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Hear from our team

Sage Bionetworks is expanding its interdisciplinary team dedicated to advancing the impact of data-driven predictive modeling on human health. Because we believe that research provides the greatest impact when built on a foundation of collaborative relationships and open systems, we work to build and support communities of collaborative researchers. As such, the team at Sage Bionetworks operates as an integrated group of computational biologists, disease biologists, clinicians, and software engineers.

If you enjoy the challenges of designing and implementing new approaches to computational biology, genomics and therapeutic discovery, and like the idea of a dynamic start-up environment, we invite you to explore the career opportunities at Sage Bionetworks.

Sage Bionetworks seeks talented professionals committed to excellence and innovation who can balance interdisciplinary teamwork and individual initiative in a mission-based research environment. We offer a variety of positions including internships and Postdoctoral fellowships.

Sage Bionetworks offers competitive salary packages in an outstanding urban research setting. Benefits include health and disability insurance, a 403(b) retirement plan, relocation, transportation subsidies, and a flexible spending plan.

For general inquiries regarding careers at Sage Bionetworks contact us

For current positions view the job descriptions below.

Find out more about Sage Bionetworks and living in Seattle

 

Current Positions

Technology Platforms and Services
At Sage Bionetworks we are working on the tools and platforms required to gather, share and use biomedical data in novel ways. These are targeted both at the research community, as well as organizations and individual who are involved in providing data and being involved in the research process. They range from the technology platforms Synapse and BRIDGE, through novel methods of addressing governance issues around the distribution of human data such as Portable Legal Consent, to the ability to run Challenges to solve data-driven questions through our partnership with DREAM.
Platforms and Services

Data Science
The Data Science group works with data integration and develops analysis pipelines for genomic scale research. Much of our effort is dedicated to enabling and assisting large scale research consortia that span multiple institutions where we solve hard data integration problems in order to promote collaborative research. We focus on developing general purpose tools and techniques that will allow research to be reproducible and reusable by leveraging our in house technology platform.

Research Operations
The Research Operations group sits at the intersection of research, patient/citizen engagement and technology. It supports the scientific and strategic initiatives of the organization, and develops robust data protection policies and procedures for open research and collaborations.

Systems Biology
The Systems Biology research group at Sage Bionetworks is working to understand the underlying mechanisms causal to common disease. We use large-scale genomic analysis to identify disease subclasses, generate diagnostic and prognostic biomarkers, and to identify pathophysiology causal to disease in collaboration with academic and industry partners. Our current portfolio is focused on neurobiology, spanning both neurodegenerative and neuropsychiatric disorders, and includes projects in other disease areas including immunology, metabolic disease and craniofacial deformation.
Highlights in Neurobiology Projects

Computational Biology
The Computational Biology group focuses on developing integrative probabilistic models for prediction of disease phenotypes and validating of hypotheses generated by novel methodologies. Currently opportunities include: positions in Oncology focused on conducting original research in analyzing large-scale high dimensional genomics data to develop predictive models of cancer phenotypes. Positions in collaboration with the recently merged Sage/DREAM effort, focused on designing and implementing crowd-sourced collaborative challenges around cancer phenotype prediction problems. Positions in stem cell bioinformatics with a focus on development of the data and analysis bioinformatics portal for the Progenitor Cell Biology Consortium, as well as research projects on modeling molecular mechanisms underlying stem cell differentiation.

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BRIDGE: Patients as Research Partners

Biomedical research needs to shift and proceed with the sense of urgency that each of us experiences when we become patients. And it needs to empower patients with the voice and the tools they need to manage their health, understand their disease and contribute to research. The BRIDGE platform and its first pilot community projects will give us successes and lessons that help us understand (1) how to bring the open-source movement to medical discovery, (2) how to activate citizen-patients for participation in medical research, and (3) how to incentivize scientists to share their data and disease models to accelerate biomedical discovery.

To spur new medical discoveries we must transform the way research is conducted, drawing on the wisdom and insights of patients and their families—the people most familiar with disease—and the data they can now collect about their health.

