Workshop: Flavors of the Pharmaverse

Monday, Aug 12, 9:00 AM – 5:00 PM PDT

Presented by:

Andrew Bates
Data Solutions Engineer, Atorus Research

Casey Aguilar-Gervase
Senior Data Visualization Engineer, Atorus Research

Daniel Sjoberg
Senior Principal Data Scientist, Genentech

Becca Krouse
Data Science Leader

Ellis Hughes
Data Science Leader, GSK

Over the past 4 years, the pharmaverse was created and has blossomed into a booming community of organizations and package developers aimed at supporting R development with focus on the clinical reporting pipeline. Even within a world as standardized as regulatory submissions, organizations still tend to have sometimes vastly different requirements within their own processes.

In this workshop, we’ll give a high level overview of the scope and tools available within the pharmaverse for the clinical pipeline, including tools for ADaM data set curation, creating Analysis Results Data Sets, and TLGs. To help attendees understand how there are different paradigms and pathways through the pharmaverse, we’ll take a tour through two to three different strategies available to support table, listing, and figure creation. Attendees of this workshop will walk away with an understanding of how the pharmaverse can help their organization and where they can look to learn more about the right tools to support their needs.

Presentation: Making an App a System

Tuesday, Aug 13, 2:40 PM – 4:00 PM PDT

mike stackhouse

Presented by:

Mike Stackhouse

Atorus CIO

What data processing in your Shiny app is redundant or must happen within the app at all? What makes Shiny beautiful is how it blends data visualization into a compact bundle of code. That said, there are challenges to overcome to get from a developer’s console to users’ screens. Tools like Posit Connect help with this process, but as an app matures, developers and their users may encounter different performance issues. To address this, sometimes this means evolving and introducing separate data pipelines. In this presentation, we will overview some different types of scaling issues for a Shiny app. Additionally, we will introduce the new package {matte}, which provides support for adding data pipelines to your app that live outside Shiny.

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