From Clinical Research Pioneer to AI Explorer
For decades, J. Michael Dean, MD, MBA, helped shape the infrastructure behind some of the nation's most important
clinical research efforts. A Professor Emeritus in the Department of Pediatrics and founder of the University of Utah's Data Coordinating Center, Dean built systems that support large-scale, multi-site clinical trials and advance pediatric
research nationwide.
For decades, J. MichaelToday, retirement has not slowed his curiosity.
After retiring in 2024, Dean enrolled in an AI Engineering bootcamp to better understand how emerging AI technologies
could support clinical research. His capstone project focused on a challenge familiar
to many research teams: accelerating clinical trial startup. Using publicly available
clinical trial protocols, he developed a prototype application capable of generating
draft informed consent documents, demonstrating how AI might help reduce administrative
burden and streamline research workflows.
What surprised him most was the speed at which modern AI tools could help bring an
idea to life. Working alongside generative AI coding assistants, Dean was able to develop and deploy a functioning prototype while learning entirely new
technical skills along the way.
His exploration of AI has extended well beyond clinical research. An avid model railroader,
Dean has used AI-assisted development tools to create software that controls his model
railroad through a custom Python interface. He has also begun incorporating AI into
hobbyist engineering and design projects, using it to generate code for custom 3D-printed
components.
Through these experiments, Dean sees AI as a powerful tool for learning, problem-solving, and innovation
"I think it is important for faculty and staff to understand the potential here," he shared. "This technology is moving incredibly quickly."
For Dean, AI represents the latest chapter in a lifelong commitment to embracing new technologies
in service of research and discovery. From helping build national clinical research
networks to exploring AI-assisted development, his journey reflects a mindset that
continues to ask what might be possible next.