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McWilliams School of Biomedical Informatics researchers awarded $31M in grants for medical artificial intelligence innovation research

McWilliams School of Biomedical Informatics researchers awarded $31M in grants for medical artificial intelligence innovation research
( McWilliams School of Biomedical Informatics at UTHealth Houston reached a funding landmark with 15 faculty members awarded 16 different grants totaling more than $31 million between August and October 2023. Each grant has a focus on medical artificial intelligence (AI) innovations and advancements in research or health care.

“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 Jiajie Zhang, PhD, dean and Glassell Family Foundation Distinguished Chair in Informatics Excellence at McWilliams School of Biomedical Informatics. “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.”

The 16 grants include 14 new awards and two supplemental awards for a total amount of $31,285,374. Five of the awards, including two U01 grants and three R01 grants, are from the National Institute on Aging, part of the National Institutes of Health (NIH), and total over $19 million.

National Institute on Aging grants

Yejin Kim, PhD, assistant professor with McWilliams School of Biomedical Informatics, was awarded an NIH grant of nearly $4 million. Xiaoqian Jiang, PhD, the Christopher Sarofim Family Professor in Biomedical Informatics and Bioengineering and chair in the Department of Health Data Science and Artificial Intelligence at the school, is also an investigator on this project aimed at identifying treatment efficacy of Alzheimer’s disease therapy.

“There is still a critical gap in our understanding of why some patients do not respond to treatment,” Kim said.

The research team will use the grant funds to develop machine learning models to identify patient subgroups who respond differently to treatments. “Not only can our proposed machine learning model identify an individual patient’s treatment efficacy, but the model is built in a privacy-preserving manner, without sharing patient-level data to an outside party,” Kim said.

Cui Tao, PhD, the Dr. Doris L. Ross Professor at the school, is contributing on three recently awarded grants, including serving as the contact principal investigator for a five-year NIH grant of more than $5.7 million. Collaborating on the grant is GQ Zhang, PhD, vice president and chief data scientist in the Office of Data Science at UTHealth Houston, and a professor with both McWilliams School of Biomedical Informatics and McGovern Medical School at UTHealth Houston, where he holds the Distinguished Chair in Digital Innovation. The project goal is to build the proposed Alzheimer’s Disease Clinical Trial Simulation framework — a standardized, accessible, and reusable 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,” Tao said. “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.”

Zhongming Zhao, PhD, professor, chair, and director of the Center for Precision Health at McWilliams School of Biomedical Informatics, serves as an investigator on three separate grants. The first is a newly awarded grant and joint project with Jiang. This NIH grant, which is the largest of the awards earned by faculty during this cycle, is for over $6.4 million. Zhao and Jiang aim to advance Alzheimer’s disease research by creating the “AIM-AI” genetic map. This tool has “the ability to transform the genetic catalog of Alzheimer’s disease in a way that is actionable, integrated, and multiscale,” Zhao said. Ultimately, AIM-AI will allow genetics to be integrated with other modalities and have clear utility for subsequent etiological and drug discovery studies.

Jiang is an investigator on six of the 16 awards; the most for faculty during this recent award period. He was also awarded an NIH grant for more than $3.4 million to establish a comprehensive informatics framework that integrates ontology and computational phenotyping to harmonize electronic health records (EHRs). “The aim is to build a digital patient profile over the trajectory of more than a decade. Alzheimer’s disease is gradual, and there are multiple evident sources that we can use to profile the degree of cognitive function changes influenced by multiple chronic conditions in different subpopulations,” Jiang said.

Degui Zhi, PhD, Glassell Family Professor with the school, was awarded a supplement to a current NIH project. The $381,000 budget will supplement a $4.8 million grant, as Zhi and his fellow researchers benchmark the AI algorithms they are developing on a standardized neuroimaging dataset.

National Library of Medicine grants

The NIH’s National Library of Medicine (NLM) awarded three new grants to McWilliams School of Biomedical Informatics faculty members, and another NLM grant was transferred to the school. Two-time alumna Laila Rasmy Bekhet, PhD, assistant professor, was awarded her first grant in August with a nearly $1.4 million grant from the NLM. Bekhet will contribute to the field of medical AI by creating enhanced training methods for clinical foundation models. These models have the potential to not only enhance the performance of a variety of clinical predictive models but also offer a viable solution to common issues that impede the acceptance of deep learning-based models in practice. Additionally, clinical foundation models can play a crucial role in providing accurate and comprehensive contextual and temporal representations of patients.

