FUSION is designed to mine complex multiscale datasets to identify clinical and molecular phenotypes critical to accelerated biomarker discovery. FUSION allows researchers to rapidly import and build model training sets utilizing a broad range of data types from clinical, multiomic, biochemical, and imaging sources. Users can interactively review this diverse range of data for domain-of-applicability across molecular and clinical phenotype, disease specificity and patient outcomes. Users can continually explore training data quality and relevance utilizing integrated literature search options which access over 25 million peer-reviewed abstracts automatically filtered on the terms and concepts in both open access and experimental datasets, further ensuring the latest biomarker advances are utilized during model development. FUSION is accelerating how quickly heterogeneous multiscale data can be integrated and utilized in the research enterprise.

Biomarkers are used to measure and evaluate normal biological processes, pathogenic events, and pharmacologic response to a therapeutic intervention. With FUSION, researchers can now effectively evaluate the predictive value of a biomarker signature for monitoring efficacy and reduced toxicity at the individual patient level. Upon manual or automated submission of patient-state parameters the system will generate and display a process or endpoint prediction, prediction confidence, and a multiscale visual inventory of patient descriptors, molecular interactions, pathway involvement, and disease associations. On-demand access to this diverse range of information assists with both mechanistic understanding and the characterization of clinical utility during companion biomarker development. FUSION is redefining the pace and potential of high-complexity biomarkers to accelerate drug development and support the design of more effective and personalized therapy selection strategies at the point-of-care.