Data Challenges
Our data challenges are designed to generate insights in the immediate term and to attract researchers to Alzheimer’s disease and related dementias in the medium and long term.
Data Challenges provide a mechanism to engage with a global community of researchers and data scientists and offer an opportunity to harness their expertise, insights, and potentially some “outside of the box” thinking and approaches. We always strive to draw in expertise from across the scientific community – including outside of the Alzheimer’s and related dementias field, where our aim is to keep them involved in our mission and goals.
The AD Workbench's collaborative workspaces allow us to promote data sharing and open science through the challenges we host — with the goal of addressing important questions, sharing results, and making the code developed to uncover new insights available to the community.
Current Challenges
Global Neurodegeneration Proteomics Consortium Data Challenge
We're helping accelerate biomarker discovery in Alzheimer’s and related dementias, using the Global Neurodegeneration Proteomics Consortium (GNPC) Harmonized Data Set—the world’s largest neurodegeneration proteomics resource—to generate insights that could improve detection, prognosis, and treatment pathways.
The submission process closed in January 2026. Decisions will be announced in Spring 2026.
Past Challenges and Hackathons
2025 Bio-Hermes Biomarker Data Challenge
The Bio-Hermes Biomarker Data Challenge was open to academic researchers based in the UK. Challenge participants demonstrated that scalable, non-invasive approaches can achieve clinically meaningful detection and risk stratification for Alzheimer’s disease. Across analyses, multimodal models integrating blood biomarkers (particularly pTau217), cognitive testing, and functional measures outperform single-modality approaches and, in some cases, exceed the performance of PET imaging alone. Functional independence as captured through extended activities of daily living emerged as a critical component of clinically useful risk prediction. Together, the findings support a shift toward accessible, blood-based, and behaviorally informed tools to enable earlier, more equitable identification of Alzheimer’s disease across diverse populations.
2022 NTK Hackathon
The AD Data Initiative NTK Hackathon was open to researchers, biostatisticians, data scientists, and other experts interested in attempting to improve our understanding of the early indicators of neurological disease using the NTK App and other robust analysis tools on the AD Workbench.
2021 Alzheimer's Detection Challenge
The AD Data Initiative Alzheimer’s Detection Challenge aimed to build an automated algorithm that classifies a patient’s phase of Alzheimer’s disease (AD) based on a common cognitive screening tool for dementia—the Clock Drawing Test (CDT). The result was shared with AD Workbench users to expand the existing suite of analytics for the benefit of the user community and the advancement of AD research.
