Unmet Need
Chronic pain affects about 100-million adults in the United States and is primarily treated with drugs, which can have significant negative side effects (NIH-Institute of Medicine). A promising alternative therapy is electrical peripheral nerve stimulation (PNS) therapy. However, PNS therapy has been associated with suboptimal efficacy because the amount of stimulation to deliver is often uncertain and the current therapies are primarily open-loop (i.e. require manual adjustment of the stimulation parameters). Critical to advancing PNS treatment is a deeper understanding of pain processing, but the pain system is difficult to probe experimentally and analyze computationally. Mechanistic models of pain transmission have been developed to investigate the appropriate amount of stimulation necessary but the data from these models have proven difficult to analyze. There is a strong need for a computational method that quantifies pain and relays the proper amount of PNS to adequately alleviate the pain.
Technology Overview
Johns Hopkins researchers have developed a closed-loop approach to control PNS in a manner that reduces amplified pain signals caused by injury or disease, while still maintaining normal pain processing capabilities. Closed-loop PNS therapies can automatically adapt based on the patient’s current need to reduce pain transmission to the brain.
Stage of Development
Preclinical data is available.