While Bekhet serves as the principal investigator, Tao and Zhi are additional investigators providing support. “I am eager to push the boundaries of scientific knowledge and contribute to the development of improved medical AI solutions that can further enhance health outcomes. I am confident that the world is eagerly awaiting our groundbreaking discoveries,” Bekhet said.

For one of his six grants, Jiang was awarded $3.2 million from the NLM to foster data sharing and collaborative research in the field of genomics, while maintaining stringent data privacy standards. The project will work toward integrating genomic data sharing with institutional review boards, which are responsible for approving clinical trials, for easier ethical review.

Zhao is also working with Xiangning Chen, PhD, professor, on their NLM grant, which received a $620,000 supplement. Those funds will help the researchers continue developing deep learning methods to transform genetic and genomic data into image-like objects and custom vocabulary for better data use in genetic research.

In September, Hongfang Liu, PhD, chair ad interim in the Department of Bioinformatics and Systems Medicine at McWilliams School of Biomedical Informatics and a distinguished Cancer Prevention and Research Institute of Texas (CPRIT) Scholar, transferred an NLM grant worth almost $1.9 million to the school. The project focuses on advancing informatics research on cohort discovery and identification with a goal of enhancing applications of EHR data for clinical research. The results will positively impact EHR data applications like learning health care systems, predictive modeling, and AI in health care.

National Human Genome Research Institute grants

The NIH’s National Human Genome Research Institute issued two awards to faculty during this recent cycle. Zhi earned a $2.5 million competitive renewal award for his grant originally awarded in 2018. Zhi’s team has spent the last few years building a new informatics tool that reveals detailed genetic relationships between humans. With the new funds, the researchers plan to further their work with “RaPID” — the first computationally feasible method for inferring identity-by-descent segments among individuals in a biobank-scale cohort.

Liu was awarded a new grant worth $2.8 million to address the diagnostic odysseys that patients with rare diseases experience. According to the NIH, an estimated 25 to 30 million Americans are affected by rare diseases. Liu says that due to the lack of clinical evidence and empirical knowledge, awareness of rare diseases remains low among health care providers. Liu’s research aims to address the translation gap by building an innovative, end-to-end informatics framework to accelerate the diagnosis of rare diseases.

Additional NIH grants

Two of Jiang’s awards are part of the NIH’s Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) Program. These grants are collaborations with Historically Black Colleges and Universities and Hispanic Serving Institutions. For the first AIM-AHEAD project, Kai Zhang, PhD, assistant professor,, Jiang and research colleagues will utilize machine learning and AI tools to examine the role donor-recipient blood type mismatches play in heart transplantations and help reduce health disparities by formulating interventions. The second AIM-AHEAD award includes Arif Harmanci, PhD, assistant professor, and Han Chen, PhD, associate professor with UTHealth Houston School of Public Health, as part of the team of researchers. For that collaborative grant, Jiang and colleagues will work with faculty from Tuskegee University to strengthen data governance and facilitate the adoption of artificial intelligence/machine learning technologies, while ensuring the ethical treatment and representation of minority populations.

Zhao is collaborating with two other researchers outside of the school on a $2.3 million National Cancer Institute grant. The project, which focuses on personalized immunotherapy for the lymphatic system, aims to advance cancer treatment research by utilizing state-of the-art imaging technologies, expertise in cancer vaccine design and production, single-cell RNA sequencing, immunoprofiling, and multiplex immunofluorescence.

Toufeeq Syed, PhD, associate professor and assistant dean of education informatics at McWilliams School of Biomedical Informatics, was awarded a one-year, $270,000 grant from the NIH’s National Institute of General Medical Sciences. Syed, who joined the school this summer, will use the funds to develop an online, asynchronous course that is open and accessible via the Internet to the larger biomedical research community.

A National Science Foundation “Infrastructure Innovation for Biological Research” grant worth over $515,000 was awarded to Xiaobo Zhou, PhD, the Dr. and Mrs. Carl V. Vartian Professor in Clinical Informatics at McWilliams School of Biomedical Informatics; Jianguo Wen, PhD, assistant professor; and Jiajia Liu, PhD, a postdoctoral research fellow. The funds will be used to create novel machine-learning approaches to advance the study of cell development.

Many of the grants will result in research and job opportunities for new faculty or current UTHealth Houston students.

“In order to deliver on all of these projects, our school will need motivated researchers to work side by side with the faculty members. The grants serve as a platform to propel the next generation of informatics leaders,” Dean Zhang said.

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[] McWilliams School of Biomedical Informatics researchers awarded $31M in grants for medical artificial intelligence innovation research