Predicting seizure patterns for people with focal epilepsy
Official title: Modeling seizures in patients with focal epilepsy
Funded at University of Colorado Denver · NIH-11169981 · Data updated 2026-11-12
This project builds tools to forecast how often seizures may happen over time for people with focal epilepsy using long-term seizure records.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Colorado Denver NIH-funded |
| Lab location | 1 site (Aurora, UNITED STATES) |
| Project start | September 19, 2023 |
| Project end | August 31, 2028 |
| Funding year | 2025 |
| Award (this year) | $420,551 |
| NIH project number | 5R01NS133040-03 |
| Project ID | NIH-11169981 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are people with focal epilepsy who keep regular seizure records or are willing to share longitudinal seizure data.
✕Less likely to help
People with generalized seizure types (for example, primary absence epilepsy) or those without ongoing seizure records are less likely to benefit directly from this work.
What this research studies
If you have focal seizures, this work looks at daily seizure records like yours to learn typical patterns and how they change over time. The team uses data from the Human Epilepsy Project, which tracked hundreds of people with focal epilepsy, and applies advanced statistical models that can find subgroups with different seizure trajectories. They also model 'clumping'—times when one seizure makes another more likely—to better predict near-term risk. The goal is to combine these patterns into dynamic, personalized forecasts that update as new seizure information becomes available.
Why it matters
Potential benefit: If successful, these tools could give people clearer, personalized forecasts of seizure risk to support treatment decisions and daily planning.
How similar studies have gone: Dynamic prediction models have helped other medical conditions and Hawkes-type models have described seizure clustering, but combining subgroup trajectories with clumping in focal epilepsy is a newer approach.
Where this research is happening
-
University of Colorado Denver
Aurora, United States Active
Researchers
- Principal investigator: Juarez-Colunga, Elizabeth — University of Colorado Denver
- Study coordinator: Juarez-Colunga, Elizabeth
Related research
Other NIH-funded projects on the same topics.
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Predicting seizure patterns in focal epilepsy patients
Aims to create personalized models to forecast how often seizures will happen over time in people with focal epilepsy.
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Understanding and predicting seizures in patients with focal epilepsy
This study is working on new ways to predict how often people with focal epilepsy might have seizures, using information from 450 patients to better understand their unique seizure patterns over time.
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Patchy (mosaic) genetic changes in focal epilepsy
This project looks for mosaic (patchy) genetic mutations in brain tissue from people with mesial temporal lobe epilepsy to better understand causes and help guide future treatment choices.
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Behavior-based signs to predict seizures and death risk in epilepsy
Researchers are using AI-driven 3D video analysis of mouse behaviors to find subtle behavior patterns that might signal seizure risk and higher mortality for people with epilepsy.
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Investigating a new treatment for seizures using a specific inhibitor in mice
This study is looking at how a special treatment might help reduce seizures in mice with epilepsy, especially when the condition starts after injuries like strokes or head trauma, and it uses a method that could be easier and safer than current treatments.
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Investigating how to predict epilepsy in newborns with seizures
This study is looking at the best medications to help newborns who have seizures, which can sometimes lead to bigger health issues later on, and it's for families with babies who might be experiencing these seizures.
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.