FUSION is designed to mine complex multiscale datasets to identify chemical and molecular properties critical to precision drug development. 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 chemical and biological species. 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 drug discovery and repurposing advances are utilized during model development. FUSION is accelerating how quickly heterogeneous multiscale data can be integrated and utilized in the research enterprise.

FUSION is designed to mine complex multiscale datasets to identify chemical and molecular properties critical to drug discovery and development. FUSION can explore biochemical processes utilizing AI-based search techniques to evaluate a broad range of candidate structures and activities for predictive value across multiple molecular properties and endpoints. Onscreen automation options allow researchers to control exploration constraints including the identification of druggable properties and privileged structures, optimal scaffold design and ADMET profiling throughout the drug discovery and clinical trials process. Whether operating at the target, lead, pathway or patient level, the computational strategies utilized within FUSION will provide critical new insights between molecular features and future drug response. The FUSION Analytics Platform is a new paradigm within in silico drug development and repurposing helping researchers identify the right target, the right hit and the right exposure.

New and accelerated molecular profiling strategies are required to permit safe and cost-effective precision drug development. FUSION predictive models complement physical experiments providing a new level of flexibility and reproducibility not available in other in silico screening technologies. FUSION will automatically design and evaluate candidate molecular structure-activity combinations based on desired performance specifications across a range of species, endpoints and targets on demand. Upon submission of a new chemical entity, FUSION discovery reporting provides an activity prediction, prediction confidence, a multiscale visual inventory of molecular descriptors, structural alerts, pathway involvement and disease associations all live linked to the supporting literature. Automated access to this diverse range of information will assist with mechanistic understanding and accelerate a range of mission-critical drug development activities. FUSION is redefining the impact statistical and mechanistic models are having on precision drug design, accelerated drug development, and safer drug production.