C-BRAIN currently runs 64 NVIDIA data center GPUs on premises alongside cloud-based nodes on Microsoft Azure, with additional NVIDIA GPU capacity, including NVIDIA Blackwell systems , on the horizon as the consortium’s ambitions scale.
To explore how AI and accelerated computing can advance Alzheimer’s research while navigating its technical demands, C-BRAIN is working with NVIDIA to incorporate technologies including the NVIDIA BioNeMo open developer platform and the MONAI framework for C-BRAIN’s research pipelines.
“The C-BRAIN collaboration with NVIDIA aims to unlock those models in a way that they can deliver something quite impactful and important,” said Bateman.
“A great deal of optimization is going to be needed as we push the boundaries of what today’s spatial omics machine learning architectures can model,” Ojewole said. “NVIDIA software is definitely going to come into play there.”
Researchers at C-BRAIN have already built two tools: OpenScientist — built with Lawrence Berkeley National Laboratory in an effort led by research scientist Justin Reese — and InsightEngine , built with 387 Labs.
OpenScientist is an open source agentic AI co-scientist that takes a scientist’s research question and dataset, then semi-autonomously generates hypotheses, runs analyses and produces verifiable, auditable insights. InsightEngine is an open source research platform that uses agentic AI to test hypotheses against the scientific literature, analyzing user-supplied datasets, exploring a biomedical knowledge graph and checking every claim against evidence to catch hallucinations before researchers commit to costly experiments.
In published case studies, OpenScientist completed analyses in minutes that domain scientists estimated would take weeks to months, at a cost of under $10 per run. At C-BRAIN’s current reach of over 200 research groups, this capability could release substantial research capacity, potentially exceeding one million hours annually at scale.
Looking ahead, C-BRAIN aims to build a multimodal biological foundation model trained on the full breadth of its data — neuroimaging, multi-omics, fluid biomarkers and longitudinal clinical measures.
By year three, it aims to discover new causal mechanisms of brain aging and Alzheimer’s disease, moving to testable scientific principles using the full scope of available research and data.
Bateman said, “ AI that can think and reason has the potential to accelerate discoveries that will lead to powerful and implementable preventions and treatments for the entire population.”
Key considerations
- Investor positioning can change fast
- Volatility remains possible near catalysts
- Macro rates and liquidity can dominate flows
Reference reading
- https://blogs.nvidia.com/blog/open-source-ai-tools-cbrain-dementia/#primary
- https://blogs.nvidia.com/blog/author/acosta/
- https://blogs.nvidia.com/blog/open-source-ai-tools-cbrain-dementia/#disqus_thread
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Informational only. No financial advice. Do your own research.