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Using an Intelligent Control Arm in a trial enables sponsors to reduce the number of subjects who receive a placebo. As a result, Intelligent Control Arms can cut patient recruitment time by up to 50%.
An Intelligent Control Arm is composed of Digital Twins that are perfectly matched to the actual subjects in a trial. Digital Twins reduce variability arising from differences between subjects at baseline, resulting in increased power to detect treatment effects.
Each subject in a trial with an Intelligent Control Arm is assigned a perfectly matched Digital Twin that describes what would have happened if the subject had received a placebo. By acting as counterfactuals, Digital Twins provide the necessary evidence to understand how each subject in a trial responded to the experimental therapy.
Using synthetic control patients cuts patient recruitment time for a trial in half. This reduces clinical trial cycle time and time-to-market by 30 to 60%.
Synthetic control patients minimize patient recruitment cost and dropout by reducing the total number of patients involved in a clinical trial.
Unlearn’s synthetic control patients eliminate population differences between the control and treatment arms to improve power and increase confidence in trial results.
Unlearn is a science-first company that has created the first machine learning (ML) platform for creating Intelligent Control Arms with Digital Twins. Unlearn is working closely with biopharma companies and regulators to ensure our methods meet the highest scientific and regulatory standards.
See what Professor Collin M. Stultz, MD, PhD has to say about Unlearn.
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