Unlearn

Optimize Clinical Trials with AI-powered Digital Twins is a concept pioneered by Unlearn, a San Francisco-based company. Unlearn leverages artificial intelligence to create digital twins, which are AI-generated models of patients used to forecast health outcomes in clinical trials. By integrating these digital twins into clinical research, Unlearn aims to reduce trial timelines, lower costs, and improve the accuracy of outcomes. Their approach, termed TwinRCTs, utilizes digital twins to enhance the power of clinical trials by requiring fewer participants while still maintaining robust data integrity and validity. The digital twin technology developed by Unlearn is already being employed in various therapeutic areas, including neuroscience and immunology. This innovative approach helps to generate predictive models that can simulate patient responses under different treatment scenarios, ultimately accelerating the development of new therapies. The company's AI-driven solutions are regulatory-qualified, supporting their integration into clinical trials conducted by leading global pharmaceutical companies, which helps bring life-saving treatments to market more swiftly.

Key Features

• Shorten Time to Enrollment: Accelerate late-stage study enrollment with fewer required participants.

• Confident Early-Stage Decisions: Increase the observational power in early-stage trials without adding more patients.

• Enhanced Participant Attraction: Improve participant engagement by offering a higher chance of receiving experimental treatment.

• Generative AI Modeling: Utilize advanced AI models trained on extensive patient-level data for accurate health forecasts.

• Regulatory Adherence: Ensure trials meet FDA and EMA standards, enhancing credibility and compliance.

FAQ

What is a patient's digital twin?

A patient's digital twin is a virtual representation that forecasts their future health outcomes based on extensive data from previous clinical studies.

How do digital twins improve clinical trials?

Digital twins improve clinical trials by allowing more power to be concentrated within smaller participant groups, leading to faster enrollment and more efficient trials.

How is a participant's digital twin created?

Digital twins are created by collecting a participant's baseline data and running it through our AI model, which has been trained on historical patient data.

Do digital twins comply with regulatory standards?

Conducting clinical trials using digital twins aligns with guidances from regulatory bodies like the US FDA and European Medicines Agency, ensuring the trials are credible and compliant.

How can I find out more about using digital twins in medicine?

You can learn more about applying AI in medicine and for your specific needs by contacting our team and reading our published materials on the applications of digital twins in drug discovery and development.