Whats new in the world of medical AI grants

This month, we dive into some of the most recent grants in medical AI, including projects on developing voice-activated AI for people who stutter, designing nonaddictive painkillers to combat the opioid epidemic, and predicting the effects of sleep apnea.

Increasing the accessibility of voice-activated AI for people who stutter

The US National Science Foundation is awarding funds to support research initiatives aimed at tackling obstacles encountered by individuals with disabilities. This includes efforts to create assistive and rehabilitative technologies that can improve their well-being and increase their chances of securing meaningful employment. The National Science Foundation has selected a total of six research groups to progress from Phase 1 to Phase 2 of their Convergence Accelerator’s Track H, which focuses on enhancing opportunities for individuals with disabilities . One of these is the HeardAI project. Over 80 million people worldwide stutter. Stuttering varies between individuals, but can cause high levels of discomfort, embarrassment and anxiety. It often impacts a person’s quality of life, relationships, job performance and opportunities. With the increasing use of voice-activated technology within daily life, individuals with speech difficulties are continuously excluded. With this additional funding, the HeardAI team can work on developing an app that makes voice-activated AI accessible for people who stutter, promoting inclusivity in an progressively digital world . Funding amount: US $5 million Funded project/device: HeardAI Funder: National Science Foundation’s Convergence Accelerator program Research organization(s): Michigan State University (MI, USA), Western Michigan University (MI, USA) and the nonprofit Friends: The National Association of Young People Who Stutter (CO, USA)

Predicting adverse effects of obstructive sleep apnea

Sleep apnea is a potentially serious sleep disorder that causes your breathing to stop and start while you sleep. Worldwide, almost 1 billion adults are estimated to have mild to severe sleep apnea. Untreated sleep apnea can be particularly dangerous as it can increase your risk of strokes, heart attacks and diabetes, and even reduce lifespan. The current method of diagnosing obstructive sleep apnea relies on the apnea hypopnea index, which gauges the frequency of breathing interruptions (apneas) and reduced airflow periods (hypopneas) during sleep . However, this method has limitations and is not accurate in predicting the consequences of these respiratory events. To address this knowledge gap, researchers at Mount Sinai (NY, USA) developed an AI model that analyzes the compromised sleep functions typically affected by apnea—such as breathing patterns, oxygen saturation, and sleep stages—and integrates them into a probability score that predicts the likelihood of short- and long-term outcomes of the disorder. Preliminary data from almost 11,000 participants suggests that their machine learning model predicts the probability of short-term and long-term conditions including sleepiness and cardiovascular mortality with an accuracy ranging between 54% and 87%. After receiving their funding from the National Heart, Lung and Blood Institute, the researchers will validate their findings and hope to advance sleep apnea treatment and management . Funding amount: US $4.1 million Funded project/device: AI-driven sleep apnea outcome prediction model Funder: National Heart, Lung and Blood Institute at the National Institutes of Health Research organization(s): Mount Sinai

Developing nonaddictive painkillers to combat the opioid epidemic

Painkillers like oxycodone, though commonly used in medicine, are highly addictive. However, it is difficult to create nonaddictive alternatives without understanding how these drugs interact with body proteins . Ben Brown, a research assistant professor of Chemistry at Vanderbilt University (TN, USA) has just been granted a $1.5 million Avenir Award in Chemistry and Pharmacology of Substance Use Disorders by the National Institute on Drug Abuse to analyze billions of potential opioid drugs with AI. His focus will be on Mu-opioid receptors, crucial for pain modulation but also addictive. Alongside other researchers, Brown will use AI to analyze drug-protein interactions, considering dynamic protein movements, with the goal of designing and synthesizing drugs with fewer addictive side effects . Funding amount: US $2.275 million Funded project/device: Nonaddictive drug research and synthesis Funder: National Institute on Drug Abuse Research organization(s): Vanderbilt University

UAE launches Falcon Foundation to fund generative AI model progress

This grant news is more about launching a funding foundation rather than specific funded project, but is no less exciting. The Technology of Innovation Institute (TII) in the UAE has launched the Falcon Foundation, a non-profit aimed at advancing open-source generative AI models. Unveiled at the World Governments Summit 2024, the initiative seeks to foster collaboration and transparency in AI governance. TII has committed $300 million to fund the Foundation's projects. Headquartered in Abu Dhabi, TII, under the Advanced Technology Research Council, drives tech research in the emirate . The Falcon Foundation is anticipated to establish the UAE as a significant player in AI technology, at the forefront of generative AI adoption. Funding amount: US $300 million (initial funding) Funded project/device: The Falcon Foundation Funder: Technology of Innovation Institute in the United Arab Emirates Research organization(s): TBC Be sure to get in touch if you have any queries about Future Medicine AI or are interested in publishing in the journal, please contact Commissioning Editor, Emma Hall (e.hall@fmai-hub.com). Disclaimers:The opinions expressed in this feature are those of the author and do not necessarily reflect the views of Future Medicine AI Hub.