SAGE BIONETWORKS
2901 Third Ave Ste 330, Seattle, WA 98121 www.sagebionetworks.org

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Organizations Filed Purposes: Sage Bionetworks is a strategic research organization with a mission to coordinate and link academic and commercial biomedical researchers, patients and citizens through a Commons that represents a new paradigm for genomics intellectual property, researcher cooperation and contributor evolved resources. This mission has several interdependent themes, including: conducting research on network models of disease; building the computational platform for the Commons; and activating public engagement. Sage Bionetworks is a non-profit research organization that seeks to develop predictors of disease and accelerate health research through the creation of open systems, incentives, and standards. We create strategies and platforms that empower researchers to share and interpret data on a colossal scale, crowdsource tests for new hypotheses, and contribute to knowledge through community challenges.

Sage Bionetworks is a strategic research organization with a mission to coordinate and link academic and commercial biomedical researchers, patients and citizens through a Commons that represents a new paradigm for genomics intellectual property, researcher cooperation and contributor evolved resources. This mission has several interdependent themes, including: conducting research on network models of disease; building the computational platform for the Commons; and activating public engagement.

Research Communities and Challenges: Sage Bionetworks conducts research independently as well as with collaborators worldwide across a variety of disease areas. We work to redefine how complex biological data is gathered, shared and used through open systems, incentives, and norms. Our work includes the building of platforms and services and undertaking research developing predictors relating to health. Research: As biological research has become more data intensive, the breadth of data and expertise required to address research problems has expanded. It requires the integrated efforts of a distributed set of researchers (such as bench/data scientists, data engineers, project managers, administrators, governance experts, and clinical researchers) with shared interests and complementary resources. Effective collaboration depends on a collective ability to work together in trusted ways that lead to translatable biomedical insights. We call this scientific coordination. Sage's scientific coordination stack includes: 1) hypothesis and data generation, 2) data curation, 3) analysis, 4) interpretation, and 5) dissemination. We focus on building a federated network of individuals who bring diverse expertise and approaches to develop robust solutions. New research projects initiated in 2019 included: TREAT-AD - Funded by the NIA to build a diverse portfolio of new therapeutic and diagnostic targets for Alzheimer's disease (AD). Ongoing research communities included: Agora - Funded by the NIA, Agora is a platform that enables researchers to access information about how genes are associated with Alzheimer's disease. It aggregates lines of biological evidence from multiple sources, so researchers can better prioritize which genes they want to follow up on for development of new therapies. All of Us - A program to engage over one million participants in a study to improve the ability to prevent and treat disease based on individual differences in lifestyle, environment and genetics. CD2H (National Center for Data to Health) - With aims to foster collaboration across more than 50 premier medical research institutions within the prestigious Clinical and Translational Science Awards, or CTSA, network. Cancer Systems Biology Consortium (CSBC) - Sage serves as the Coordinating Center for the CSBC and Physical Sciences in Oncology Network (PS-ON) program. This five-year award builds on the work of the NCI funded Sage Bionetworks' Center for Cancer Systems Biology from 2010 through 2015. Human Tumor Atlas Network (HTAN) - Funded by NCI, Sage is the data coordinating center for HTAN which aims to leverage the power of human genome sequencing and other state-of-the-art profiling technologies, to analyze changes in individual tumors. iAtlas -Together with the Institute for Systems Biology, Sage was funded by the Cancer Research Institute to build iAtlas, an online database and web resource designed to help basic and clinical researchers navigate immunological data across multiple tumor types. KiAAP - Funded by Bill and Melinda Gates Foundation, Sage was engaged to support the distributed efforts of BMGF funded data scientists across a number of ongoing research projects in neurocognitive development. MODEL-AD Consortium - Sage runs the Knowledge Portal, the distribution site for data, analysis results, analytical methodology and research tools generated by the AMP-AD and M2OVE-AD Consortia. NF Open Science Initiative (NF-OSI) - A first-of-its-kind Neurofibromatosis research collaboration dedicated to defeating the rare genetic disorder neurofibromatosis type 2. Tumor Neoantigen Selection Alliance (TESLA) - A global research alliance with 30 public and private groups to advance the development of more effective personalized cancer treatments. Funded by the Parker Institute for Cancer. VEOIBD Portal - Funded by the Helmsley Charitable Trust, the VEOIBD Portal aggregates Consortium-identified genotypic data with data from other data sources to find causes and treatments for Inflammatory Bowel Disease (IBD). Challenges: With algorithms playing an increasing role in biomedical analysis and patient care, there's a need for a more rigorous framework for evaluating and improving the capabilities of these algorithms. Sage Bionetworks has pioneered the development of concepts and infrastructure to objectively evaluate algorithms across a broad spectrum of biomedical domains, including bioinformatics, biomedical informatics, and clinical trials. As a trusted partner in hosting challenges and benchmarking initiatives, Sage serves as a broker between data generators and data modelers. We combine technology with biomedical and data science expertise to facilitate the objective assessment of algorithms on critical data sets, including proprietary data and algorithms that cannot be broadly shared. Sage works with the DREAM community to host open challenges. DREAM is recognized as a leader in biomedical competitions, successfully motivating research teams to address fundamental questions about systems biology and translational medicine and to advance computational methods. DREAM challenges invite participants to propose solutions - fostering collaboration and building communities in the process. Sage Bionetworks provides institutional support, along with the infrastructure to host challenges via our Synapse platform. Active Challenges hosted on the Synapse platform in 2019 included: Allen Institute Cell Lineage Reconstruction DREAM Challenge - In this partnership between The Allen Institute and DREAM, this Challenge comprises 3 sub-challenges focused on reconstructing cell lineage trees of different sizes and nature. The goal of this challenge is to mobilize a larger community for evaluating new optimal tree-building methods. BMS Anti-PD Challenge - This challenge consists of a competition-based computational research study that will generate exploratory biomarker data from the data. The Challenge will be administered in three serial stages focused on (1) tumor RNA-Seq, (2) tumor DNA-Seq, and (3) integrated analysis across multiple marker types. EHR DREAM Challenge - This challenge seeks to prospectively predict patient health outcomes in order to 1) lower the barriers to piloting innovative machine learning and data science methods in healthcare, 2) establish clinically relevant prediction benchmarks and evaluation metrics, and 3) minimize the distance between model developers and the clinic to reduce the time for model implementation. IDG Drug-Kinase Binding Challenge - This challenge seeks to evaluate the power of statistical and machine learning models as a systematic and cost-effective means for catalyzing compound-target interaction mapping efforts. Malaria DREAM Challenge - This challenge focuses on the infectious disease agent, malaria, with the goal of predicting the changing biology of Art-resistant malaria. Parkinson's Disease Digital Biomarker DREAM Challenge - This challenge is designed to benchmark methods for the collection and processing of sensor data for development of digital signatures reflective of PD burden and treatment efficacy. A major goal of this research is to use predictive modeling approaches to develop digital predictors of PD based on sensor data. Single Cell Signaling in Breast Cancer - This challenge uses genomic, transcriptomic, and proteomic measurements to evaluate signaling responses of 67 well-characterized breast cell lines to drug treatment at the single-cell level to better understand single-cell signaling and signaling modeling. Tumor Deconvolution DREAM Challenge - The goal of this Challenge is to evaluate the ability of computational methods to deconvolve bulk expression data, reflecting a mixture of cell types, into individual immune components.

