Funders › WA › Sage Bionetworks › 2018
Grants paid by Sage Bionetworks, tax year 2018
EIN 26-4489946 · Seattle, WA · Form 990, Schedule I · NTEE U50
In tax year 2018, Sage Bionetworks (EIN 26-4489946) reported 17 grants paid totaling $1,660,903. Dataset version 2026.09.0, built 2026-09-03.
Every grant, 2018
| Tax year | Recipient | Match | Amount | Type | Purpose | Source filing |
|---|---|---|---|---|---|---|
| 2018 | Institute for Systems Biology Seattle, WA | A | $489,494 | paid | Assist in the development of an integrative platform: the Pan-cancer Immune Atlas (iAtlas) to host the data and results derived from the PanCancerAtlas Immune Response Working Group and to provide external investigators witht the ability to reproduce results of the IRWG. Provide expertise related to the analyses of the metabolic and transcriptional regulatory networksand will work collaboratively to develop, implement, test, and benchmark all methods related to the dynamic analyses of the transcriptional regulatory and metabolic networks aimed at drug target discovery for Alzheimer's Disease. The Institute for Systems Biology will provide expertise related to the (dynamic) analyses of the metabolic and transcriptional regulatory networks and will work collaboratively to develop, implement, test, and benchmark all methods related to the dynamic analyses of the transcriptional regulatory and metabolic networks aimed at drug target discovery for the AMP-AD CC project. | 201922899349300212 |
| 2018 | Icahn School of Medicine at Mount Sinai New York, NY | A | $325,616 | paid | Perform computational and integrative analysis of the AMP/AD data sets to develop a set of high probability therapeutic targets necessary for their assessment and integration into drug discovery efforts for the Agora project. Image-guided studies to determine the contribution of breast cancer cells to metastatic outgrowth Leukemias for the CSBC project. | 201922899349300212 |
| 2018 | University of California San Diego La Jolla, CA | A | $206,908 | paid | To determine the test validity and test-retest reliability of smartphone-based measurement of CRF. To evaluate the feasibility and acceptability of using a smartphone application to measure CRF. This will be examined using a system usability scale and assessing compliance and overall satisfaction with the administered protocol. Provide expert consultation in the use of agile science methods for creating strategies for facilitating sustained engagement with the MPower 2.0 application. This includes providing expertise related to behavioral theory, human centered design, and measurement strategies. Develop an experimental design and broader strategy for gathering evidence to foster iterative improvement on mPower to foster improved sustained engagement with the tool. | 201922899349300212 |
| 2018 | Stanford University Stanford, CA | A | $175,960 | paid | Oversee the genomic profiling, analysis, and computational modeling of metastatic colorectal cancer patient data. Prioritize candidate metastasisassociated genes and provide for modeling in organoids. Contribute to the analysis of cell fitness and clone size distributions in the metastatic colon organoid models. Interpret the data from the microenvironmental arrays. Create a baseline model for future comparison using existing framework for Digital Mammography Challenge. | 201922899349300212 |
| 2018 | Fred Hutchinson Cancer Research Center Seattle, WA | A | $56,144 | paid | Study the mechanisms that underlie metastatic castrate resistant prostate cancer(CRPC). We will combine approaches from pharmacology, as well as cell and computational biology to identify kinases that are functionally important for driving cell growth and proliferation in CRPC. We will employ Kinome regression approach to: (1) identify kinases in CRPC cell lines and patient-derived organoid models and test in silico predicted candidate kinase inhibitors in 3D bone-mimetic cultures; and (2) validate the effect of candidate kinase inhibitors in in vivo CRPC bone metastasis models, followed by molecular characterization. | 201922899349300212 |
| 2018 | University of Pittsburgh Pittsburgh, PA | A | $56,016 | paid | Combine approaches from pharmacology, as well as cell and computational biology to identify specific kinases that are functionally important for the growth of metastatic CRPC. We will also build a computational model to predict response to >300 naive kinase inhibitors in a physiological-relevant CRPC bone metastasis model. Further, we will probe the spatial nature of the kinase-driven signaling patterns in the tumors, which is critical to understanding the mechanisms of drug response. Overall, these studies have a strong potential to advance medical practices; a new therapeutic option for metastatic CRPC could give unprecedented hope to the providers and patients who currently face this disease with severely limited alternatives. | 201922899349300212 |
| 2018 | The University of Texas Md Anderson Cancer Center Houston, TX | A | $55,976 | paid | Validate in 3D the top kinase inhibitors selected in the 2D screening. These experiments will be performed on up to 3 prostate cancer cellular models, including cell lines and patient-derived xenografts, testing different concentration of the inhibitors. | 201922899349300212 |
