Abstract: Scientists in drug discovery research utilize a wide variety of instrumentation and techniques to advance their research. While instrumentation vendors often provide software tools to deal with data wrangling and visualization, a simple collection of isolated tools often fails to address the scale and overall scope of the data analysis encountered in discovery research. This can lead to lost productivity as scientists work to process, collate and summarize their work across various informatics systems. Shiny has seen increasing use in Pharma clinical research. On the other hand, Shiny apps are also transforming discovery research by putting powerful data wrangling, visualization and reporting tools into the hands of bench scientists. To solve the aforementioned problems in drug discovery research, we developed a suite of tools using Shiny to automate data wrangling, integration, visualization and reporting. Examples will be presented in areas such as automated signal processing and batch analysis of electrocardiogram data, collection and visualization of biomarker and physiology measurements from pharmacology studies, and access to a high performance computation cluster for non-experts. These Shiny tools and have shown value by increasing productivity and accelerating scientific research.
Speaker: Gordon Turner
Affiliation: Novartis
Title: Shiny apps for accelerating early drug discovery research
Abstract_Sanitzed: Scientists in drug discovery research utilize a wide variety of instrumentation and techniques to advance their research. While instrumentation vendors often provide software tools to deal with data wrangling and visualization, a simple collection of isolated tools often fails to address the scale and overall scope of the data analysis encountered in discovery research. This can lead to lost productivity as scientists work to process, collate and summarize their work across various informatics systems. Shiny has seen increasing use in Pharma clinical research. On the other hand, Shiny apps are also transforming discovery research by putting powerful data wrangling, visualization and reporting tools into the hands of bench scientists. To solve the aforementioned problems in drug discovery research, we developed a suite of tools using Shiny to automate data wrangling, integration, visualization and reporting. Examples will be presented in areas such as automated signal processing and batch analysis of electrocardiogram data, collection and visualization of biomarker and physiology measurements from pharmacology studies, and access to a high performance computation cluster for non-experts. These Shiny tools and have shown value by increasing productivity and accelerating scientific research.