GALVANI Scalable Workflow Innovation for Focal tES Therapy

Objective

The ERC Galvani project aims to revolutionize transcranial electrical brain stimulation (tES) therapy for epilepsy through a computational breakthrough. By combining the expertise of clinical researchers and computational neuroscientists, the project will develop personalized brain stimulation solutions integrating magnetic resonance imaging (MRI) and stereoelectroencephalography (SEEG) data into advanced brain models. Neuroelectrics, a leader in medical neurotechnology, is implementing these solutions in a pipeline that transforms patient data into individualized brain models and optimized tES protocols in focal epilepsy. However, algorithms are highly dependent on the availability of high-quality MRI data and require time-consuming manual processing. Clinical translation at scale faces two key challenges: first, image head cropping and uneven data quality in MRI scans, and second, brain lesions, which deviate from normal anatomy and require manual segmentation by trained operators. These result in a more complex, time-consuming, and costly personalization process. To overcome these obstacles on the path from ground-breaking research to innovation, the SWIFT project introduces an AI-based deep learning approach that enhances MRI data quality and automates the handling of anatomical alterations, such as brain lesions, improving model accuracy and reducing processing time. To ensure translation into innovation, the project will develop a business strategy that addresses productization, regulatory, intellectual property, and commercialization challenges toward the goal of making model-driven tES therapy more scalable, cost-effective, and accessible to a broader range of epilepsy patients.