| 2018 | Duke University Durham, NC | A | $52,160 | paid | Metastasis is the primary cause of cancer patient mortality and is virtually uncurable. In colorectal cancer (CRC), which represents the third leading cause of cancer-related mortality in the United States, 10-20% of patients with Stage II disease and 50% with Stage III develop recurrence, while another 20% of patients present with metastases at diagnosis. Current targeted therapies for metastatic colorectal cancer (mCRC) prolong survival by mere months with little benefit in the adjuvant setting. Improved treatment strategies are thus urgently needed, but require characterization of the molecular drivers and microenvironmental determinants of the metastatic phenotype. Critically, the advent of advanced genome-engineering and lineage tracing technologies, 3-D organotypic culture systems and platforms to probe the tumor microenvironment provides an unprecedented opportunity for rapid, functional and phenotypic screens towards delineation of the genotype-phenotype map in cancer. | 201922899349300212 |
| 2018 | Partners Healthcare System Inc Somerville, MA | A | $47,732 | paid | Combine mouse mammary cancer models with high-resolution imaging to quantify early vs late disseminated cancer cells, outgrown metastases, and their colocalization and dynamics. To quantify behavior of disseminated cancer cells using laser scanning confocal microscopy and other techniques available at the MGH Center for Systems Biology. | 201922899349300212 |
| 2018 | University of Massachusetts Worcester Worcester, MA | A | $46,255 | paid | There is an ongoing debate concerning whether early DCCs or late DCCs drive metastasis during the life of a patient when both population will likely co-exist. We hypothesize that in fact both early and late disseminated cancer cells (DCCs) cooperate to drive metastatic outgrowth. Here, we adopt an innovative interdisciplinary approach combining metastatic tumor modeling, tissue engineering, high-resolution in vivo microscopy, and integrative omics analysis to tackle the problem. We believe the success of this pilot proposal will provide novel strategies to combat the deadly metastatic diseases, as well as foster our future collaborations. | 201922899349300212 |
| 2018 | University of Arizona Tucson, AZ | A | $38,685 | paid | The goal of the project is to develop small molecules (from in silico docking on the CD44 binding pocket and peptidomimetics of CD44 peptide) and peptides (from the peptide array) to disrupt the interaction between CD44 and FERM domain-containing proteins. These tools will help to define if the proteins are druggable, and whether targeting protein-protein interactions can have a more specific effects than global inhibition of the ectodomain of CD44 using antibodies or small molecules. This will pave the way to testing therapeutic hypotheses for AMP-AD targets relating to protein-protein interactions. | 201922899349300212 |
| 2018 | Rutgers the State University of New Jersey Piscataway, NJ | A | $36,570 | paid | The research proposal outlines image-guided studies to determine the contribution of breast disseminated cancer cells to metastatic outgrowth. | 201922899349300212 |
| 2018 | Oregon Health & Science University Portland, OR | A | $21,269 | paid | CSBC Pilot testing and optimization of MCAT/Her2 crainbow cells on MEMA platform and MEMA optimization and screening. | 201922899349300212 |
| 2018 | San Ysidro Health San Diego, CA | A | $19,929 | paid | San Ysidro Health (SYHealth) will participate in the "All of Us Research Program Sage Bionetworks - Federally Qualified Health Centers Consent Study" for participant recruitment and data collection. Findings from this study will be used immediately to improve, elaborate, and/or supplement AoURP informed consent materials for AoURP national launch. The project begins with formative work to determine study approach and contribute to study protocols and ends with data submission and analysis verification by the site PI. | 201922899349300212 |
| 2018 | Hudson River Healthcare Foundation Peekskill, NY | A | $18,845 | paid | Research Assistants (RAs) will recruit potential participants using a variety of techniques including engagement tabling in Barham House, a senior apartment building, at the Peekskill Kiley Center with the Community Action Program, and at local community venues like the Salvation Army, the Peekskill Library, and a local homeless shelter, in addition to health-center based recruitment. The RAs and Pilot Coordinator will liaise with community stakeholders to coordinate such recruitment efforts. Interested individuals are screened by RAs using the REALM-SF tool and, if eligible, invited to participate in a 1:1 interview or a focus group. Each session lasts approximately 1 hour and is facilitated and recorded by a Research Assistant. An additional RA participates for notetaking purposes as appropriate. In addition to these implementation activities, our PIs and Project Coordinators liaise with the other FQHCs involved, with Sage, and with MITRE to provide ongoing feedback on the REALM | 201922899349300212 |
| 2018 | University of Rochester Rochester, NY | A | $7,667 | paid | Provide consultation on interpretation and guidance on mPower 1.0 analysis and design and scientific strategy for mPower 2.0 data collection. | 201922899349300212 |
| 2018 | New York University New York, NY | A | $5,677 | paid | Data generation and analysis for the Proteogenomics Computational Challenge | 201922899349300212 |
Match tier: A Reported EIN · B Exact name and place · C Strong name match · D Probable name match · U Unresolved. Tiers C and D are inferred, not reported; see how matching works.
Recipient matching for this dataset version has not yet completed its independent precision check. Tier A rows carry the EIN the filer reported; tiers B–D are the matcher's inference and should be read as leads until the check is published on the methodology page.
Derived from IRS Form 990 e-file XML. Dataset version 2026.09.0, built 2026-09-03. All years for this funder.
The same organization elsewhere in the program: exempt status and filing health · federal awards · grant guidance · open opportunities.
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