of using machine learning and biostatistics to improve clinical trials for the benefit of patients and sponsors.

Unlearn invented their TwinRCT solution to enable biopharma partners to run faster, more successful clinical trials. A TwinRCT is a randomized trial that uses machine learning to achieve a higher probability of success with a smaller number of patients. As in a traditional RCT, patients are randomized to a treatment group and a control group, but, unlike a traditional trial, a prognostic digital twin is created for every patient using a machine learning model trained on historical data. The treatment effects for the primary and secondary outcomes can all be estimated from the trial with greater precision after correcting for a prognostic score derived for each patient's digital twin.

TwinRCTs provide a scientifically-sound method for using deep learning and historical patient data to improve clinical trials.