Identifying biomarkers to predict outcomes from brain stimulation for epilepsy
Official title: Biomarkers to Predict Outcome from Responsive Brain Stimulation for Epilepsy
Funded at University of Pennsylvania · NIH-11092694 · Data updated 2026-11-12
This study is looking to find ways to predict how well people with hard-to-treat epilepsy will do with a special brain device called responsive neurostimulation, so they can get the best treatment possible.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Pennsylvania NIH-funded |
| Lab location | 1 site (Philadelphia, United States) |
| Project start | April 1, 2023 |
| Project end | March 31, 2026 |
| Funding year | 2025 |
| Award (this year) | $1,105,222 |
| NIH project number | 5R61NS125568-03 |
| Project ID | NIH-11092694 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals with intractable epilepsy who are not suitable candidates for surgical intervention.
✕Less likely to help
Patients who have well-controlled seizures with medication or those who are not candidates for brain stimulation therapy may not benefit from this research.
What this research studies
This research aims to develop biomarkers that can predict how well patients with intractable epilepsy will respond to a brain stimulation device known as responsive neurostimulation (RNS). By analyzing clinical and electrophysiological data, the study will use machine learning techniques to create a predictive biomarker signature. This signature will help determine the most effective therapy for patients who have not responded to medication. The goal is to improve clinical decision-making and ensure that patients receive the most suitable treatment options.
Why it matters
Potential benefit: If successful, this research could lead to more personalized and effective treatment options for patients with epilepsy, potentially improving their quality of life.
How similar studies have gone: Other research has shown promise in using biomarkers for predicting treatment outcomes in epilepsy, but this specific approach using machine learning and federated data analysis is relatively novel.
Where this research is happening
-
University of Pennsylvania
Philadelphia, United States Active
Researchers
- Principal investigator: Davis, Kathryn Adamiak — University of Pennsylvania
- Study coordinator: Davis, Kathryn Adamiak
Related research
Other NIH-funded projects on the same topics.
-
Scaling Up Task-Shifted Epilepsy Care for Children in Africa
A study to help children with epilepsy in Africa get diagnosed and receive seizure care through trained community health workers.
-
Closed-loop control of interneuron timing to influence seizures and memory in epilepsy
A study tests a brain-quieting system that uses light to precisely time certain brain cells in epilepsy-prone mice to see if this can lessen seizures and improve memory.
-
Epilepsy Data Ecosystem: A Big-Data Sharing Platform for Better Care
A national effort to collect and share large, multi‑modal brain data from people with medication‑resistant epilepsy to speed discoveries and improve treatment options.
-
Exploring epilepsy genes in zebrafish to understand human brain seizures
A study in zebrafish will model human epilepsy genes to help explain how certain brain mutations contribute to seizures.
-
New MRI tools to better plan pediatric epilepsy surgery
A new MRI-based approach helps doctors decide the best time to surgically remove brain tissue in children with difficult-to-control seizures.
-
Sahel Epilepsy Study: finding patterns in epilepsy in rural Africa and its links to genes
A plan to study epilepsy in rural Nigeria to discover how common it is, what factors affect risk, and how genetics may influence it, with results that could improve care for people with epilepsy.
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.