Press

PROCOVA procedure outlines a clear regulatory-qualified framework for implementing AI-generated prognostic digital twins in clinical trials

The potential for AI implementation in healthcare can barely be measured, as it can already do what humans do, just countless times better and more efficiently.

Led by Insight Partners, financing builds on the company’s momentum in working with leading biopharmaceutical companies to improve clinical trial efficiency.

Collaborators will leverage AI-generated Digital Twins to enable smaller, more efficient pivotal clinical trials.

The AI 100 is CB Insights' annual list of the 100 most promising private AI companies in the world.

Ann E. Taylor, M.D., Chief Medical Officer at AstraZeneca, has joined the Unlearn Board of Directors.

The use of digital twins in the healthcare industry is revolutionizing clinical processes.

The Rock Health team reflects on the evolution of digital in clinical trials, discuss the current state, and explore the opportunity to further transform drug discovery.

Eisai has joined the company’s world-class syndicate of investors as part of its Series A extension along with Epic Ventures and Alumni Ventures Group.

The Center for Data Innovation spoke with Charles Fisher, chief executive officer and founder of Unlearn.AI

Researchers, pharmaceutical companies and a handful of tech start-ups are experimenting with a new model: virtual clinical trials.

Unlearn.AI is changing how we treat patients with medicines in trials.

The San Francisco-based company creates digital replicas of participants in clinical drug trials using artificial intelligence.

Unlearn’s unique model has shown that it can provide realistic digital patient records to supplement actual control patients in Alzheimer’s Disease trials

Unlearn.AI Inc. has raised $12 million to pursue a goal of using artificial intelligence to help life sciences companies run better clinical trials...

The Unlearn platform processes historical clinical trial datasets from thousands of patients to build the disease-specific machine-learning models used to create what is called “Digital Twins” and...

Unlearn has built disease-specific models that generate control patient data by using demographic information and observations of the same variables over time, such as common lab tests and...

“Unlearn’s pioneering use of Digital Twins will limit the number of patients that need to go on placebo while also reducing overall trial enrollment time."

“This new financing marks an important milestone in our growth and will contribute to the significant progress we are making with regulators and with our commercial partners, who are already...

Smith and colleagues used 18 months of data on 1,909 patients from the Coalition Against Major Diseases (CAMD) AD database to develop an algorithm for generating digital twins.

Unlearn.AI allows researchers to: Populate control arms in clinical trials, enabling rigorous clinical evidence with fewer subjects.

Machine learning and artificial intelligence (AI) are already being actively used in drug discovery to evaluate potential binding of small-molecule drugs to proteins, but there's potential for the...

Technology creates Digital Twins and Intelligent Control Arms to reduce clinical trial timelines and improve confidence in trial results

Digital twins enable faster recruitment with higher powered, individualized trials [capable of generating] additional data from the same or fewer number of patients.

Clinical trials could be made more efficient by using artificial intelligence to incorporate other data sources, such as historical control arms or real-world data.

Unlearn.AI Inc. is going a step further, using data from historical trials and patient registries to build algorithms that simulate artificial patients.

“Understanding how to predict and manage differences between patients is the primary goal of precision medicine. Computational models of disease progression developed using machine learning...