As drug developers and regulators alike increasingly warm to creative ideas for running clinical trials, a machine learning platform created by three physicists is drawing in $50 million from tech VCs. Unlearn bills itself as the only company that can generate "digital twins" of patients for use in clinical trials, so that biopharma companies can test their drugs with fewer real patients than they would need to in traditional trials, but get similarly, if not even more, reliable results. "Our product is not an AI model -- it's a clinical trial," CEO Charles Fisher wrote in an email interview with TechCrunch. He divulged that Germany's Merck KGaA is among three drugmakers using Unlearn's platform in the design of its clinical trials -- although it's not directly for the digital twin service but prognostic information from the digital twins. Whereas there have been efforts and guidance from the FDA to use real-world data to support regulatory decisions, none have quite gone as far as incorporating constructed patient profiles. Unlearn believes its technology can accomplish that through a combination of machine learning and new statistical methods.