Description
{teal} has evolved tremendously over the past 5 years, from a small R-shiny based package to a large scalable framework that transforms clinical trial data exploration journey. The framework's key features, such as dynamic data filtering, code and report generation, promote transparency and reproducibility throughout the data exploration process. In this workshop, we will cover the typical {teal} workflow in a clinical trial setting, then take participants through a series of exercises to create teal apps with varying degrees of complexity. We will walk through a sample of module templates for baseline, safety and efficacy analyses, highlight new features and demonstrate how to implement them. Lastly, we will show examples of how to customize existing modules and build a bespoke analysis module from scratch. The workshop will equip participants with the knowledge and skills to leverage {teal} and its family of packages to build their own teal apps for the real-world clinical trial they are supporting, bringing data closer to stakeholders, ultimately leading to quicker insights and better-informed decisions. For more information about {teal}, please visit https://insightsengineering.github.io/teal/
Bio:
Dony Unardi is a Data Scientist with more than a decade of experience in the pharmaceutical industry. In the last five years, he has supported the adoption of R and implemented R solutions within his role in Product Development Data Sciences at Roche/Genentech. He authored several internal R packages and Shiny apps, focusing on data curation and harmonization. Dony has a Bachelor’s degree in Computer Information Systems and is currently the Engineering Team Lead, leading the development effort of the teal framework.
