Every Cure

Funding pattern

What this funder pays for, at what size, and how to position adjacent work. Read from their filings, with every number checked against the record.

Grant history

All 5 reported grants, largest first.

• $971,372

  University of North Carolina · Chapel Hill, NJ · 2024

  Unc will co-lead development of the integration layer that connects diverse datasets into a unified biomedical knowledge graph. They will define ontology standards, conduct manual curation, and lead harmonization across… read allUnc will co-lead development of the integration layer that connects diverse datasets into a unified biomedical knowledge graph. They will define ontology standards, conduct manual curation, and lead harmonization across drug, disease, and molecular data types. Their role ensures the robokop and monarch knowledge graphs and proprietary datasets are systematically aligned to every cure's computational infrastructure. less
• $362,247

  The Scripps Research Institute · La Jolla, CA · 2024

  Scripps will integrate its biothings explorer platform into every cure's knowledge graph, contributing apis, data evaluation, and ontology mapping expertise. They will identify proprietary datasets, evaluate their utili… read allScripps will integrate its biothings explorer platform into every cure's knowledge graph, contributing apis, data evaluation, and ontology mapping expertise. They will identify proprietary datasets, evaluate their utility, and refine integration processes for clinical and patient-level data. Their work strengthens interoperability and ensures high-value biomedical data is connected across the matrix project. less
• $309,022

  Institute for Systems Biology · Seattle, WA · 2024

  Isb will curate, evaluate, and integrate large biomedical datasets into every cure's knowledge graph, focusing on data quality and ontology harmonization. They will perform manual curation, cross-validation, and develop… read allIsb will curate, evaluate, and integrate large biomedical datasets into every cure's knowledge graph, focusing on data quality and ontology harmonization. They will perform manual curation, cross-validation, and development of protocols to ensure reliable drug, disease, and molecular associations. Their work ensures the spoke database and other key sources are incorporated into a robust computational framework for drug repurposing. less
• $303,699

  Penn State University · University Park, PA · 2024

  Penn state will lead the development of advanced computational tools, including algorithms to predict drug repurposing opportunities within the knowledge graph. They will work on data extraction, harmonization, and mach… read allPenn state will lead the development of advanced computational tools, including algorithms to predict drug repurposing opportunities within the knowledge graph. They will work on data extraction, harmonization, and machine learning model development to rank candidate drugs. Their role provides the computational "engine" that drives prioritization of promising therapies. less
• $235,161

  University of Alabama Birmingham · Birmingham, AL · 2024

  Uab will contribute specialized biomedical data and expertise in integrating patient-level, genomic, and clinical datasets into the knowledge graph. They will support validation of predicted drug-disease associations th… read allUab will contribute specialized biomedical data and expertise in integrating patient-level, genomic, and clinical datasets into the knowledge graph. They will support validation of predicted drug-disease associations through computational and experimental methods. Their work ensures the knowledge graph is grounded in high-quality clinical and biological evidence. less