Artificial intelligence has already proven to be a major boon in speeding up the drug discovery and development processes, creating advanced diagnostic tools and uncovering new insights into the human genome, to name just a few of the technology’s applications.
Those advancements can quickly hit roadblocks, however, in the form of disorganized databases that AI algorithms aren’t able to easily sift through.
To break down those obstacles, the National Institutes of Health (NIH) has launched a new initiative to build a set of analytics tools and best practices that’ll help researchers get their data ready for AI-powered analysis. The Bridge to Artificial Intelligence, or Bridge2AI, program is specifically aimed at making the technology more applicable to biomedical and behavioral research projects.
“Generating high-quality, ethically sourced data sets is crucial for enabling the use of next-generation AI technologies that transform how we do research,” said Lawrence Tabak, Ph.D., acting director of the NIH. “The solutions to long-standing challenges in human health are at our fingertips, and now is the time to connect researchers and AI technologies to tackle our most difficult research questions and ultimately help improve human health.”
The NIH plans to invest a total of $130 million in the program over the course of four years, depending on the availability of the agency’s funds.
Beyond developing standards that’ll guide other scientists through the process of building AI-ready databases—with a strong focus on avoiding perpetuating the inequities and ethical problems inherent in many previous medical data sets—the funding will also help Bridge2AI researchers begin churning out those AI-ready data.
The resulting compendiums will span multiple data types—such as voice recordings, genomic analyses and more—that future researchers could analyze with AI tools for a wide range of uses: for example, to pinpoint changes in the body, draw connections between genetic abnormalities and certain health conditions and study the biological processes at play while the body recovers from illness, according to the NIH.
The agency has already begun doling out the funding. About $7.7 million was split between the University of California (UC), Los Angeles, UC San Diego and the University of Colorado Denver to begin establishing a network of research centers dedicated to the Bridge2AI program.
Another $22.4 million went to the program’s first four data generation projects. They’re aiming to build ethically sourced data sets that, when AI tools are applied, will be able to predict health outcomes, find biomarkers in voice recordings and derive genomic insights from cell maps while also outlining new guidelines for compiling similarly ethical databases.