Component Type: Tutorial
CE: ACPE 2.75 Knowledge UAN: 0286-0000-21-503-L04-P; CME 2.75; IACET 2.75; RN 2.75
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Traditional approaches to medical product development rely on generating pages upon pages of analysis results to describe the safety and effectiveness of novel therapies. Study teams struggle to understand and communicate the story hidden within the data to their colleagues. First and foremost, with the high cost of conducting translational clinical research, it is common to collect as much data as possible on as many endpoints as possible. This phenomenon is further reinforced due to our limited understanding of biological mechanisms and pathways, including the potential genomic underpinnings of a disease or treatment response.
Ben Shneiderman stated that “the purpose of visualization is insight.” Therefore, the goal of this short course is to describe data visualization techniques to aid in the understanding and communication of results from applications in clinical trials and genomics research. Numerous practical illustrations and examples from the literature will be presented. To be accessible to a wide audience, this course will focus on principles and interpretation, and limit technical jargon.
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DIA 2021 Who should attend? This short course is designed to be accessible to a wide audience, it will focus on principles, limit technical jargon, and interpret numerous examples of data visualization using data from the life sciences literature. The audience may include any individual interested in developing their skills for more efficient interpretation and communication of various aspects of study design and analysis.
Learning Objectives Describe the transition from traditional methods of data analysis to visual approaches; Identify life science data using one or more data visualizations; Assess the strengths and limitations of various graphical techniques; Explain the “data story” of numerous clinical research, examples using data visualization techniques.
