Neurava Receives NIH Grant to Develop SUDEP Risk Assessment Platform

In recent news, the National Institutes of Health (NIH) awarded Neurava Inc. a $4 million Blueprint MedTech Optimizer grant to support development of a sudden unexpected death in epilepsy (SUDEP) risk stratification and forecasting algorithm. The funding, which could extend for up to 4 years, will support advancement and validation of a quantitative SUDEP risk assessment platform designed to improve clinical prediction and decision-making, with the long-term goal of advancing toward first-in-human clinical evaluation.¹

"This award represents a pivotal moment for Neurava and for the epilepsy community," Vivek Ganesh, PhD, Co-CEO & Co-Founder, Neurava, said in a statement.¹ "Despite decades of research, SUDEP risk remains difficult to quantify and communicate in a clinically actionable way. This program allows us to move beyond fragmented risk factors and toward a unified, quantitative framework that can meaningfully inform patient care and clinical decision-making."

The NIH Blueprint MedTech program is a competitive, trans-agency initiative aimed at accelerating development of neurotechnology innovations toward clinical use. The Optimizer award supports device and algorithm development, as well as validation and integration into clinical settings. Neurava’s selection highlights the need for more objective, data-driven approaches to understanding and mitigating SUDEP risk, a leading cause of mortality among people with epilepsy.¹

The company’s platform includes a wearable system composed of a neckband and armband designed to capture multimodal physiologic data. According to Neurava, the armband measures seizure-related activity, while the neckband monitors cardiac, respiratory, and oxygen saturation signals, enabling detection and alerting capabilities intended to support early intervention during high-risk periods such as nighttime.²

For context, the device uses AI-based algorithms to analyze physiologic data and estimate SUDEP risk. A web-based portal then allows patients and clinicians to monitor trends over time, and the system can generate alerts to caregivers or emergency medical services when high-risk events are detected.²

READ MORE: Survey Highlights Gaps in Epilepsy Treatment Expectations and Communication

SUDEP remains one of the leading causes of mortality among individuals with epilepsy, with an estimated incidence of approximately 1 per 1000 patient-years in adults, and higher rates observed in those with uncontrolled seizures. Although the underlying mechanisms are not fully understood, peri-ictal dysfunction involving respiratory, cardiac, and autonomic systems is believed to play a central role.³

Established risk factors include frequent generalized tonic-clonic seizures, nocturnal seizures, and suboptimal adherence to antiseizure medications; however, accurately quantifying individual patient risk in clinical practice remains a persistent challenge. As a result, there is growing interest in objective, data-driven tools that can support risk stratification and enable earlier intervention in high-risk populations.³

Neurava is an innovative MedTech startup focused on developing wearable technology that can detect and alert for seizures, cardiorespiratory dysfunctions, and stratify SUDEP risk. According to the company, its multi-modal monitoring platform posseses the potential to improve the lives of those affected by epilepsy.¹

REFERENCES
1. Neurava Awarded $4 Million NIH Blueprint Optimizer Award to Develop SUDEP Risk Stratification Algorithm. Neurava Inc. News Release. Arpil 23, 2026. Accessed May 5, 2026. https://www.prnewswire.com/news-releases/neurava-awarded-4-million-nih-blueprint-optimizer-award-to-develop-sudep-risk-stratification-algorithm-302751938.html
2. Neurava Inc. Products. Neurava website. Accessed May 5, 2026. https://www.neurava.com/products
3. Sudden unexpected death in epilepsy (SUDEP). Centers for Disease Control and Prevention. Reviewed November 2, 2023. Accessed May 5, 2026. https://www.cdc.gov/epilepsy/sudep/index.html