UC San Diego selected to lead components of the NIH Common Fund’s Bridge2AI program

UC San Diego selected to lead components of the NIH Common Fund’s Bridge2AI program

Researchers at College of California San Diego College of Medication have been chosen to steer elements of the Nationwide Institutes of Well being (NIH) Widespread Fund’s Bridge to Synthetic Intelligence (Bridge2AI) program. Over the subsequent 4 years, Bridge2AI will award $130 million to speed up the widespread use of AI in biomedical analysis and well being care.

Physicians and scientists have lengthy acknowledged the potential of AI to assist perceive and deal with illness, however its use in medical and analysis settings stays restricted. That is, partially, as a result of AI instruments can’t all the time be simply or appropriately utilized to new datasets that weren’t organized for one of these evaluation. Moreover, most AI algorithms operate as “black packing containers” -; once they attain a conclusion about one thing, nobody is aware of precisely how or why that call was made.

To deal with these points, Bridge2AI will fund 4 Knowledge Era Tasks to create complete AI-ready datasets that can lay the groundwork for brand new, interpretable and reliable AI applied sciences. The 4 multi-site tasks might be unified by the Bridge Heart, an govt hub that oversees the combination, dissemination and analysis of all Bridge2AI actions.

Trey Ideker, PhD, professor at UC San Diego College of Medication, will function principal investigator for one of many Knowledge Era Tasks. Lucila Ohno-Machado, MD, PhD, professor and affiliate dean for informatics and expertise at UC San Diego College of Medication, will function a principal investigator for the Bridge Heart.

That is the primary time NIH has invested in biomedical AI at this scale, and we’re thrilled to be part of it. UC San Diego has confirmed itself to be a pioneer in medical and analysis AI expertise, however this funding will assist cement our place within the AI revolution.”


Trey Ideker, PhD, Professor, UC San Diego College of Medication

Cell maps for AI

Ideker and collaborators are anticipated to obtain practically $20 million within the subsequent 4 years to launch Cell Maps for AI, a analysis challenge designed to usher in a brand new period of precision drugs. The workforce envisions a future through which an AI algorithm may analyze a affected person’s genome and decipher which illness they’ve, what stage they’re in and which remedies are almost certainly to assist. Importantly, they are saying the algorithm have to be interpretable, such {that a} doctor may level to the molecular and mobile pathways that inform its selections.

“It isn’t sufficient for an algorithm to only take a posh set of mutations and resolve what drug to offer a affected person if we do not know why it is making that selection,” stated Ideker. “We might now have sufficient human genomes sequenced to energy precision drugs, however what we do not have but is a transparent map of mobile biology to interpret the information with.”

To deal with this, the challenge goals to map the construction and performance of a human cell in its entirety, beginning with essentially the most primary cell kind: the stem cell. The researchers will acquire induced pluripotent stem cells from quite a lot of genetic backgrounds and mix microscopy, biochemistry and computational instruments to review their biology at a number of scales. The ultimate product might be a complete mannequin of the cell, from genes and proteins to whole organelles and the way all of them work collectively. As soon as the stem cell has been modeled, they plan to make use of the identical method to mannequin different cells, resembling these which might be dividing, differentiating or in numerous illness states.

Their aim is to finally have a library of cell maps throughout many demographic and illness contexts, which can be utilized to coach AI algorithms to make knowledgeable and interpretable selections about human well being.

“With Bridge2AI, we’re not solely producing unprecedented datasets, but additionally growing a system to do that work in an organized and moral approach, which is able to set the sphere up for future success,” Ideker stated.

Extra principal investigators on the challenge embody Prashant Mali, PhD, on the UC San Diego Jacobs College of Engineering and researchers at UC San Francisco, Stanford College, College of Alabama, College of Alabama at Birmingham, College of Montreal, Simon Fraser College, College of South Florida, College of Texas at Austin, College of Virginia and Yale College.

Bridge Heart

Coordinating all program efforts is the Bridge Heart, consisting of six cores targeted on Administration, Ethics, Teaming, Requirements, Device Optimization and Abilities and Workforce Improvement. UC San Diego is predicted to obtain practically $10 million over 4 years to steer each the Administrative and Ethics Cores.

“Main the Bridge Heart is thrilling in some ways,” stated Ohno-Machado. “Along with supporting this groundbreaking and interdisciplinary analysis, we can even spearhead new fashions of scientific collaboration, make sure the coaching of a extremely numerous group of researchers and in the end construct AI instruments which might be actually relevant to everybody.”

Ohno-Machado will lead the Bridge Heart Administrative Core and co-lead the Ethics Core with Camille Nebeker, EdD, on the Herbert Wertheim College of Public Well being and Human Longevity Science at UC San Diego. Different UC San Diego investigators embody Cinnamon Bloss, PhD, additionally on the Herbert Wertheim College of Public Well being, Tsung-Ting Kuo, PhD, at UC San Diego College of Medication, and Jingbo Shang, PhD, Babak Salimi, PhD, and Berk Ustun, PhD, all at Jacobs College of Engineering and the Halıcıoğlu Knowledge Science Institute. Extra Bridge Heart collaborators embody college on the Broad Institute, Vanderbilt College and College of Texas Well being.

Nebeker, together with UC San Diego College of Medication college Sally Baxter, MD, and Linda Zangwill, PhD, are additionally main modules inside one other Knowledge Era Challenge referred to as AI Prepared and Equitable Atlas for Diabetes Insights (AI-READI), led by principal investigators at College of Washington. The challenge will generate an ethically sourced knowledge repository to develop machine studying fashions with the aim of studying how Sort 2 diabetes is influenced by sufferers’ genes, way of life and environments.

“Producing high-quality ethically sourced datasets is essential for enabling the usage of next-generation AI applied sciences that rework how we do analysis,” stated Lawrence A. Tabak, DDS, PhD, who’s performing the duties of the Director of NIH. “The options to long-standing challenges in human well being are at our fingertips, and now’s the time to attach researchers and AI applied sciences to sort out our most tough analysis questions and in the end assist enhance human well being.”

Supply:

College of California – San Diego

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