Digital Health:Smartphones and other wearable sensors have put touchscreens and high-fidelity sensors into the pockets of billions of people. These technologies provide an opportunity to paint a rich understanding of health and disease in the everyday world outside of the clinic. They also provide communication tools that allow participants a more active voice in research programs. With our Digital Health program, we work to advance health research through practices that support the design, development and implementation of studies that use technology to monitor health outside of the clinical setting, and the analysis and sharing of the resulting study data. We help to derive and test digital biomarkers. We evaluate analytical methodologies to benchmark best practices in study design and data analysis. Sage's Digital Health program is built around Bridge, a technology platform for conducting biomedical research studies primarily using the ResearchKit (iOS) and ResearchStack (Android) frameworks. Bridge is composed of HIPAA-compliant web services and multi-language SDKs that facilitate: registration and informed consent to participate in research; web-based tools to design and schedule study surveys and sensor-based tasks; acquisition and secure transfer of multiple data types (surveys, sensors, audio, video, or custom data types); a study management portal with daily dashboard updates; and de-identification and storage of study data in our collaborative data science environment, Synapse. Digital Health studies active in 2019 included: Cardiovascular Fitness Module - As part of the PMI All of Us study, Sage is developing methods to use the sensors built into smartphones to assess Cardiorespiratory fitness in a way that can scale to potentially one million participants and become a generally useful tool for clinical research. Mobile Toolbox - Together with Northwestern University and Penn State University, Sage is developing a suite of mobile cognitive tests that will be distributed via Sage's technology platforms for integration into research studies where participants can test themselves using their own smartphone. Mole Mapper MoleMapper is a personalized tool to help users map, measure, and monitor mole using a smartphone camera. mPower Public Researcher Portal - The mPower Public Researcher Portal provides an updated version of the mPower iPhone study piloting new approaches to monitoring key indicators of Parkinson Disease. My BP - The "My BP Lab" research study uses surveys and sensor data collected from participants' phones to quantify and understand their daily stress. The research app, developed by Sage Bionetworks together with UCSF and Samsung, uses sensor data from Samsung mobile phones. Psorcast - This app-based research study collects and validates longitudinal measurements of psoriasis digital biomarkers to establish personalized 'psoriasis forecasts'. The models will be matched to patients based on their measurements, demographics, medical history, genetics, lifestyle, and environmental variables to potentially forecast disease progression, therapeutic efficacy and timing, and dynamics of flare/remission cycles.

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