The Health-Tech Podcast #111: The Story of Unlearn.ai with Charles Fisher

Charles is a scientist with interests at the intersection of physics, machine learning, and computational biology and is the founder of Unlearn.ai . Previously, Charles worked as a machine learning engineer at Leap Motion and a computational biologist at Pfizer. He was a Philippe Meyer Fellow in theoretical physics at École Normale Supérieure in Paris, France, and a postdoctoral scientist in biophysics at Boston University. Charles holds a Ph.D. in biophysics from Harvard University and a B.S. in biophysics from the University of Michigan.


Unlearn creates Digital Twins to populate Intelligent Control Arms in clinical studies. While others leverage existing data, Unlearn generates a new type of data, for any type of patient. A Digital Twin is a longitudinal, computationally generated clinical record that describes what would have happened if a specific patient received a placebo.

https://www.linkedin.com/in/drckf/ | www.unlearn.ai

Get in touch:

www.jamessomauroo.com | www.somx.co.uk

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White Papers

Using AI-based Prognostic Models to Design Efficient, Unbiased Clinical Trials

Webinars

Part 3: Innovation in Clinical Research: AI-based Drug Development Tools and the Regulatory Landscape‍

Webinars

Part 2: Faster, More Efficient Trials: Novel Trial Designs using Digital Twins‍

Watch an overview of specific use cases for Digital Twins and learn how novel trial designs with Digital Twins enable smaller trials that maintain their power.
Watch a panel discussion on the regulatory landscape where experts share perspectives on the future of AI-based drug development tools like Digital Twins.
Statistical principles of clinical trials with Digital Twins