Periodic Reporting for period 1 - VIRTUAL BRAIN TWIN (Virtual Brain Twin for personalised treatment of Psychiatric Disorders)
Okres sprawozdawczy: 2024-01-01 do 2025-06-30
Schizophrenia and related psychoses impose a life‑long health and economic burden, yet clinical decisions still rely on coarse symptom scales and trial‑and‑error pharmacotherapy. Recent advances in neuroimaging, multiscale modelling and high‑performance computing now make it possible to move psychiatry from population averages to patient‑specific mechanisms.
Virtual Brain Twin (VBT) sets out to deliver that paradigm shift. The 17‑partner consortium is building the first personalised, multiscale “digital twin” of the human brain that links molecular pathways, microcircuits and whole‑brain networks to individual clinical profiles. Leveraging EBRAINS cloud‑HPC resources, VBT integrates curated multimodal datasets, biophysically detailed cell models and data‑driven AI to simulate disease trajectories and predict treatment response in silico. The initial clinical focus is schizophrenia, whose dopaminergic and glutamatergic dysfunctions are explicitly captured in our models.
The expected impact is three‑fold. Scientifically, VBT will provide an open, reproducible modelling framework and FAIR data pipelines that accelerate brain research across Europe. Clinically, virtual trialling of drugs and neuro‑stimulation on a patient’s twin promises earlier, safer and more cost‑effective care, potentially reducing the large annual EU burden of psychosis. Economically, the project cultivates a new digital‑health market around certified decision‑support tools and de‑risked drug‑discovery pathways.
From the outset, social‑science and humanities partners ensure that the technology evolves in dialogue with the people it serves. Ethnographic interviews, ethics‑by‑design guidelines and co‑creation labs with patients, relatives and clinicians steer data governance, consent models and user‑interface choices, safeguarding trust, transparency and inclusivity. Alignment with the EU AI Act, GDPR and the Digital Europe “Virtual Human Twin” roadmap positions VBT as an exemplar for responsible, human‑centric AI in health care.
By integrating cutting‑edge neuroscience with ethical, societal and industrial foresight, VBT lays the foundations for precision psychiatry and establishes Europe as a leader in digital-twin medicine.
Virtual Brain Twin (VBT) sets out to deliver that paradigm shift. The 17‑partner consortium is building the first personalised, multiscale “digital twin” of the human brain that links molecular pathways, microcircuits and whole‑brain networks to individual clinical profiles. Leveraging EBRAINS cloud‑HPC resources, VBT integrates curated multimodal datasets, biophysically detailed cell models and data‑driven AI to simulate disease trajectories and predict treatment response in silico. The initial clinical focus is schizophrenia, whose dopaminergic and glutamatergic dysfunctions are explicitly captured in our models.
The expected impact is three‑fold. Scientifically, VBT will provide an open, reproducible modelling framework and FAIR data pipelines that accelerate brain research across Europe. Clinically, virtual trialling of drugs and neuro‑stimulation on a patient’s twin promises earlier, safer and more cost‑effective care, potentially reducing the large annual EU burden of psychosis. Economically, the project cultivates a new digital‑health market around certified decision‑support tools and de‑risked drug‑discovery pathways.
From the outset, social‑science and humanities partners ensure that the technology evolves in dialogue with the people it serves. Ethnographic interviews, ethics‑by‑design guidelines and co‑creation labs with patients, relatives and clinicians steer data governance, consent models and user‑interface choices, safeguarding trust, transparency and inclusivity. Alignment with the EU AI Act, GDPR and the Digital Europe “Virtual Human Twin” roadmap positions VBT as an exemplar for responsible, human‑centric AI in health care.
By integrating cutting‑edge neuroscience with ethical, societal and industrial foresight, VBT lays the foundations for precision psychiatry and establishes Europe as a leader in digital-twin medicine.
During the first 18 months, VBT advanced the technical and scientific foundations for multiscale brain-twin modelling. A Data Management Plan was implemented and accompanied by a publication on Sharing Imaging Data in the Open Science Era (Giehl et al. 2024 Lancet Digital Health). An automated MRI processing pipeline with integrated quality assurance was developed and published (Bey et al., 2024).
On the modelling side, partners generated microcircuit and network models incorporating schizophrenia-related alterations, and designed mean-field models for hippocampus, thalamus, and striatum (Tesler et al., 2024–25; di Geronimo et al., 2025). The first whole-brain model integrating the dopaminergic subsystem was implemented for schizophrenia, enabling disease-relevant parameter sweeps to explore neurotransmitter modulation on brain dynamics.
Machine learning pipelines for reconstructing neural mass models were developed, linking microscale simulations to whole-brain activity. These developments lay the groundwork for simulating disease trajectories and therapy response in silico and developing the workflows for the clinical trials using patient-specific virtual brain twins.
On the modelling side, partners generated microcircuit and network models incorporating schizophrenia-related alterations, and designed mean-field models for hippocampus, thalamus, and striatum (Tesler et al., 2024–25; di Geronimo et al., 2025). The first whole-brain model integrating the dopaminergic subsystem was implemented for schizophrenia, enabling disease-relevant parameter sweeps to explore neurotransmitter modulation on brain dynamics.
Machine learning pipelines for reconstructing neural mass models were developed, linking microscale simulations to whole-brain activity. These developments lay the groundwork for simulating disease trajectories and therapy response in silico and developing the workflows for the clinical trials using patient-specific virtual brain twins.
VBT has pushed digital‑twin neuroscience beyond current limits. We released open‑source pipelines that render sensitive imaging data FAIR, enabling compliant twin construction already underpinning high‑impact publications. We also advanced producing the first biophysically detailed schizophrenia models for cortex, thalamus, basal ganglia and cerebellum, and introduced region‑specific mean‑field components so whole‑brain twins now reflect local pathophysiology. Clinically we linked these parameters to data‑driven symptom dimensions, offering model‑based biomarkers for early psychosis stratification. A cloud‑HPC “playground” provides the framework for reproducible workflows, accelerating community uptake. VBT teams mapped stakeholders and IP routes, and produced an AI‑Act‑aligned ethics framework that de‑risks clinical deployment. The impact is in precision psychiatry, potentially de‑risking drug discovery in a scalable EU brain‑twin market. Next steps include finalization and testing of clinical workflows, and preparation of prospective clinical trials and regulatory‑sandbox pilots.