Biomedical innovation
Driving the future of knowledge and care



UT researchers work across the spectrum of science. Some deepen our fundamental understanding of complex biomolecular, cellular, and structural mechanisms of the human body. Others build on those discoveries to put next-generation cancer therapies, imaging techniques, surgical tools, and orthopedic technologies into doctors’ hands.
These researchers are pioneering innovative tools, technologies, and methodologies, including advanced imaging, materials characterization, gene sequencing, bioinformatics, modeling, and machine learning. Across disciplines, they share one bold goal: restoring quality of life to its full potential.

UT’s Approach
By exploring the fundamentals of key molecules, cells, and tissues, UT researchers are laying the foundation for new drug discovery and clinical treatments. Teams develop innovation-enabling imaging techniques and preclinical models to study molecular mechanisms and understand the progression of an array of health conditions.
In partnership with Oak Ridge National Laboratory, UT is committed to developing new precision radioisotope cancer “theranostics”—diagnostics plus therapies—from concept to clinical application. The collaborative team has been awarded $20 million from the UT–Oak Ridge Innovation Institute to hire experts across multiple disciplines and build a center of excellence focused on developing new targeted cancer treatments.
Researchers are pursuing a wide range of advanced prediction, diagnostic, and surgical techniques and tools. Examples include biosensors for bacterial infection, wearables that remotely monitor patient vital signs, and improved surgical robots.
UT researchers are also collaborating with health care and industry partners to advance a precision medicine approach to orthopedics. They have developed and tested new prosthetic systems, bone regeneration technologies, artificial tendons, 3D printed implants and scaffolds, and other steps forward in regenerative medicine.
“My biggest goal for the future is that one day, we can completely reverse injury without putting permanent implants in the body—for example, a biological hip vs. a metal hip. We take an incremental approach while always keeping our eyes on this audacious end goal. We’re getting closer and closer to the technologies that will enable it.”
— David Anderson, Associate Dean for Research and Graduate Studies, UT College of Veterinary Medicine





Highlights

Researchers
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UT-ORNL Governor’s Chair for Advanced & Nanostructured Materials
Synthesis of biomaterials, biomedical devices, drug delivery, biomedical engineering, biosensors for health monitoring, applications of artificial intelligence, machine learning (ML) and deep learning (DL) in various science and engineering domains in: biopolymers, nanoscience, drug development, theranostic agents, developing new biomedically relevant instrumentations and sensor/monitoring environments for in vivo and in vitro methods
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Associate Dean for Research and Graduate Studies, College of Veterinary Medicine
Biomedical materials, medical devices, tissue regeneration, stem cells, biotherapies, bioactive particles, tissue scaffolds, animal models, tissue engineering, additive manufacturing, biometrics, biomechanics
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Assistant Professor, Nuclear Engineering
Nuclear medicine, molecular imaging, isotope production, radiochemistry, radiopharmaceutical development, cancer, targeted tracers, drug development, radiolanthanides, transition metals, small animal imaging, inorganic chemistry, biochemistry, ligand design, radiolabeling, diagnostic imaging, targeted therapy
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Heath Endowed Faculty Fellow in Business & Engineering and Associate Professor, Industrial and Systems Engineering
Markov decision processes, dynamic programming, predictive analytics, reinforcement learning, time series analysis, anomaly detection, genomics, critical care, chronic care, emergency medicine
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Professor, Mathematics, Associate Vice Chancellor, Director, AI Tennessee
Artificial intelligence, data science, quantum computing, machine learning, computational statistics, Bayesian statistics, topological data analysis, uncertainty quantification
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Fred N. Peebles Professor and IAMM Chair, Civil and Environmental Engineering
Structure-process-property relationships of natural and advanced materials, radiation-based imaging, scattering of materials and extreme environment, additive manufacturing, artificial intelligence-based cellular solids for multifunctional design, infinitely recyclable fiber reinforced composites, advanced green manufacturing






