Taking Flight Award
Federico Moro, PhD / Mario Negri Institute for Pharmacological Research
This project will test whether a treatment that lowers GFAP levels can reduce these harmful changes and help prevent epilepsy from developing or make it less severe.
Taking Flight Award
Justin Ryan, PhD / SUNY Upstate Medical University
Dr. Ryan and his team will study breathing changes before, during, and between seizures in many more patients than was previously possible.
Taking Flight Award
Patrick Davis, MD, PhD / Boston Children’s Hospital
By uncovering how the brain responds to different levels of stimulation, this research could help make neurostimulation more personalized, leading to better seizure control and reducing the need for trial-and-error treatment approaches.
Bridge to Breakthrough Award
Ranmal Samarasinghe, MD, PhD / University of California, Los Angeles
With this grant, the team will test if correcting a gene can bring memory supporting cells back online.
Bridge to Breakthrough Award
Ankit Khambhati, PhD / University of California, San Francisco
By using advanced MRI technology, this team can look deeper into the brain’s unique wiring and structure than ever before.
Bridge to Breakthrough Award
Lauren Lau, PhD / Massachusetts General Hospital
Ultimately, this work aims to identify the biological mechanisms that trigger seizures and guide the development of more targeted and effective therapies to improve seizure control and quality of life for people living with epilepsy.
Bridge to Breakthrough Award
James Niemeyer, PhD / Cornell University
By studying both acute seizures and Dravet syndrome, Dr. Niemeyer hopes to uncover new cellular and network targets for therapies.
Catalyst Award
Deborah Kurrasch, PhD / Stream Neuroscience
The goal of this research is to complete safety testing to confirm that SN‑2000 is well‑tolerated and to determine safe dosing levels for its future development as a treatment for people with epilepsy.
SUDEP Clinical Biomarker Team Science Award
Satya Sahoo, PhD / Einstein Medical
Using advanced artificial intelligence, this team aims to make advances that will facilitate the development of a personalized risk prediction tool that can estimate an individual’s SUDEP risk and clearly explain the reasons behind it.
