January 15, 2020 — With public data set to play an increasingly important role in drug discovery and development, an integrated, data-driven approach to clinical planning can optimize the probability of success. The increasing availability of public data sets, such as The Cancer Genome Atlas (TCGA) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI), offers a transformational opportunity for insight-driven planning at all phases of the drug development life cycle. The size and scope of these public data sets are often considerable, compiling billions of data points across multiple modalities and representing data that would have previously required many years and millions of dollars to generate.

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