data Science

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Why can’t we agree on how to define digital twins in healthcare?

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Summary of the EMA September 2022 Qualification Opinion for PROCOVA™


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The European Medicines Agency has qualified Unlearn’s AI-powered method for running smaller, faster clinical trials.
Digital twins seem to be everywhere in healthcare now, but no one agrees on a single definition for them.