Every Cure

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 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.

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 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.

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 MACHINE LEARNING MODEL DEVELOPMENT TO RANK CANDIDATE DRUGS. THEIR ROLE PROVIDES THE COMPUTATIONAL "ENGINE" THAT DRIVES PRIORITIZATION OF PROMISING THERAPIES.

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 THROUGH COMPUTATIONAL AND EXPERIMENTAL METHODS. THEIR WORK ENSURES THE KNOWLEDGE GRAPH IS GROUNDED IN HIGH-QUALITY CLINICAL AND BIOLOGICAL EVIDENCE.