Join us for the next event in our Institute's fall 2025 Speaker Series featuring Théoden "Tay" Netoff, Ph.D., Professor, Department of Biomedical Engineering, Ronald L. and Janet A. Christenson Faculty Impact Fellow, University of Minnesota. 

This event is sponsored by the Institute for Integrative and Innovative Research (I³R). 

To join via zoom remotely:

Please click the link below to join the webinar: https://uark.zoom.us/j/86748544631?pwd=1Y1bW2ahh8LzleqBHPUjeajHAQ5JBC.1

Personalization of Neuromodulation Therapies

The promise of personalized medicine through neuromodulation is held back by a single, staggering challenge: an unimaginably vast number of potential treatment settings. Neuromodulation, which uses electrical pulses applied to the brain or spinal cord, treats conditions like epilepsy, Parkinson's disease, depression, and chronic pain, and offers significant potential for personalized care. Modern implantable pulse generators have a vast number of adjustable settings, including electrode contacts and stimulation parameters like pulse amplitude, width, and frequency. This results in a combinatorial explosion, with a potential parameter space of over four quadrillion possible configurations. Physicians currently lack the tools to effectively navigate this immense space and find the optimal settings for each patient. 

Our research addresses this critical need by developing systems engineering processes and tools to optimize neuromodulation therapies. We've created methods that, while not exhaustively exploring the entire parameter space, provide a structured approach for physicians to search for improved patient outcomes. We've successfully applied these tools across various clinical applications, demonstrating that even a partial exploration of the parameter space can lead to significant clinical improvements and surprising, often unanticipated, discoveries. These findings not only enhance the efficacy of current treatments but also offer new insights into the underlying mechanisms of neuromodulation. Our work highlights the critical role of systematic optimization and engineering principles in transforming complex medical device therapies from a trial-and-error process into a data-driven, personalized approach.