By Shania Kennedy
Researchers from the McWilliams School of Biomedical Informatics at UTHealth Houston were awarded over US$31 million for 16 projects aimed at driving innovations in healthcare artificial intelligence (AI).
The grants include 14 new awards and two supplemental awards. Five of these grants, totaling more than US$19 million, were awarded by the National Institute on Aging (NIA), part of the National Institutes of Health (NIH).
The first project is focused on identifying the treatment efficacy of Alzheimer’s disease therapy. Researchers involved in the investigation noted that there are significant knowledge gaps around why some patients do not respond to these treatments.
The project aims to help close these gaps by developing machine learning models to identify subgroups of patients that respond differently to treatment.
The second project is set to build the “Alzheimer’s Disease Clinical Trial Simulation” framework, which will serve as an accessible, reusable, and standardized platform for Alzheimer’s disease trial design and simulation.
“The pressing need to address the challenges in Alzheimer’s disease and related dementias research inspired our exploration of this topic,” explained principal investigator on the project Cui Tao, PhD, and Professor in the Department of Health Data Science and Artificial Intelligence Dr. Doris L. Ross. “The increasing prevalence of these illnesses and the limitations of traditional randomized clinical trials motivated us to seek innovative solutions, and we recognized that the integration of real-world data and clinical trial simulation could offer a transformative approach to advance our understanding and, potentially, lead to finding more effective treatments.”
The third project, receiving the largest of the awards at US$6.4 million, aims to create an actionable, integrated genetic catalog of Alzheimer’s known as AIM-AI. The “genetic map” will enable genetic insights to be integrated with additional modalities for use in drug discovery and etiological research.
The fourth project will build a robust informatics framework that incorporates computational phenotyping and ontology data to “harmonize electronic health records,” the press release indicates.
The final NIA award will supplement an existing project working to benchmark AI algorithms with standardized neuroimaging data.
The NIH’s National Library of Medicine (NLM) awarded three new grants and transferred another to the school.
One of the funded projects is focused on developing enhanced training methods for clinical foundation models, which could help improve clinical prediction models and some deep learning applications.
The second project aims to integrate genomic data sharing with institutional review boards to make ethical review for clinical trials easier.
The third project will supplement ongoing work to develop deep learning approaches that can transform genomic data into vocabulary and image-like objects for use in genetic research.
The transferred grant, worth US$1.9 million, will support a project aimed at advancing applications of EHR data for clinical research through improved cohort discovery and identification.
The NIH’s National Human Genome Research Institute also issued two awards to the school’s faculty.
The first is a renewal grant to continue work on “RaPID,” a computational method for exploring genetic relationships and inferring identity-by-descent segments among individuals.
The other project is focused on improving rare disease awareness among healthcare providers through an informatics framework designed to accelerate the diagnosis of these conditions.
Five additional NIH grants were also awarded.
The first two are part of the NIH’s Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) Programme.
One of these projects will leverage AI and machine learning to investigate the role of donor-recipient blood type mismatches in heart transplantations and design interventions to reduce health disparities.
The other project will allow UTHealth Houston researchers to collaborate with experts from Tuskegee University on work to improve data governance, facilitate the adoption of health AI, and promote health equity for minoritized populations.
The third additional NIH grant supports a project focused on personalized immunotherapy for the lymphatic system and driving cancer treatment research.
The fourth project will develop an online, asynchronous informatics course that is open to the larger biomedical community.
The final award, a National Science Foundation “Infrastructure Innovation for Biological Research” grant, will be utilized to develop machine learning tools to advance research into cell development.
“This is an incredible achievement for McWilliams School of Biomedical Informatics; these grants play a key role in advancing informatics research while also expanding on the important role technology continues to play in medicine,” said dean and Glassell Family Foundation Distinguished Chair in Informatics Excellence at McWilliams School of Biomedical Informatics, Jiajie Zhang, PhD, in the press release.
“All of the newly awarded grants center around medical AI. Our world is at the start of the ‘Cognitive Revolution,’ which is driven by AI. There is no better time for these types of critically important research studies and developments,” he continued.
