# Advancing method benchmarking and data sharing through crowd-sourced competitions in cancer research

> **NIH NIH U24** · SAGE BIONETWORKS · 2020 · $853,709

## Abstract

Project Summary/Abstract
Crowd-sourced competitions have transformed biomedical research by incentivizing the coalescence of
communities around timely and difficult problems. These communities have created new standards and
benchmarks, and developed innovative solutions to dozens of pressing research problems. The Dialogue on
Reverse Engineering Assessment and Methods (DREAM) Challenges is a leader in generating communities
through these crowd-sourced competitions. DREAM is an open science, collaborative competition framework
that allows participants from around the world to work together to solve fundamental biomedical questions. Its
vision is to allow open collaboration amongst individuals and groups, maximizing societal impact through the
“wisdom of the crowd”. Over the past 13 years DREAM Challenges have developed key biomarkers and
benchmarks for cancer research, fostering the development of innovative methods, the objective assessment
of tools and algorithms, the development of community standards, and greater access to critical data sets. To
enable the next generation of Challenges, we propose to expand our existing infrastructure into an innovative
platform for rapid, rigorous and scientifically-valid Challenge-based assessments. We propose to create a
Challenge framework that (1) provides a discovery engine for biomedical Challenges and their outputs, (2)
contains innovative tools that enhance and streamline Challenges, and (3) is scaleable and supports
distributed assessments using private and sensitive data. These will be married to a suite of educational tools,
instructions, best-practices guidelines, and workshops and conferences to expand the solver community and
support the organization of independent challenges to maximize impact on biomedical research. Our proposal
will utilize several existing and funded driver Challenges in high-impact cancer domains, encompassing key
biomedical data in imaging, genomics, EHR (structured and unstructured text), and clinical trial data.

## Key facts

- **NIH application ID:** 9952095
- **Project number:** 1U24CA248265-01
- **Recipient organization:** SAGE BIONETWORKS
- **Principal Investigator:** Paul Christopher Boutros
- **Activity code:** U24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $853,709
- **Award type:** 1
- **Project period:** 2020-07-01 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9952095

## Citation

> US National Institutes of Health, RePORTER application 9952095, Advancing method benchmarking and data sharing through crowd-sourced competitions in cancer research (1U24CA248265-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9952095. Licensed CC0.

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