Big data has referred to the means to acquire and analyze new, complex and multi-dimensional sources of information. Novel tools to extract meaning from ‘big data’ have the potential to drive substantive changes in clinical practice, from personalized diagnostics, prognostics and therapeutics to intelligent drug design, population surveillance/screening and the mining of the electronic health record. Successful integration of data analytics and data sciences within platforms for biomedical discovery are expanding further innovations and applications to patient care.
In this symposium we will explore underlying principles of big data approaches, and the translation of findings to clinical applications. Discussions will explore three examples of integrated ‘big data’ and functional discovery approaches, (1) digital imaging and improved pathologic diagnosis, (2) pathogen and microbiome big data approaches to identify new therapeutic targets and implement better prevention methods for pathogens from C. difficile to COVID-19, and (3) single cell sequencing to define genomic and environmental drivers of cancer, and identify targets for new therapeutic approaches. These examples will provide insights into how computational pathology is developing the tools we will be using to care for patients in the future.