The past few decades have seen the emergence of affordable genomics, sensors, mobile phone cameras and apps and online tools that for the first time allow each of us to collect data on ourselves precisely and frequently. If we can invest in systems that make it possible to correlate all the insights and data that people can now collect on themselves with the clinical data our doctors collect, we can for the first time generate integrated natural history timelines of individual health and disease that can power transformational research.

Toward this goal, Sage Bionetworks, with support from the Robert Wood Johnson Foundation’s Pioneeer Portfolio is building BRIDGE a web-based, open-source platform that will allow patients to provide their data and insights as research partners on the health problems that matter most to them.

On BRIDGE, citizens, patients and researchers will be able to use online tools that connect people, their data and their stories to build communities focused on defining the research question that matters most to patients and their families. Participants will be able to use BRIDGE’s consent tools and data portal to contribute their health data into open research projects such as those that Sage Bionetworks is enabling with its Synapse data repository and collaborative work space. The insights that come from the data will then be reported back on BRIDGE and also drive new rounds of research collaborations.

To shape BRIDGE’s development, Sage Bionetworks is collaborating with three health communities that each have unique use cases for the BRIDGE functionalities they need to run their own patient-partnered studies. These studies focus on Fanconi anemia (a rare inherited blood disorder), sleeping disorders and Type 2 Diabetes.

The Fanconi Anemia BRIDGE Study: creating 21st century approaches for FA people and their families to monitor their own health and for FA researchers to develop a better understanding of the biology surrounding key events in disease progression.

The Sleep Disorders BRIDGE Study: crowdsourcing a deeper understanding by and for the public using a mobile phone sleep app that will allow researchers to correlate sleep patterns with responses to available sleep medications.

The Type 2 Diabetes BRIDGE Study: understanding how a patient’s disease biology, decision-making, lifestyle are inter-connected to affect disease outcome.

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Today, Sage Bionetworks and DREAM opened three new DREAM Challenges.

The three launches are the Alzheimer’s Disease Big Data DREAM Challenge #1, the Broad-DREAM Gene Essentiality Prediction Challenge, and the DREAM9 Acute Myeloid Leukemia (AML) Outcome Prediction Challenge.

These Challenges tackle important questions related to Alzheimer’s Disease, cancer genomics and acute myeloid leukemia (AML). Help us journey forward as we strive to maintain DREAM’s high level of excellence in translational systems biology while also welcoming new DREAMers to our community who can help us innovate and extend the wisdom of the crowds into new arenas of human health.

This DREAM9 “Challenge season” will conclude with final Challenge submissions due in mid-September, 2014. Best performers from the AD#1 DREAM8.5 Challenge will be invited to present their results at the International Biomedical Commons Congress, to be held in Paris in April 2015. Best performers from the two DREAM9 Challenges will be invited to present their results at the DREAM track of the RECOMB/ISCB Systems and Regulatory Genomics/DREAM Conference, to be held in San Diego, California November 10-14, 2014.

As we have done in previous Challenges, best performer teams will also be invited to co-author a Challenge-specific paper for submission to a scientific journal

To read details of the challenge, register and get started, please click on a link below:

Alzheimer’s Disease Big Data DREAM Challenge #1 (delayed DREAM8.5 Challenge):
Predict the best biomarkers for early AD-related cognitive decline and for the mismatch between high amyloid levels and cognitive decline.

The Broad-DREAM Gene Essentiality Prediction Challenge
Develop predictive models to infer genes that are essential to cancer cell viability using gene expression and/or gene copy number features.

The DREAM9 Acute Myeloid Leukemia (AML) Outcome Prediction Challenge (open for registration only: data access available TBA)
Predict the outcome of treatment of AML patients (resistant or remission), their remission duration and overall survival based on clinical cytogentics, known genetics markers and phosphoproteomic data.

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The Resilience Project is a joint collaboration between the Icahn School of Medicine at Mount Sinai and Sage Bionetworks.

Watch Stephen Friend’s TED Talk on the Resilience Project, and read his Perspective in Science Magazine (written with Eric Schadt), both released today. You can visit the Resilience Project website today to sign up for enrollment in the study later this summer.

