Level: Beginner
Kelci Miclaus, Senior Manager Advanced Analytics R&D, JMP Life Sciences, SAS
Rebecca Lyzinski, JMP Clinical Research Developer, SAS
Conducting translational and clinical research comes with a big price tag. Given costs and time considerations in studies for understanding health outcomes and disease, researchers commonly collect as much data on as many endpoints as possible. This is further motivated by our limited understanding of the biological underpinnings of disease and good clinical research practice protocols to assess not only efficacy of new therapeutics, but safety and operational integrity. In the life science data “life cycle,” the data volume poses challenges to analyze and communicate results; traditional practices that produce hundreds of tables are not efficient nor effective. This presentation will focus on common and new visualization techniques in clinical trial research. We highlight both data summary visualization techniques and plots to communicate the results of complex statistical analyses. This will include distributional summaries of safety and efficacy in clinical trials, clinical findings trends (waterfall plots, shift plots, spaghetti plots, lasagna plots, swimmer plots), time-to-event and clinical operational integrity anomaly detection. Examples will be presented with Graph Builder, highlighting the latest features of this platform. We will then demonstrate the implementation of these visualization practices in JMP Clinical, a vertical solution tailored to create highly customized clinical analysis reviews, and give an overview of the latest features available in JMP Clinical 7.1.
