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Updates to the R Validation Hub Executive Team

By Doug Kelkhoff on September 5, 2023

As the R Validation Hub closes in on its 5th year of activity I want to take a quick trip down memory lane and reflect on how we got here. Perhaps I should start by reminding everyone how it all started. Back in 2018, as the prospect of using R for any regulated analysis was still a hotly contested question, industry participants brought our donated space at Harvard to capacity as attendees gathered for the first ever R/Pharma conference.

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Risk Assessment App v2.0.0

By Aaron Clark on August 16, 2023

Welcome! It’s with great excitement and long-awaited anticipation that I get to share some recent updates that have hit the {riskassessment} app’s GitHub repository earlier this month. If this is the first time you’ve heard or seen the application, I’d recommend starting with our README to gain some familiarity with the project, especially with installation instructions. However, (in a nut-shell) the app is a full-fledged R package that seeks augment the utility of the {riskmetric} package within an organizational context.

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{riskassessment} App voted best Shiny app at shinyConf 2023! 🎉

By Juliane Manitz on June 2, 2023

The {riskassessment} app, presented by Aaron Clark from the R Validation Hub Executive Committee, was voted best Shiny app at shinyConf 2023. The 2nd Annual Shiny Conference was held in March 2023. It was all virtual with over 4k global registrants. Congratulations!! The app provides a shiny front-end to augment the utility of the {riskmetric} package, thus user-friendly and interactive access to risk assessment of R packages. The apps functionalities include:

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Summary of 2022 Case Studies

By Juliane Manitz on March 15, 2023

Last year, the R validation hub recently initiated a three-part presentation series on case studies in which eight pharmaceutical companies shared their experiences on building a GxP framework with R. These case studies highlighted both easy and challenging aspects of implementing risk assessment for R packages in a GxP environment. In this blog post we attempt to summarize common themes, difference in approaches, and challenges. All implementations followed the risk validation process for R packages outlined in the white paper.

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Participating Organisations

Members of the following organisations are participating in this project