Unlearn.AI

Unlearn builds digital twins of clinical trial participants and uses them to make clinical trials smaller, faster and cheaper. A digital twin is an AI generated forecast of one participant's clinical outcomes, and the company applies these forecasts at several points in a study. Before a protocol is finalized, sponsors can model the patients they expect to enroll and test eligibility rules, endpoints and sample size. While a study is running, pre specified digital twin analyses sharpen interim decisions such as stopping for efficacy or futility, and design scenarios can be re run when evidence changes. After readout, digital twins serve as a comparator that extracts more information from data already collected, in both randomized and single arm studies, and the results inform the next study design. The company also offers AI regulatory strategy expertise. The vendor's own examples report a 20 percent sample size reduction and about 2 million dollars in total cost savings for a Phase 1 and 2 study at the design stage. They also report a 33 percent smaller control arm and more than four months of enrollment time saved in completed Phase 3 trials from a large sponsor that were re analyzed with digital twins. It cites work with AbbVie among others. The customers are pharmaceutical and biotech sponsors. Pricing is not published, and the site asks visitors to talk to the company about where their study stands.