Imagine having a digital copy of a person's brain that doctors can use to test treatments without any risk to the patient. This system creates these 'virtual brains' using a mix of medical scans and genetic data while keeping the person's identity completely secret. It is like a flight simulator, but for neurology, helping researchers predict how dementia progresses.
Biomedical research is stalled because patient data cannot be shared or used for personalized therapy without risking the patient's identity. Current anonymization methods are insufficient for complex neuroimaging data.
A distributed research platform and four demonstrators: a neurodegeneration simulation tool, a multiscale model visualizer, a disease prediction improver, and a subclass identification tool.
If you are a drug discovery firm dealing with high failure rates in clinical trials — this project developed a simulation demonstrator for neurodegeneration that allows testing drug effects on virtual brain twins before human trials.
If you are a medical AI software developer dealing with strict GDPR rules on patient data — this project developed a distributed research platform that ensures data protection by design and by default.
If you are a neurological diagnostic center dealing with late-stage dementia detection — this project developed a demonstrator improving disease prediction to identify risks earlier using multiscale data.
Based on available project data, no specific pricing or commercial cost model is mentioned; it is described as a research infrastructure for academia and the private sector.
The project aims to provide thousands of multilevel virtual brains, suggesting a high capacity for scaling across large patient cohorts.
Based on available project data, specific licensing terms are not provided, though it is designed as an open yet protected space for innovation.
The platform is built to be compliant with EU General Data Protection Regulations (GDPR) using data protection by design and by default to prevent re-identification.
It integrates data from multiple sources, including genomics, proteomics, imaging, and wearables, annotating them to a common 3D brain space.
The consortium is heavily weighted toward research and academia, with 12 universities and 8 research institutes. However, there is a strategic industrial presence with 2 industry partners and 4 SMEs, representing a 9% industry ratio, which indicates a bridge between theoretical brain modeling and commercial health-tech application.
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