AI‐driven patient selection can drastically reduce sample sizes in Alzheimer's disease clinical trials

An AI-driven patient selection method can drastically reduce the sample size and cost of a trial by at least 20%, while maintaining statistical power, thereby accelerating therapeutic development by enabling more cost-effective trials.

Authors

Publication Details

Journal
Alzheimer s & Dementia
Published
2025-12-01
DOI
https://doi.org/10.1002/alz70859_100413
Primary Topic
Dementia and Cognitive Impairment Research
Type
article
Field-Weighted Citation Impact
0.00
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article

AI‐driven patient selection can drastically reduce sample sizes in Alzheimer's disease clinical trials

Christian Dansereau, César Laurent, Adrián Noriega de la Colina, Angela Tam
Alzheimer s & Dementia
Dementia and Cognitive Impairment Research
article

AI‐driven patient selection can drastically reduce sample sizes in Alzheimer's disease clinical trials

Christian Dansereau, César Laurent, Adrián Noriega de la Colina, Angela Tam
article en

Abstract

An AI-driven patient selection method can drastically reduce the sample size and cost of a trial by at least 20%, while maintaining statistical power, thereby accelerating therapeutic development by enabling more cost-effective trials.

Alzheimer s & DementiaVol. 21(S5)
Openalex Percentile: Top 34%
Dementia and Cognitive Impairment Research
DOIOpen Access PDFOpenAlex
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AI‐driven patient selection can drastically reduce sample sizes in Alzheimer's disease clinical trials — Christian Dansereau, César Laurent, et al. · Alzheimer s & Dementia (2025) | TGRS Research Map | TGRS