Challenge: Pioneering Research for Early Prediction of Alzheimer's and Related Dementias EUREKA – Innovita Research

Challenge: Pioneering Research for Early Prediction of Alzheimer's and Related Dementias EUREKA

Alzheimer's disease and Alzheimer's disease-related dementias (AD/ADRD) impact over 6 million Americans, causing progressive cognitive, functional, and behavioral impairments. Early detection is crucial, especially with emerging treatment options, but current clinical tools are not sensitive enough for early prediction.

Elderly man painting - illustrative photo.

Elderly man painting – illustrative photo. Image credit: Carola68 via Pixabay, free license

The National Institute on Aging (NIA), part of the National Institutes of Health (NIH), is running the PREPARE Challenge (Pioneering Research for Early Prediction of Alzheimer's and Related Dementias EUREKA Challenge) to advance solutions for accurate, innovative, and representative early prediction of AD/ADRD.

To achieve this goal, the challenge will feature three phases that successively build on each other.

Submissions to this Challenge must be received by 11:59 p.m. UTC, Jan 31, 2024.

Phase Overview

PhaseAnticipated DateDescription
Phase 1 [Find IT!]: Data for Early Prediction (CURRENT)September 2023Find, curate, or contribute data to create representative and open datasets that can be used for early prediction of AD/ADRD.
Phase 2 [Build IT!]: Algorithms and ApproachesSeptember 2024Advance algorithms and analytic approaches for early prediction of AD/ADRD, with an emphasis on explainability of predictions.
Phase 3 [Put IT All Together!]: Proof of Principle DemonstrationMarch 2025Top solvers from Phase 2 demonstrate algorithmic approaches on diverse datasets and share their results at an innovation event.

Prize Overview

PhasePrize Pool
Phase 1 [Find IT!]: Data for Early Prediction of Alzheimer's$200,000
Phase 2 [Build IT!]: Algorithms and Approaches$250,000
Phases 3 [Put IT All Together!]: Proof of Principle Demonstration$200,000
Total$650,000

Source: DrivenData