# Personalized Seizure Forecasting: A Precision Medicine Approach > **NIH NIH R01** · YALE UNIVERSITY · 2024 · $1,319,282 ## Abstract PROJECT SUMMARY The hallmark of epilepsy is recurrent seizures, i.e., paroxysmal attacks of abnormal brain electrical activity that are associated with high morbidity and premature mortality. In addition to the direct morbidity of seizures, people with epilepsy must also contend with the ever-present uncertainty about when the next seizure will occur. The unpredictability of seizures represents a significant and disabling feature of epilepsy. Despite decades of research, there is no established method for determining when a seizure could occur. Akin to weather forecasts that estimate the probability of rain, seizure forecasts that quantify the likelihood of seizures over a future temporal window could increase the quality of life for patients and families living with epilepsy, so they could plan around a seizure event. A forecast could help patients and families prepare for, or even mitigate upcoming seizures. The overarching goals of the present proposal are (1) to elucidate the relationship between biochemical changes in saliva (a readily available biofluid that reflects systemic chemistry) and electrophysiological features that determine seizure likelihood (recorded from a Responsive Neurostimulation (RNS®) System) and (2) to leverage these relationships to develop effective seizure forecasting methods that will empower people with epilepsy with the unprecedented ability to anticipate and prevent seizures. We have strong preliminary data from people with epilepsy that several saliva chemicals exhibit novel multidien (multi- day) and circadian (~24-hour) concentration changes that correlate with periods of increased seizure likelihood. Our central hypothesis states that a latent biochemical variable for seizure likelihood can be detected in people with epilepsy using serial salivary sampling. We will pursue the following specific aims: (1) establish biochemical signatures of multidien seizure likelihood and develop effective seizure forecasting approaches; and (2) establish biochemical signatures of increased seizure likelihood over the circadian cycle. Successful completion of this project will significantly advance the fields of chronobiology, metabolism, and epilepsy by: (a) identifying novel multidien and circadian rhythms in biochemical and metabolic pathways in people with epilepsy and healthy controls, (b) linking these changes to possible causes of seizures, and (c) using these changes to forecast seizures and define a more effective standard of care. The expected positive impacts on public health will be to (a) empower people with epilepsy with the ability to anticipate and prevent seizures, (b) provide researchers with validated saliva sample collection and analysis approaches, and (c) discover ground-breaking biochemical insight into the human chrono-metabolome. Detailed knowledge about the chrono-metabolome is expected to fuel innovative studies on various episodic brain disorders that place a large burden on society, like migraine,... ## Key facts - **NIH application ID:** 11000075 - **Project number:** 1R01NS132121-01A1 - **Recipient organization:** YALE UNIVERSITY - **Principal Investigator:** Maxime Olivier Baud - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $1,319,282 - **Award type:** 1 - **Project period:** 2024-07-01 → 2029-06-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/11000075 ## Citation > US National Institutes of Health, RePORTER application 11000075, Personalized Seizure Forecasting: A Precision Medicine Approach (1R01NS132121-01A1). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/11000075. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*