ArticleAlzheimer's & dementia (New York, N. Y.)
Pooling Alzheimer's disease clinical trial data to develop personalized medicine approaches is easier said than done: A proof-of-principle study and call to action.
Article in Alzheimer's & dementia (New York, N. Y.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Changes in Daily Functioning in Association With Tau and Amyloid Among Unimpaired Older Adults With and Without Elevated Amyloid.Neurology · 2025Trial
- Pooling Alzheimer's disease clinical trial data to develop personalized medicine approaches is easier said than done: A proof-of-principle study and call to action.Alzheimer's & dementia (New York, N. Y.)Article
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Authors and funding
9 authors.
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Abstract
With the advent of the first generation of disease-modifying treatments for Alzheimer's disease, it is clearer now more than ever that the field needs to move toward personalized medicine. Pooling data from past trials may help identify subgroups most likely to benefit from specific treatments and thus inform future trial design. In this perspective, we report on our effort to pool data from past Alzheimer's disease trials to identify patients most likely to respond to different treatments. We delineate challenges and hurdles, from our proof-of-principle study, for which we requested access to trial datasets from various pharmaceutical companies and encountered obstacles in the process of arranging data-sharing agreements through legal departments. Six phase I-III trials from three sponsors provided access to their data (total HIGHLIGHTS: Pooling data from past Alzheimer's disease clinical trials may help identify subgroups most likely to benefit from specific treatments and may help inform future trial design.Accessing past trial datasets is complicated, frustrating the field's communal effort to find the best treatments for the right individuals.We urge trial sponsors and the academic research community to remove data access barriers and improve collaboration through practicing open science and harmonizing outcome measures.
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