Bridging Engineering and Medicine
The Model-Informed Medical Engineering Laboratory (Jae Ho "Mike" Lee, PI) is a computational science research group at Old Dominion University affiliated with the Department of Mechanical and Aerospace Engineering, working closely with the Institute for Engineering in Medicine, Health, and Human Performance (EnMed) in the Batten College of Engineering and Technology, the Virginia Modeling, Analysis, and Simulation Center (VMASC) and the Sentara Center for Healthcare Simulation and Immersive Learning at Macon & Joan Brock Virginia Health Sciences, with clinical integration through Sentara Health and Sentara Hospitals.We focus on developing high-fidelity computational models to simulate and predict complex physiological systems in health and disease. The goal of the group is to advance digital twins for various physiological systems to support biomedical innovation (therapies and medical devices), clinical and educational applications, and regulatory science.
Our research focuses on the development of high-fidelity computational models to simulate, analyze, and predict complex physiological systems in health and disease. A central goal of the lab is to advance digital twin frameworks for physiological systems, enabling model-informed decision-making in biomedical innovation, including medical devices and therapies, as well as applications in clinical practice, education, and regulatory science.
We develop computational models of bioprosthetic heart valves to study their structural mechanics, fluid-structure interaction, and long-term performance under physiological loading. Using patient-specific and idealized geometries, our work aims to improve the understanding of valve durability, hemodynamics, and disease progression, while supporting the design and evaluation of next-generation valvular therapies within a digital twin framework.
Our research in gastric biomechanics focuses on modeling the mechanical behavior and motility of the stomach, including wall deformation, peristalsis, and interactions with luminal contents. These models are used to investigate how physiological variability and disease states influence gastric function, with applications in orally administered drug delivery, device development, and mechanistic understanding of gastrointestinal physiology.
We apply computational fluid dynamics and multiphase modeling approaches to study orally inhaled drug products (OIDPs), including aerosol transport, deposition, and device-airway interactions. This work supports model-informed assessment of bioequivalence and performance, bridging fundamental transport physics with regulatory and translational considerations relevant to inhaler design and evaluation.
A core emphasis of the MIME Lab is the development and evaluation of credible computational models for decision-making in biomedical and regulatory contexts. We study verification, validation, uncertainty quantification, and context-of-use-driven model assessment to ensure that computational tools are scientifically sound, transparent, and fit for purpose. This work supports the responsible use of simulation in medical device evaluation, drug development, and emerging digital twin applications.
We explore the use of large language models (LLMs) to support computational modeling workflows, regulatory science, and scientific knowledge extraction. This includes applications such as structured interpretation of regulatory documents, automation of model review tasks, and integration of language models with physics-based simulations to enhance transparency, reproducibility, and efficiency in model-informed research.
The MIME Lab is driven by a vision of advancing medicine and regulatory science through the rigorous application of engineering-based modeling and simulation. Our work aligns with Old Dominion University’s Life-Changing Research Initiative and its Strategic Research Framework, which emphasizes health innovation and leadership in modeling and simulation.
We actively foster collaboration and knowledge exchange across engineering, medicine, regulatory science, and industry. We welcome partnerships with researchers, clinicians, students, and organizations interested in advancing computational approaches for biomedical innovation. If you are interested in our research or exploring collaborative opportunities, we invite you to connect with us and contribute to shaping the future of model-informed medicine.
📩 Contact us at: jhlee@odu.edu