Sixteen computational Alzheimer's hypotheses presented at the Alzheimer's Association International Conference (AAIC 2026), London, July 11–15 2026. All 16 certified In-Person Posters. None of the 16 hypotheses has been tested in a wet lab.
Every poster below is a computational hypothesis. Not a validated finding. The goal of the Neurodegenerative Reversal Research Foundation is to fund wet-lab validation of these hypotheses.
Authors on all 16: David S. Lewis, Enrique Zueco, Haley Yi — AIXC Research. Certified by the Alzheimer's Association via cOASIS (the Association's official abstract platform). The abstract supplement publishes in Alzheimer's & Dementia around December 2026. We list the pericyte biomarker poster first because it is the one we want to test first.
Fluid Biomarkers Of Pericyte Injury For Precision Vascular Subtyping
Not yet tested in a lab. This is a computational hypothesis.
Recursively Optimizing AI Swarms For Precision Target Discovery: A Persistent-memory Approach To Neurodegeneration
Not yet tested in a lab. This is a computational hypothesis.
Reinforcement Learning With World Models For Optimizing Alzheimer's Disease Treatment Timing And Dosing
Not yet tested in a lab. This is a computational hypothesis.
Test-time Scaling And Self-verification For Precision Alzheimer's Diagnostics: Thinking Slower To Think Better
Not yet tested in a lab. This is a computational hypothesis.
Reinforcement Learning From Verifiable Rewards In CNS Drug Optimization
Not yet tested in a lab. This is a computational hypothesis.
Neuro-symbolic AI For Alzheimer's Disease: Physics-informed Biomarker Prediction And Verifiable Intervention Planning
Not yet tested in a lab. This is a computational hypothesis.
Co-evolving Virtual Cell Models And Perturbation Planners For Alzheimer's Disease Drug Discovery
Not yet tested in a lab. This is a computational hypothesis.
Neuro-symbolic Recursive Self-verification For Alzheimer's Disease Modeling: Anchoring AI In Biological Physics
Not yet tested in a lab. This is a computational hypothesis.
Dynamic Causal Discovery: Open-ended Mapping Of Neuroinflammatory Pathways
Not yet tested in a lab. This is a computational hypothesis.
Iterative Self-critique For Uncovering Cryptic Epistasis In Alzheimer's: Multi-hop Genomic Reasoning Via Monte Carlo Tree Search
Not yet tested in a lab. This is a computational hypothesis.
Self-improving Discovery Agents In AI-driven Neurodegenerative Disease Research
Not yet tested in a lab. This is a computational hypothesis.
Execution-grounded AI Scientist For Autonomous Alzheimer's Drug Target Discovery
Not yet tested in a lab. This is a computational hypothesis.
Hierarchical Disease-state Generators For Neurodegenerative Genomics: Simulating Multi-omic Interventions
Not yet tested in a lab. This is a computational hypothesis.
Coherence-validated Causal World Models For Multi-scale Alzheimer's Disease Progression And Pharmacologic Reversal
Not yet tested in a lab. This is a computational hypothesis.
AI-driven Physicochemical Optimization Of Allosteric NAMPT Modulators: From Generative Chemistry To Brain-penetrant Therapeutics
Not yet tested in a lab. This is a computational hypothesis.
Neuro-symbolic Ideation Engines For Alzheimer's Therapeutics: Preventing Biological Hallucinations In Autonomous Discovery
Not yet tested in a lab. This is a computational hypothesis.
These 16 hypotheses exist only on paper. The next step is experimental validation. Partner with us to make it happen.
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