Imagine having a digital copy of your brain that doctors can use to test medicines before you ever take them. Instead of guessing which pill works through trial and error, they run simulations on this virtual version to see the result. It's like a flight simulator, but for mental health treatment, ensuring the right dose and drug from the start.
Psychiatric treatment currently relies on trial-and-error pharmacotherapy, leading to poor outcomes for 30-50% of schizophrenia patients. This inefficiency creates a massive economic burden on healthcare systems.
A multiscale digital twin platform that integrates fMRI/sMRI data, AI, and HPC to simulate brain disease trajectories and predict drug responses.
If you are a drug developer dealing with high failure rates in clinical trials — this project developed a multiscale modelling ecosystem that predicts treatment response in silico. This allows for de-risked drug-discovery pathways and virtual trialling of pharmaceutical drugs.
If you are a MedTech company dealing with imprecise brain stimulation settings — this project developed a virtual brain twin that evaluates alternative treatments like brain stimulation. This helps in creating certified decision-support tools for clinicians.
If you are a clinic owner dealing with the fact that 30 to 50% of schizophrenic patients show insufficient response to treatment — this project developed a platform to optimize medication type and dosage. This reduces the economic burden of long-term trial-and-error care.
Based on available project data, no specific pricing or cost model for the end-user is mentioned; the project is funded by a EUR 10,000,000 EU contribution.
The project initially focuses on schizophrenia, but it aims to create a general ecosystem for generating virtual brain twins for psychiatric patients.
Based on available project data, the project provides an open, reproducible modelling framework and FAIR data pipelines, though specific commercial licensing terms are not detailed.
The platform is designed for alignment with the EU AI Act, GDPR, and the Digital Europe Virtual Human Twin roadmap to ensure data safety and protection.
The project runs from 2024-01-01 to 2027-12-31, with initial access for researchers before expanding to clinicians and patients.
The consortium is heavily research-oriented, consisting of 19 partners across 9 countries. It is dominated by 9 universities and 5 research institutions, with a very low industry presence (only 1 industry partner and 1 SME, representing a 5% industry ratio). This suggests the current output is primarily scientific and academic, requiring a strong bridge to commercialize the resulting decision-support tools.
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