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.
With unfettered access to these data, organizations can leverage this wealth of information to immediately adopt more rational approaches to trial design, patient stratification, repurposing, indication expansion, and portfolio strategy.
We see progressive organizations taking a strategic approach to compiling and integrating publicly available data to guide insight generation through a mixture of mechanistic and data-driven exploration. This data and knowledge asset can additionally be enriched with data from the organization’s own preclinical and clinical programs to exponentially increase an organization’s capability to develop and test hypotheses quickly and fuel a more data-driven approach to clinical planning.
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Authors: Renée Deehan, PhD | VP, Computational Research and Tobi Guennel, PhD, SVP, Product Development & Systems Integration