The University of Maryland Institute for Health Computing (UM-IHC) in North Bethesda, Maryland, is the hub for health computing innovation and collaboration in Montgomery County.
UM-IHC merges the computational expertise, clinical expertise, biomedical innovation, health data and academic resources of the University of Maryland, College Park; the University of Maryland, Baltimore; and the University of Maryland Medical System to innovate health care delivery and support the Montgomery County life science community.
Partnering with the nearby critical mass of federal agencies and biotech industries, UM-IHC uses advanced computing to improve well-being and quality of life, fight disease and enhance outcomes for all people across Maryland and beyond.
UM-IHC is a signature initiative of the University of Maryland Strategic Partnership: MPowering the State, which provides funding support along with Montgomery County.
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Artificial Intelligence (AI) is revolutionizing our capacity to analyze data. The UM-IHC conducts research in AI and applies this powerful technology to bio-monitoring wearable, sensor data, clinical, and many other datasets to revolutionize medicine. The research involves exploring and analyzing the data using various learning models to find hidden patterns and relationships. This facilitates knowledge discovery that can be used to tackle health related problems and can eventually lead to better health in individual patients, communities, regions, and even larger areas.
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Bioinformatics processes large amounts of information across biological and clinical datasets, and has evolved substantially as a scientific field in the last decade. The UM-IHC leverages immense computational power to analyze and interpret very large amounts of biological data, such as gene sequences, transcriptomics, structural genomics, and more. These analyses can be linked to clinical data and used to anticipate disease, develop improved diagnostic and prognostic tools, and identify novel drug targets as well as disease biomarkers.
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Immersive visualization facilitates visual knowledge discovery from scientific and medical dataset that are incredibly challenging to visualize. The virtual world of the metaverse is the next horizon in health care. Immersive virtual reality/augmented reality (VR/AR) technologies for medical education have the potential to fundamentally change, improve and reduce the cost of training and maintaining skills across all aspects of health care—in Maryland, across the United States, and in developing countries worldwide.
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The future of clinical research is to decentralize patient engagement from medical centers to the community. At the UM-IHC, we will use data science and the Electronic Health Record to improve the way clinical research is performed. Specifically, we aim to generate clinical research data that reflects the communities at-hand, disrupts workflow, and increases the chances of successful findings at lower cost and greater efficiency. This will include a major focus on community-based and pragmatic clinical trials to build real-world evidence at high-scale, in line with emergent polices at the NIH, FDA, and other key policy-setters around the U.S. and world.
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Improving the health and wellbeing of all the residents of Maryland is at the core of UM-IHC’s mission, vision, and goals. Real-world data, advanced computational methods, community engagement, and interdisciplinary partnerships drive precision medicine at population scale, allowing for the classification of high-risk subpopulations, identification of the drivers of health and disease, and the development, testing, implementation, and dissemination of tailored interventions and care delivery models that meet patient and community needs.
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The UM-IHC will use AI, machine learning and network medicine to identify novel therapeutic targets as well as biomarkers that can be advanced into the Learning Health System. We will validate the importance of these newly discovered targets in chemical assays, cellular and animal disease models at allied partner institutes, and show that our findings are important for furthering disease understanding and clinical practice through biospecimen analyses. The UM-IHC will also develop real-time algorithms, software systems and toolkits that ingest, filter, visualize, and analyze multiple interacting data streams in the fields of protein and drug discovery.
