It takes more than a decade to bring a new medicine to patients who need it. Much of that time is spent recruiting patients to assess the medicine’s safety and efficacy in a series of clinical trials.
In a typical clinical trial, up to 50% of subjects receive a placebo and/or current standard of care. An Intelligent Control Arm incorporates AI-generated digital subject data into a clinical trial to reduce the number of subjects who receive placebo.
Intelligent Control Arms populated with these Digital Twins:
In the end, it’s about increasing confidence in trial results. It’s about getting new medicines to patients who need them as quickly as possible. It’s about time.
A comprehensive, longitudinal, and computationally generated clinical record that describes what would have happened if a specific subject had received a placebo. Unlearn uses its proprietary DiGenesis™ process to create Digital Twins that are statistically indistinguishable from actual subject data.
Determine the inclusion criteria, endpoints, and study sizes with the highest chances of success.
Add an Intelligent Control Arm to model the standard of care in an open-label clinical trial.
Reduce the number of subjects in a concurrent control arm by incorporating Digital Twins to model the standard of care.
Analyze trial results to identify subgroups that received more benefit from a treatment.
Our models are trained on curated longitudinal patient datasets originating from historical control arms, patient registries, and/or real world datasets.
We use patent-pending algorithms related to Conditional Restricted Boltzmann Machines to simulate comprehensive, longitudinal digital subject records.
Paired analyses increase statistical power in clinical trials without compromising study integrity.