Unlearn, a startup creating digital twins used in the control arm of clinical trials, announced today an extension to its Series A funding round, bringing the total amount raised to $15 million.
New investors Eisai, Epic Ventures and Alumni Ventures Group contributed to the oversubscribed round. They join 8VC, DCVC, DCVC Bio and Mubadala Capital Ventures, which contributed to Unlearn’s original Series A funding round in April, worth $12 million.
WHAT IT DOES
Unlearn uses its machine learning model, called Digenesis, to construct digital twins for participants in clinical trials. A digital twin is a virtual replica of a person that can, in the case of Unlearn, be used to describe what would happen if the participant had been given the placebo in the trial.
With the creation of digital twins in studies, Unlearn generates an intelligent control arm that can reduce the sample size and decrease the number of participants given the placebo.
Its flagship product is the use of digital twins in Alzheimer’s disease research. The model can create digital twins that are statistically indistinguishable from their real-life patient twin.
Unlearn has conducted research on its Alzheimer’s digital twins and found that its model could supplement real subject data in control arms and predict disease progression.
“Our AD Digital Twins product has demonstrated its capacity to increase trial power and, more recently, rescue trials in jeopardy of failure from high dropout rates due to COVID-19 – while managing regulatory risk and limiting timeline delays,” said Dr. Charles Fisher, the founder and CEO of Unlearn, in a statement.
WHAT IT’S FOR
The company did not disclose what the funding would be used for. However, it is currently working with biopharmaceutical and medical device companies along with regulators to refine its product.
The pandemic has made it more challenging to conduct clinical trials in person, so many organizations have turned to digital trials instead.
Digital clinical trials pose a number of opportunities and challenges, according to a paper published in Nature. For one, they allow for remote data collection using wearables that many people already own and use. This could allow for broader participant recruitment, because people can enroll regardless of where they live. A challenge, however, is that many of the tools that would be used to collect real-world data are consumer-grade and would need to be updated to medical-grade.
Companies that have deployed digital features to their research processes include Labcorp, which recently added a technology platform to help streamline the clinical trial and drug development process, and Castor, which uses its electronic-data-capturing tool to gather information from clinicians, patients, devices, wearables and electronic health records to build a study.
ON THE RECORD
“Unlearn has proven how generative AI-models trained on clinical data can be successfully utilized to create Digital Twins of patients for complex populations such as Alzheimer’s Disease,” said Dr. Shun Asami, a senior director at Eisai Innovation, in a statement.
“We believe that the Unlearn technology and its Intelligent Control Arms have the potential to solve the enrollment challenges, timeline delays, and high failure rates that too often burden clinical trials.”