Most current efforts to develop new therapies start with people who are sick and hardly ever result in new cures. In the Resilience Project, we will organize a worldwide search to find healthy adults that carry genetic mutations for severe forms of childhood disease yet, remarkably, do not show any signs of illness. These rare individuals are “unexpected heroes” because they hold answers — in the form of buffering mutations or environmental factors — that can help us to better understand the biology of disease, and accelerate the development of preventive approaches for these severe childhood diseases. Our hope is to discover the specific factor(s) that make these people resilient and untouched by the catastrophic illness that their DNA says they should have.

The Icahn School of Medicine at Mount Sinai and Sage Bionetworks will coordinate this multi-year, multi-partner open research project through thorough sampling, validation and deciphering phases. Mount Sinai will function as a central generator of the analyses to identify the unexpected heroes. The de-identified data collected at all stages of this project will be made available for open research by hosting it on Synapse, Sage Bionetworks’ compute platform to support open, collaborative data analysis.

In the sampling phase of the project, our aim is to enroll and consent one million healthy individuals over 40 years of age from diverse communities and locations across the globe. To maximize the number of un-expected heroes we identify within this broad search, we will apply two important strategies. First we believe that a rich source of unexpected heroes will be in the extended families and consanguineous populations that are known to have carriers of a particular genetic mutation who have become sick with the disease. Therefore, in addition to a non-targeted recruitment of healthy individuals, we will recruit healthy members of these two groups into the study. Second, with the cost of high throughput genetic screens falling rapidly, we are not limited to testing one million samples against only one gene at a time. Instead, we will screen samples simultaneously against 685 genetic mutations that are known to be causative for one of 127 severe childhood disorders.

Once samples are collected, Mount Sinai and individual disease community data production partners will process samples using the genetic screen described above. When test results find an unexpected hero, we will obtain assistance from clinical genetics experts from around the world who have expertise in the given disease and can assist our data production partners with the validation of the initial unexpected hero result. For validation, we will need to re-contact unexpected heroes to obtain their agreement for the validation and follow-up studies: based on previous experience with genetic testing, we expect that more than half of the identified unexpected heroes will want to proceed with the follow up work in order to learn more about why they are healthy and resilient in spite of being a genetic carrier of a genetic mutation that normally causes disease at an early age.

Since we expect to identify and validate no more than several hundred unexpected heroes that carry specific disease mutations from the one million individuals tested, we cannot rely upon the power of statistics to guide us in our deciphering efforts. But we can follow in the footsteps of recent studies that successfully identified rare variant “positive outlier” mutations in cancer patients. These approaches focus on the restricted pool of positively validated mutations in the identified unexpected heroes and interrogate each one of them to elucidate network biology and investigate environmental factors.

For this deciphering phase of the project, Sage Bionetworks will help coordinate information and data flow with researchers at the institutions listed below. We anticipate that these researchers will want to participate as one of many distributed teams of experts that are all working in an open sharing collaborative manner where real-time data are available on Synapse (www.synapse.org) for many to co-investigate.

Below are some representative examples of Centers that have expressed an interest to help decipher the source of resilience for each of the validated unexpected heroes:

Icahn School of Medicine at Mount Sinai: data generation and deciphering
Sanger Center: genetic deciphering in human stem cells
University of Lausanne: genetic deciphering in mouse models
University of Alabama: genetic deciphering in yeast models
Nestle’s (Switzerland): non-genetic deciphering testing
National Institute of Environmental Health Science: non-genetic deciphering testing

We believe that inverting the traditional disease study to instead study the wellness of individuals whose genetics indicates they should be sick has important implications. First, by learning what genetic or environmental factors buffer against severe genetic disease, we start to decode the biology of what prevents diseases from occurring in the first place. Second, if successful, we expect this effort will accelerate research by identifying genetic and non-genetic factors that are the source of resilience and represent novel approaches for preventive therapeutics. Third, by demonstrating that we can identify the sources of buffering that allow carriers of genetic mutations for severe childhood disorders to stay healthy into their 40’s, we provide hope that similar resilience approaches could be applied to other disease such as inherited forms of cancer and Alzheimer’s disease.

