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Pharmaceutical R&D involves a large number of disciplines working together to design, execute and interpret the results of a wide variety of experiments, with the ultimate goal of developing medicines that will help patients around the world.
Many of the disciplines involved in this research have had limited training in statistical methods, and more generally, in quantitative thinking, which is critical to interpreting data and making inferences that lead to effective decision making.
A key challenge for a Statistics department in such organizations is how to facilitate a higher level of understanding throughout R&D. Often, such efforts are grass-roots and rely on informal tutorials that stem from real-time issues faced by the project teams. More formal efforts may be needed in order to make a step-change in quantitative capabilities within a large research organization.
This roundtable discussion is intended to share ideas about the various ways a Statistics department can help their pharmaceutical R&D colleagues gain the quantitative understanding they need to effectively contribute to team discussions involving data interpretation and inference.
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