Notice Number: NOT-HL-20-758
Release Date: March 24, 2020
National Heart, Lung, and Blood Institute (NHLBI)
The National Heart, Lung, and Blood Institute (NHLBI), part of the National Institutes of Health (NIH), invites novel Solutions for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research. The goal of the challenge is to foster innovation in computational analysis and machine learning approaches utilizing large-scale NHLBI-funded datasets to identify new paradigms in heart failure research. The challenge aims to address the need for new open source disease models that can define sub-categorizations of adult heart failure to serve as a springboard for new research hypotheses and tool development in areas of heart failure research from basic to clinical settings.
Adult heart failure is a chronic, progressive disorder in which the heart is unable to efficiently pump blood, and more than 6.5 million Americans suffer from this condition. It is currently often categorized by a single metric – left ventricular ejection fraction – but is known to be a multi-organ, systemic syndrome with many related but seemingly disparate phenotypes. Additionally, social, behavioral, environmental, and genetic determinants often captured in study data have a considerable influence on outcome but are not well-understood. The field of heart failure research currently lacks a systematic framework that incorporates these many factors in a comprehensive disease model. An adult heart failure sub-phenotyping scheme incorporating many disease-associated factors would provide a new paradigm that will benefit investigations into the mechanism of disease, diagnosis, and, ultimately, prevention and treatment.
The NHLBI seeks to foster such paradigm shifts in heart failure research by awarding innovative Solutions that utilize existing large health datasets. NHLBI has a history of making considerable investments in the creation of deep data resources including: long-standing, deeply-phenotyped epidemiological cohorts, innovative clinical trials, and large-scale precision medicine efforts that have generated whole genome sequencing and “other omics” data for more than one-hundred thousand individuals. Many of these and other data are publicly accessible via the Database for Genotypes and Phenotypes (dbGaP) and the Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). The NHLBI Heart Failure Big Data Analysis Challenge webpage provides further details about available open- and controlled-access NHLBI-funded datasets and data access resources.
With these datasets in hand, the NHLBI is seeking to promote the application of computational analysis and machine learning approaches to create opportunities for hypothesis generation and research tool development for heart failure research. This challenge aims to reward innovative, computational Solutions utilizing large health datasets to develop a schema for the sub-phenotyping of adult heart failure that facilitates basic and/or clinical heart failure research objectives. A successful adult heart failure sub-phenotyping Solution will be a novel, pragmatic, accessible research tool for a spectrum of heart failure researchers. Successful Solutions will also be free and openly available to the research community. Participants are strongly encouraged to take advantage of NHLBI-funded datasets in the development of their Solution and are also welcome to bring other relevant data to their analyses.
The NHLBI is conducting this Challenge under the America Creating Opportunities to Meaningfully Promote Excellence in Technology, Education, and Science (COMPETES) Reauthorization Act of 2010, as amended [15 U.S.C. § 3719].
NHLBI will award up to a total of $250,000. Up to five (5) winners will be selected, with each winning up to $50,000. NHLBI will advertise the results of the competition and publicly display the winning Solutions. Winning participants may be invited to present their Solutions at an NHLBI-hosted scientific symposium.
Please direct all inquiries to:
For more information, including on how to enter, please visit the NHLBI Heart Failure Big Data Analysis Challenge webpage.