Why Alzheimer's Disease Needs a New Diagnostic Paradigm
Current approaches to Alzheimer's diagnosis are reactive, expensive, and often too late. We need a fundamental shift toward early biological detection.
Global Impact
More than 55 million people worldwide currently live with Alzheimer's disease or other forms of dementia, with projections suggesting this number will nearly triple by 2050.
Late Detection
Current diagnostic approaches rely heavily on cognitive assessments and clinical symptoms, which typically only manifest years after the disease has already caused significant neuronal damage.
Imaging Limitations
While brain imaging techniques like PET and MRI can detect amyloid plaques and tau tangles, they often miss the earliest molecular changes and are expensive, invasive, and inaccessible to many patients.
Biomarker Gaps
Existing blood and cerebrospinal fluid biomarkers lack the sensitivity and consistency needed for reliable early screening, leading to missed diagnoses and delayed interventions.
Gut Signals Ignored
Emerging research reveals that gut microbiome dysbiosis and metabolic disruptions occur years before cognitive decline, yet these early biological signals are not captured by standard diagnostic protocols.
Treatment Window
Without early detection, patients miss the critical window for therapeutic intervention when treatments could be most effective at slowing disease progression and preserving cognitive function.
These challenges demand a paradigm shift: from detecting Alzheimer's after irreversible damage to identifying biological risk signals years before symptoms appear. NeuroBiome AI is our answer.