Large-scale omics datasets are revolutionizing how pharmaceutical companies identify targets for therapeutic development, and have become one of the main paths in accelerating precision medicine. For example, the DiscovEHR collaboration between the Regeneron Genetics Center and Geisinger Health System studied over 50,000 whole exome sequences with their associated EHR-derived clinical phenotypes, and identified more than 4 million rare variants, revealing clinical association to genes encoding drug targets. However, turning petabyte-scale, heterogeneous datasets into actionable insights remains a challenge for companies using legacy genomic data technologies. Reducing preclinical timelines and creating targeted therapeutics requires working within an informatics platform that can scale with the complex datasets generated across the drug discovery pipeline. Such an environment requires the ability to integrate home-grown and open source analytical tools, streamline team collaboration, and secure data based on stringent regulatory compliance. Our customers have employed the following strategies to help them define and execute their informatics approach.

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