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“The way biomedical research is carried out is changing fundamentally,” Sage Bionetworks President Stephen Friend declared at the beginning of a webinar about the crowdsourced computational challenges Sage is facilitating in partnership with the DREAM (Dialogue for Reverse Engineering Assessment and Methods) project that originated at IBM. Friend laid out five opportunities he believes are giving rise to new ways to generate, analyze, and support new research models:

- It’s now possible to generate massive amounts of human “omic’s” data.
- Network modeling approaches for diseases are emerging.
- Information technology infrastructure and cloud computing capacity allow an open approach to biomedical problem solving.
- There’s an emerging movement for patients to control their own sensitive information, allowing sharing.
- Open social media allows citizens and experts to use gaming to solve problems.

“The usual rule of anointed experts being the only ones who can solve problems has really been shattered,” said Friend.

For several years, Sage has been grappling with how to bring about a better understanding of the complexity of biology, given these trends. One initiative central to their efforts has been the creation of a technology platform for data sharing and analysis called Synapse, built on the model of “github” from the open-source software world, which allows distributed projects to get done and provides the foundation for running the DREAM Challenges.

Friend noted that computational biology has been driven by crowdsourcing for a long time, and challenges like those that DREAM has been running for many years have been integral to its successes. There are increasingly large and powerful sets of data in the public domain, and putting them out for many people to look at (some of them from outside the field of biology) and make predictions and unbiased evaluations based on the data is critical to solving complex problems in biology in this day and age. Data is getting so complex that it’s impossible for any single researcher or institution to analyze it effectively. As John Wilbanks, Sage’s Chief Commons Officer and a FasterCures Senior Fellow, noted, “One of the hardest things to do in the emerging Big Data world is to get your data analyzed.”

An important aim of these challenges is to foster a new culture in research. As Friend argues, “We have a serious need not just to solve specific problems, but … to build communities so that people begin to think of each other as colleagues and collaborators.” DREAM Challenges are carefully constructed to provide opportunities for publications in journals and for other forms of recognition that are important to researchers, often more important than the promise of a monetary prize.

First of the four past challenges run by Sage and DREAM (along with partners from academia, industry, government, and patient groups) was the Breast Cancer Prognosis Challenge, created to forge a computational model that accurately predicts breast cancer survival. The winning team was from the academic lab that invented the MP3 format for digital audio, bringing their expertise in data compression to the task. Hundreds of teams comprised of thousands of individuals have participated, and a number of publications have resulted, along with other opportunities for professional advancement for “solvers.”

Challenges currently open include:

- The Somatic Mutation Calling Challenge, to predict cancer-associated mutations from whole-genomic sequencing data;
- The Rheumatoid Arthritis Responder Challenge (in partnership with the Arthritis Foundation, among others), to predict which patients will not respond to anti-TNF therapy – a clinical trial could follow if a powerful classifier emerges from the Challenge for validation; and
- The Alzheimer’s Disease Big Data Challenge, which seeks to predict early AD-related cognitive decline and the mismatch between high amyloid levels and cognitive decline. Massive amounts of data in the public domain has been aggregated, collated, massaged and curated for the task.

Two more are set to open this summer, in partnership with the Broad Institute and MD Anderson Cancer Center, and several more are being considered for launch by the end of 2014. All stakeholders – including and perhaps especially patient groups – are invited to participate by proposing ideas for challenges, contributing data, recruiting teams to participate. The Sage-DREAM Challenges are looking for partners who want not only to find the answers to tough questions in their fields, but who want to help create the conditions for the real collaboration necessary to bring about “the next generation of biomedical research.”

For more information on how to get involved with an open DREAM Challenge, click here.

View webinar slides and recording

(Cross posted from http://fastercures.tumblr.com/post/81603549119/crowdsourcing-data-challenges-to-speed-the-search-for and written by Gillian Parrish)

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Sage Bionetworks CEO spoke from the main stage yesterday at TED 2014 in Vancouver. He announced the Resilience Project, a new collaboration between us and Mt Sinai that is looking for healthy individuals who carry genetic mutations that should have made them ill as children.

