Alzheimer’s research faces persistent barriers, including fragmented knowledge, heterogeneous multimodal data, and the widespread loss of negative or unpublished results. These limitations slow hypothesis generation, reduce reproducibility, and contribute to high failure rates across the discovery and translation pipeline. The Consortium for Biomedical Research and Artificial Intelligence in Neurodegeneration (C‑BRAIN) addresses these challenges through development of an AI Biomedical Research Scientist—a transformative, scientist‑in‑the‑loop platform designed to accelerate discoveries in Alzheimer’s disease and related neurodegenerative disorders.

Phase 1 is producing three foundational capabilities: AI Literature & Data Synthesis with referenced, traceable evidence; a Negative/Unpublished Data Analyzer that learns systematically from failure modes to de‑risk scientific choices; and Reviewer Three, an AI reviewer providing structured critique to elevate rigor and reproducibility. Phase 2 integrates these tools into a unified AI assistant, enabling end‑to‑end scientific workflows—from question formation to synthesis, hypothesis generation, design critique, and decision support. The platform is built on secure, privacy‑preserving architectures that allow pharma and academic partners to contribute data without centralization, making it suitable for widespread deployment.

C‑BRAIN benefits from strong cross‑sector engagement, including fifteen Major Contributing and Key Members from academia, industry, technology, and philanthropy; interest from leading AI technology companies; and participation from over 100 biomedical and AI researchers and data scientists. These partners are actively supporting training and refinement of the AI’s capabilities. C‑BRAIN is well positioned to deliver measurable impact aligned with ADDF priorities, including enhanced biomarker selection, IND‑enabling confidence, and improved clinical trial design.

ADDF investment will accelerate Phase 2 integration, the development of biological foundation models, and expansion of this platform to aging and broader neurodegeneration—establishing a scalable system capable of advancing drug discovery, translation, and patient outcomes across multiple disease areas.