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.
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.
Phase Overview
Phase | Anticipated Date | Description |
---|---|---|
Phase 1 [Find IT!]: Data for Early Prediction | September 2023 | Find, 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 Approaches | October 2024 | Advance 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 Demonstration | April 2025 | Top solvers from Phase 2 demonstrate algorithmic approaches on diverse datasets and share their results at an innovation event. |
Prize Overview
Phase | Prize Pool |
---|---|
Phase 1 [Find IT!]: Data for Early Prediction | $200,000 |
Phase 2 [Build IT!]: Algorithms and Approaches | $260,000* |
Phases 3 [Put IT All Together!]: Proof of Principle Demonstration | $200,000 |
Total | $650,000 |
- UPDATE September 2024: The Phase 2 prize pool has been increased by $10,000 The increase is reallocated prize moneys that were not awarded in Phase 1, and the total pool of prize awards for the Challenge remains $650,000.
The competitions
Data for Early Prediction (Phase 1)
Find, curate, or contribute data to help the National Institute of Aging, a center of the National Institute of Health, create representative and open datasets that can be used for the early prediction of Alzheimer's disease and related dementias. #health