By Allissa Dillman

July 15, 2026 | The 2026 Bio-IT FAIR Data Hackathon kicked-off the 25th Bio-IT World Conference & Expo by welcoming 32 data scientists, software developers, students, and life science professionals to address real-world data challenges using Open Source and FAIR (Findable, Accessible, Interoperable, Reusable) data principles. On May 18–19, 2026, the six teams convened to deliver projects that leveraged NIH Common Fund Data Ecosystem (CFDE) omics data and integrated CFDE tools to delve into themes like drug repurposing, exercise memetics, discovery, interpretable cancer prognostics, drug side effects, post-translational modification discovery, and exercise disease counteraction.  

The CFDE Training Center hosted the hackathon to unite diverse members of the scientific community for open science and data-driven discovery and to promote available CFDE datasets, tools, and resources. Attendees participated to share their expertise and lean into the expertise of others, to learn more about resources CFDE has to offer, and to build new relationships to collaborate across a wide range of fields. By the time the clock ran out, the participants had built innovative solutions to strengthen the research community.  

This year the teams were awarded $15,000 in prizes based on project outcomes to improve interoperability between CFDE and external datasets, tools, and platforms. All team projects can be accessed through the GitHub organization https://github.com/BioITHackathons and their specific Hackathon repositories are: 

1. Drug Repurposing Through Disease Similarity Analysis Using BiomarkerKB with other CFDE Resources and Tools 
   
2. Exercise Mimetics Discovery via Gene Set Foundation Models and CFDE Data Integration 
   
3. Mining the CFDE for Post-Translational Modification Secrets 
   
4. CFDE Data-driven Knowledge Discovery to Illuminate the Molecular Basis of Drug Side Effects 
   
5. **Exercise as Medicine: Identifying Molecular Signatures that Oppose Disease in Rat Multi-Omics Data  
   
6. Visible Neural Networks for Drug Response in Cancer (CellMap-VNN)  

** Links for these projects are currently private.  

Team members took to social media to highlight their work and experience: 

“This was one of the most technically and biologically rich projects I've worked on. Bridging ML engineering with systems biology in 48 hours with an incredible team is something I won't forget.” 

“The FAIR challenge wasn't just technical - it pushed us to think carefully about gene identifier harmonization across databases, reproducible pipeline design, and making results genuinely reusable across disease contexts. This experience expanded my perspective on how open data ecosystems, when combined with thoughtful engineering, can accelerate scientific discovery. It also reinforced skills I care about: building modular pipelines, integrating heterogeneous data sources, and delivering something that others can actually use and extend.” 

Those interested in learning more about CFDE Training Center events can send SUBSCRIBE to [email protected] to receive the event newsletter. 

The Common Fund Data Ecosystem (CFDE) Training Center is managed by ORAU, a 501(c) not for profit corporation, in coordination with BioData Sage LLC. The CFDE TC is supported in whole by the National Institutes of Health (NIH) Common Fund under award 1OT2OD037922-01.   

This Hackathon report was written by the Hackathon Organizing Team and is solely the responsibility of CFDE TC and does not necessarily represent the official views of the National Institutes of Health.