The project is searching for rare genetic mutations that should have cause catastrophic illness. Somehow certain individuals are “resilient” – they have been protected via genetic or environmental factors. Our calculations indicate that 1 in 15,000 people is resilient in some form. It’s simply been too expensive to find them until now.

Thanks to incredible support from 23andme, Children’s Hospital of Philadelphia, Lund University, and the Beijing Genomics Institute, we’ve already begun profiling hundreds of thousands of individual samples and re-analyzing data sets. Candidates for resilience are already emerging from that analysis.

In the coming weeks, we’ll open the project for large-scale public enrollment with electronic consent and more. Sign up to be notified when we launch at resilienceproject.me.

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John Wilbanks, our Chief Commons Officer, was recently part of the NPR TED Radio Hour talking about the biomedical research commons we are building here at Sage Bionetworks.

The show was based around the idea of the “End of Privacy” – featuring experts in security, open government, and more. Wilbanks’ piece features his TED Talk and explores whether the desire to protect privacy is slowing research, and if opening up medical data could create a wave of health care innovation.

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We, along with the rest of the biotech world, were thrilled when the NIH announced recently the Accelerating Medicines Partnership (AMP).

AMP is a partnership between the NIH, 10 biopharmaceutical companies, and several non-profit organizations that builds on pioneering work done at Sage Bionetworks and the Structural Genomics Consortium on the Arch2POCM project (which is also driving novel cancer study models in Canada). AMP promises to “transform the model for developing new diagnostics and treatments by jointly identifying and validating promising biological targets of disease” – working collaboratively in the early phases, rather than individually.

AMP will begin with three to five year pilot projects in three disease areas:

- Alzheimer’s disease
- Type 2 diabetes
- Autoimmune disorders of rheumatoid arthritis and systemic lupus erythematosus (lupus)

And we couldn’t be happier to announce as part of the AMP-Alzheimers project, Sage Bionetworks will provide the data enablement for network analysis projects consisted of across-projects data integration and rapid sharing of data and analytical tools. We’re excited to see what our work in compute platforms, data governance, and patient engagement can do inside this promising and exciting new initiative. Stay tuned for more news!

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Our president, Stephen Friend, joined a lively panel at the FasterCures 2013 conference earlier this month. The panel took on the question of failure in science, and its impacts on patients, during a session on “Learning to Love Failure,” moderated by Luke Timmerman, vice president of life sciences initiatives at Xconomy. Timmerman set the stage by saying that within “biomedical research, failure is the norm. But there is no culture talking about it.”

Dr Friend criticized the current scientific process as one that catalyzes failure because there is no way to learn from others. “Our understanding of disease is based on narrow or generalized knowledge. Just one finding is not enough.” He added that there needs to be a cultural change in science where scientific results are completely shared. “Good research shouldn’t have to always be a positive result. Negative results should also be reported.”

Watch the whole panel here:

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We are pleased to announce the final results for the DREAM 8 Challenges. During the “Challenge season” that spanned June 10, 2013 to mid-September, 2013, Sage Bionetworks and DREAM ran three DREAM 8 Challenges linked below. More than 600 individuals signed up for the Challenges and in aggregate built and submitted >1000 predictive models across the three Challenges in a timespan of roughly three months. The top performing teams presented their winning models at the November 8, 2013 DREAM Conference.

Go check out the winners for each of the challenges:
HPN-DREAM Breast Cancer Network Inference Challenge
, NIEHS-NCATS-UNC DREAM Toxicogenetics Challenge, and the Whole-Cell Parameter Estimation DREAM Challenge.

We are also very very excited to announce three new DREAM 8.5 challenges. Best performers in all DREAM 8.5 Challenges will be invited to present at the 2014 DREAM conference (date and location to be determined) with travel expenses covered by the organizers. We are also working to establish publishing partners for each of these challenges. The DREAM 8.5 Challenges are now open for registration, and will begin active problem-solving in late 2013 or early 2014.

This round of challenges include the first Alzheimer’s Disease Big Data DREAM Challenge, the ICGC-TCGA-DREAM Somatic Mutation Calling Challenge, and the Rheumatoid Arthritis Responder Challenge.