The winners of the DREAM ALS Stratification Prize4Life Challenge were recently announced by Prize4Life, Sage Bionetworks and the DREAM community. The challenge is a global data analysis competition designed to computationally determine the different subgroups of patients who suffer from amyotrophic lateral sclerosis (ALS). There is currently no method to identify whether a given ALS patient will survive the average three to five years after diagnosis, or be among those who go on to live for decades.
The purpose of this competition is to find answers for clinical practice and new trial designs, as well as personalized approaches for drug development. “We want to accelerate ALS drug discovery and believe that critical breakthroughs will come from new ways of thinking, collaborating, and sourcing ideas,” Prize4Life CEO Shay Rishoni said in a press release.
The participants were able to compete individually or in teams, and their projects were included in four different challenge categories. “I’m excited by the results of the ALS Stratification Challenge and congratulate the winners who significantly outperformed the bar,” added Rishoni. The winners were granted a total of $28,000 to be invested in their research and are going to present their work at the DREAM Conference on Regulatory and Systems Genomics meeting, set for Nov. 16-18, 2015, in Philadelphia, Pennsylvania. In addition, they also have the opportunity to co-author a Challenge overview paper, partnered by the journal Nature Biotechnology.
The winners included researchers from the Department of Computer Science and Information Engineering at the National Cheng Kung University, Taiwan; researchers from the Center for Biophysics and Quantitative Biology at the University of Illinois at Urbana-Champaign, USA; and researchers from the Department for Computational Medicine and Bioinformatics at the University of Michigan, USA.
The participating teams worked on cloud-based computational resources, which were donated by IBM, one of the sponsors of the competition. The participants submitted their source code to predict patient prognosis and, by the end of the competition, all of the methods submitted were inserted onto Sage’s Synapse platform, which will work as a library and community resource that can also serve as a basis for ongoing research.
“We are committed to finding answers to ALS and dedicated to supporting new approaches like crowdsourcing and big data analysis that have the potential to provide powerful insights into the disease,” said Donald R. Johns, MD, Vice President, ALS Development at Biogen, one of the sponsors of the challenge. “We are grateful to the participants of the DREAM ALS Stratification Prize4Life Challenge who have created new knowledge and an important repository for research that may bring improved trials, new treatments, and hope to ALS patients.”
Stephen Friend, President, Co-Founder, and Director of Sage Bionetworks, also thanked the participants of the DREAM ALS Stratification Prize4Life Challenge, and stated, “ALS is a variable disease and the speed of progression is different from person to person. Through our community-based approach, our participants were able to mine the largest ALS clinical trials and registry databases and produce promising computational models to find patterns and identify subgroups of ALS patients.”
The ALS Stratification Challenge is considered original in its definition and in its diversity of participants and sponsors, which included Eli Lilly and Company in addition to Biogen and IBM. The $28,000 financial award was raised through a crowdfunding campaign called “Fund the Prize” conducted last winter. The basis for the challenge was the largest open-access ALS clinical trial database in the world, provided by Prize4Life and developed together with NEALS and MGH, along with national ALS registries from Ireland and Italy.
“The Challenge winners and participant community will help deepen our understanding of ALS, a devastating and complicated disease,” said Gustavo Stolovitzky, DREAM founder from IBM Research and the Icahn School of Medicine at Mount Sinai. “Crowdsourcing a powerful dataset and having participants submit their source code to predict patient prognosis has advanced the Sage Bionetworks’ and DREAM’s mission of fostering open and collaborative science while addressing the problem of stratification in ALS.”
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