Global Genes’ RARE-X Names Winners of Xcelerate RARE Open Science Data Challenge

October 6, 2023

The Open Science Data Challenge launched for researchers on May 31, and focuses on rare pediatric neurodevelopmental diseases. Thousands of researchers worldwide – clinician-researchers, basic science researchers, and data scientists – participated in the inaugural challenge. The winners of the challenge were announced during the 2023 RARE Advocacy Summit in San Diego, California on September 20.

The Challenge, which closed August 16, was designed to generate new insights into these conditions and allow participants to test hypotheses for fueling therapeutic development by leveraging the growing amount of patient data on Global Genes’ RARE-X platform. Participants made use of de-identified data on the RARE-X platform, as well as electronic health record data curated by Ciitizen, and external registry data provided by the Coordination of Rare Diseases at Sanford (CoRDS). 

Global Genes invited participating researchers to address three challenge questions. The first question focused on expanding known phenotypes with previously unrecognized symptoms. Global Genes named three winners for the first challenge question, including:

  • Best approach, combining RARE-X & external data:  3Billion Team, led by Won Chan Jeong, Bioinformatics Engineer and Kyoungyeul Lee, Chief Scientific Officer; at 3Billion, Seoul, South Korea
  • Best open source method to benefit rare disease research: Chong Lab team, led by Jessica Chong, Ph.D., Assistant Professor in Pediatrics at the University of Washington, Seattle
  • Most innovative approach to analysis of patient reported data: Systems Biomedicine Team at Marseille Medical Genetics, led by Anaïs Baudot, Ph.D., CNRS Director of Research

The second challenge question involved creating machine learning algorithms to predict disease diagnoses based on the diagnostic journey documented by families providing data. Global Genes named the following team as the winner of this challenge:

  • Best computational approach for predicting a diagnosis based on patient-reported data: Ambit Inc.’s Data and Analytics Team led by Birnur Ozbas-Erdem, Ph.D., Vice President and Head of Analytics and Data Products at Ambit Inc.

The third challenge question focused on using data to validate or refute a potential therapeutic approach for one or more rare diseases. Global Genes announced two winners of this challenge:

  • Best use of the RARE-X data set: Mefford Lab at St. Jude Children’s Research Hospital, led by Heather C. Mefford, M.D., Ph.D., Principal Investigator at St. Jude Children’s Research Hospital
  • Most novel approach for potential therapeutic research: Guan Lab at the University of Michigan, led by Yuanfang Guan, Ph.D., Associate Professor in the Department of Computational Medicine & Bioinformatics at the University of Michigan

Roche served as founding partner and co-organizer of the Xcelerate Rare Challenge. Sponsors included Datavant, Horizon, and RTW Charitable Foundation. Xcelerate Rare data partners included Ciitizen, Sanford Health, and NetraMark. Global Genes also worked with Dream Challenge through the nonprofit Sage Bionetworks to craft the challenge questions and create a dedicated workspace.

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