Three converging forces are reshaping data science in life sciences: FDA regulatory updates approving R for submissions, a talent shift toward open-source languages, and a new risk-based Computer Software Assurance framework replacing legacy CSV validation. Life sciences organizations face four imperatives: modernizing statistical computing environments to support R, Python, and SAS with full auditability; embedding governance as infrastructure rather than friction; bridging the gap between models and decision-makers through scalable applications; and driving cultural change through leadership. A Domino Data Lab event (Rev Philadelphia, May 12) brings together industry leaders from Novartis, GSK, AstraZeneca, and others to discuss these challenges.
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The tooling and process imperative: More than a technology upgradeThe governance imperative: Accelerating outcomes instead of slowing down workThe application imperative: From models to decisionsThe leadership imperative: Transformation driven by mindsetThe conversation happening on May 12 in PhiladelphiaSort: