Across the pharmaceutical industry, teams struggle to access the depth and completeness of real-world data (RWD) needed to answer critical questions in Alzheimer’s Disease (AD).
The lack of integrated data reflects the interdisciplinary nature of dementia care, spanning geriatrics, neurology, and psychiatry, limits the ability to assess disease burden, model progression, and understand treatment patterns. Without an integreted dataset, pharma teams are forced to make high-impact decisions on incomplete evidence, slowing innovation, weakening payer and HTA submissions, and increasing risk across both pipeline and in- market strategies.
Existing datasets frequently lack the clinical detail needed to capture the entire patient journey. This includes important metrics such as cognitive scores (e.g., MoCA, MMSE, Mini-Cog), neuropsychiatric symptoms, caregiver context, biomarker and genetic results (such as tau, amyloid, and APOE), as well as neuroimaging occurrences (including PET, MRI, and CT). These gaps are particularly evident in complex cases of Alzheimer’s disease, early dementia, and Mild Cognitive Impairment (MCI). Additionally, neuropsychiatric complications, such as agitation, aggression, hallucinations, psychosis, and mood disturbances, can occur at any stage of Alzheimer’s disease. These complications impose significant clinical, economic, and caregiver burdens but are not well documented in most real-world data (RWD) sources.
NeuroBlu Data closes these critical evidence gaps with the largest, most clinically rich EHR-based datamart for Alzheimer’s Disease and dementia, linking structured and NLP-enriched unstructured data across all care settings over 20+ years.
The dataset includes cognitive assessments (MoCA, MMSE, SLUMS), detailed neuropsychiatric symptom capture, caregiver context, biomarkers (tau, amyloid, ), genetic markers (APOE ε3/ε4), and neuroimaging (PET, MRI, CT) — all standardized to OMOP for seamless analysis.
NeuroBlu Data enables pharma teams to:
Including prescribing practices at diagnosis, treatmentsequencing, rationale for changes, discontinuations,side effects, and progression to institutionalization, withadjustment for cognitive and neuropsychiatric factors.
Such as agitation, aggression, hallucinations, andpsychosis, as a consequence of integrating data fromgeriatrics, neurology, and psychiatry, and assess theirimpact on patients, caregivers, & healthcare resourceutilization (HCRU).
From early cognitive decline through advancedAlzheimer’s across multiple care settings, phenotypingby stage (MCI, mild, moderate, severe AD) andbehavioral profile (e.g., apathy vs. agitation).
To capture context that structured data alone missesincluding symptom severity, caregiver observations,cognitive function scores, ADL changes, crisis events,and qualitative rationale for treatment decisions.
Delivered with rapid onboarding and frequent refreshes, NeuroBlu Data empowers HEOR, epidemiology, market access, medical affairs, and commercial teams.t
