Prize4Life, Sage Bionetworks and DREAM Launch an Open Science Challenge to Find Clues to Understanding Heterogeneity in Patients with Amyotrophic Lateral Sclerosis (ALS)

June 23, 2015

Prize4Life, Sage Bionetworks and DREAM Launch an Open Science Challenge to Find Clues to Understanding Heterogeneity in Patients with Amyotrophic Lateral Sclerosis (ALS)

SEATTLE–(BUSINESS WIRE)–Today Prize4Life ( in partnership with Sage Bionetworks ( and the DREAM Challenges ( announced the opening of the DREAM ALS Stratification Prize4Life Challenge (!Synapse:syn2873386/wiki/), a global open science data analysis competition geared to develop more personalized approaches for the research, prognosis and treatment of ALS.

Computational DREAM Challenges engage diverse communities of data-focused scientists to competitively solve a specific problem in a given time period by placing scientific data, tools, leaderboards and the resulting predictive models into an open, cloud-based computational workspace — in effect, “crowdsourcing” data analysis.

ALS (amyotrophic lateral sclerosis), also known as Lou Gehrig’s disease, or Motor Neuron Disease, is a fatal, rapidly progressing neurodegenerative disease that leads to paralysis and eventually death. One in 1,000 individuals will live with, and die of, ALS. There is no cure and the average lifespan is 3-5 years.

“How long do I have to live?” “What will the quality of my life be while I live?” For patients with ALS, these are immediate questions because there is currently no way to determine whether someone with ALS will die in 2 years, like baseball great Lou Gehrig (about 90% of those patients diagnosed with ALS), or will live with the disease for up to 50 years, like physicist Stephen Hawking (who has survived longer than almost any other ALS patient). Without an ability to distinguish between patients with very different disease progressions, clinical trial efforts to evaluate potential new ALS treatments end up being expensive and fraught with failure.

The key goal of the DREAM ALS Stratification Prize4Life Challenge (or ALS Stratification Challenge) is to identify the attributes that differentiate ALS patients. Such information will help patients and families plan accordingly to increase their quality of life and will also help guide the development of so-called stratified ALS clinical trials that could enroll specific ALS subgroups for the testing of new treatments.

The ALS Stratification Challenge will run from June to mid-September, 2015, and spur the development of quantitative solutions to stratify ALS patients based on their disease progression or survival.

Prize4Life is providing the largest open ALS clinical trials database in the world (PRO-ACT:, which will serve as the basis for the Challenge. Sage Bionetworks and DREAM have created an engaging set of incentives and a cloud-based Challenge environment — called Synapse ( — where Challenge participants can access and analyze the data, work alone or on teams, submit their quantitative solutions to a leaderboard for scoring against a hidden validation data set and share their ideas, code, and analysis results with others in the Challenge. IBM is donating computational resources for the Challenge and working with Sage Bionetworks to provide a cloud-based environment to empower participants with limited computational power. An exciting technical feature of this Challenge is that participants will submit their open source algorithms in a portable framework to the IBM cloud for scoring. At the end of the Challenge all of the submitted analysis methods will be available on Sage’s Synapse platform as a Challenge library and community resource that can serve as the basis of ongoing research.

The top-performing teams will each receive a $7,000 cash prize, be invited to present the winning model at DREAM’s conference this fall, and have the opportunity to co-author a Challenge overview paper that Nature Biotechnology has expressed interest in considering.

“We believe the ALS Stratification challenge holds great promise to unlock the mysteries of how ALS develops and accelerates the development of ALS treatments and a cure,” says Shay Rishoni, Prize4Life CEO. “We established the PRO-ACT database in 2012 — with the support and partnership of the Northeast ALS Consortium, the ALS Therapy Alliance and, of course, drug companies — exactly for these goals — to bring hundreds of fresh new minds into the world of ALS research. A breakthrough for ALS research will come; we invite the brilliant minds of the computational research community to participate in that victory.”

Prize4Life and DREAM have already demonstrated the power of open Challenges to advance ALS disease research. The ALS Prediction Prize (, conducted in 2012, had over 1,000 registrants from 63 countries, and the winning approaches — described in an article in the November 2014 issue of Nature Biotechnology — outperformed the predictions of more than 12 expert clinicians of ALS, and should make it possible to reduce the costs of future clinical trials by roughly $6 million per trial in part by reducing patient enrollment by up to 20%.

Says Gustavo Stolovitzky, from IBM Research and the Icahn School of Medicine at Mount Sinai: “We are delighted to work again with Prize4Life to organize a follow-up to our previous ALS Prediction DREAM Challenge (!Synapse:syn2826267). In this Challenge, and with a data set that is around 5 times larger than in the first Challenge, we expect to deepen the findings of the first Challenge. Crowdsourcing this powerful dataset and requiring participants to submit their source code to predict patient prognosis advances the Sage and DREAM mission of fostering open and collaborative science while addressing the problem of stratification in this devastating disease.”

A unique component of the ALS Stratification Challenge is the diversity of groups involved. Leading research-based biopharmaceutical companies Biogen and Eli Lilly and Company are helping fund the Challenge effort and providing key advice, and IBM is providing cloud computing. The cash prizes for the Challenge were raised by running a crowdfunding campaign called “Fund the Prize” that ran in Fall, 2014, and succeeded in raising $28,000 for prizes ( In addition to the PRO-ACT Challenge dataset, registry data from the Irish National ALS Register and the Italian Piemonte and Valle d’Aosta Register for ALS will be released mid-Challenge. Finally, the Challenge organizing team includes winners from the earlier ALS Prediction Prize Challenge and the Rheumatoid Arthritis Responder Challenge.

Remarked Liuxia Wang (Principal Scientist of Sentrana, Inc.), who was a top performer in the first ALS Challenge and is now a member of the Challenge organizing team for the ALS Stratification Challenge, “It’s been an honor to be a part of both challenges, first as a participant, and now as a part of the organizing team. When we participated in the first ALS Challenge, we had no idea about ALS, but we did know how to dig into sales data and to sort out meaningful business insights using various statistical/machine learning algorithms. I am glad to help to organize the second Challenge to further understand why some patients progress faster than others. I would encourage all data scientists, no matter if you are in the field of life science or not, to join the mysterious, but rewarding, journey to help to accelerate the cure for ALS.” Wang’s innovative work in the first DREAM ALS Challenge provided the foundation for the launch of a new startup company, Origent Data Sciences. Origent now helps ALS researchers and biopharma companies to accelerate their ALS research and to better analyze and design their ALS clinical trials.

Said Donald R. Johns, M.D., Vice President, Head, ALS Innovation Hub at Biogen. “This is part of our ongoing effort to participate in projects that have the potential to improve our understanding of ALS, and we are hopeful that this effort will provide insights that make future clinical trials more effective and efficient. We are excited to collaborate with Prize4Life, DREAM, and Sage Bionetworks to advance the use of crowdsourcing and big data analysis to help bring understanding and hope to people with ALS.”

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