Commercialization Readiness of an Intraoperative EEG-Guided Precision Anesthesia Management System to Prevent Postoperative Delirium in Elderly and Patients at Risk for Alzheimer's & Related Dementia

Each day in the United States, over 100,000 patients receive general anesthesia, with about 40% being aged 60 and above. The current practice of general anesthesia is prone to over-sedating patients, either due to the lack of brain monitoring or using brain monitors with inaccurate indices. Over-sedation (at 28% incidence) contributes to post-operative delirium (POD) in the elderly population (≥60yrs). Notably, 11% of these elderly patients suffer from Alzheimer’s Disease and Related Dementias, placing them at an even higher risk of POD. PASCALL was founded to introduce a novel wireless neuroscience-based EEG-guided personalized anesthetic management. In our original grant, AG066325, we achieved a) (AG066325 Aim 1,2) the design, development, and FDA 510(k) pre-market clearance of a wireless anesthetic brain monitor, designated as M0 and b) (AG066325 Aim 3) the development of personalized algorithms to monitor anesthetic brain state in aging, dementia, and Alzheimer’s disease patients. In this grant, we propose concrete steps to commercialize M0 and the personalized algorithms developed in AG066325, collectively designated as PASCALL M1. We realize this innovation through the following specific aims: Aim 1 focuses on a pilot study to determine sample size, cost, and timeline for a Phase III multi-site trial while optimizing workflows, outcome measures and caregiver protocol adherence. Insights from the pilot will inform the development of a comprehensive Phase III protocol, site selection, and assembly of a cross-functional team to secure FDA clearance and support market adoption. Aim 2 and 3 focuses on enhancing the PASCALL M1 device's workflow and manufacturing capabilities. Key goals include developing FDA-compliant, in-house manufacturing under ISO 13485:2016 and achieving MDSAP certification for regulatory compliance. The device design will be streamlined to reduce application steps and improve workflow efficiency. If successful, this effort will demonstrate through clinical studies that our system can significantly reduce POD incidence, saving the healthcare system tens of billions of dollars annually by enabling early detection of POD risk and active anesthesia management, leading to shortened hospital stays by an average of 3 days for each patient developing POD after surgery.