Unlearn.AI nabs $12M to build “Digital Twins” to speed up and improve clinical trials

Twins have long played a role in the world of medical research, specifically in the area of clinical trials, where they can help measure the effectiveness of a therapy by applying a control to one of a genetically-similar pair. Today, a startup founded by a former principal scientist at Pfizer, which has developed a way of digitising this concept through the use of AI, is announcing some funding to further its efforts. Unlearn.AI, which has built a machine learning platform that builds “digital twin” profiles of patients that become the controls in clinical trials — is announcing that it has raised $12 million in a Series A round.

Enter your email address to download paper.

Click the link to begin download.
Oops! Something went wrong while submitting the form.

Enter your email address to watch the webinar.

Click the link to watch webinar.
Oops! Something went wrong while submitting the form.
Webinars

How will AI transform the future of medicine?

White Papers

Evaluating Digital Twins for Alzheimer’s Disease using Data from a Completed Phase 2 Clinical Trial

White Papers

Prognostic digital twins overcome the limitations of external control arms in RCTs

Both methods reduce control arm sizes, but only digital twins control for bias.
A Phase 2 study on crenezumab in mild-to-moderate AD was used to retrospectively assess the validity of Unlearn's approach for AD clinical trials.
Hear from Charles Fisher, founder and CEO of Unlearn, in this on-demand webinar about how AI will transform the medical landscape of tomorrow.