News

Jumping Rivers' Litmusverse: Another Success for Open-Source Validation

Since 2018, the R Validation Hub has devoted considerable time and energy to the development of powerful R packages that are designed to support the risk assessment of R packages. Our commitment to building a comprehensive validation framework—alongside tools like {riskmetric} and {riskassessment}—has proven to be a sound investment. This is reflected in the ongoing support of the R Consortium of our working group, the inclusion of our packages in the Pharmaverse, and the growing prominence of our framework and tools at the heart of the expanding risk assessment landscape.

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{riskassessment} ShinyGatherings x Pharmaverse Workshop

At a recent ShinyGatherings, some {riskassessment} contributors presented a workshop that focused on tailoring the application to org-specific risk requirements to simplify R package validation. Though we discussed the end-user experience, this workshop was really geared towards equipping “app deployers” to get the highest and best use out of the application for their organization’s specific needs. We appreciate Appsilon for the opportunity to speak about the application!

About the Workshop

The workshop’s main topics:

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Risk Assessment App v3.1.1

Progress is continuing to be made in {riskassessment}. We wanted to share some of the enhancements and updates included in the most recent release of the application. There have been multiple releases, both minor and major, since our last post, so we have a lot of new content to cover!

But before we get into too much detail, if you are new to what we are doing in {riskassessment}, we would like to encourage you to check out our README. There you can find information regarding what {riskassessment} is seeking to accomplish and how you can install and deploy an instance of it for your personal or organizational use.

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Updates to the R Validation Hub Executive Team

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. Amidst a slew of impressive shiny applications (I vividly remember shiny being the decided tone-setting theme that year), one Andy Nicholls offered up a deceptively simple question: what should validated use of R look like?

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Risk Assessment App v2.0.0

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! 🎉

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

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. There was a common theme of categorizing package quality into two or three risk categories. Test coverage was identified as a high-importance assessment metric, and the R Foundation was determined to be a trusted resource. Core R and recommended packages were treated as a collective of “low-risk” packages, with some organizations extending this to the tidyverse.

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ASA Biopharmaceutical report, Fall 2022

I’m pleased to share that the R Validation Hub’s efforts have been recognised in the ASA Biopharmaceutical report, Fall 2022. Within the edition you can find our paper, Risk Assessment of R Packages: Learnings and Reflections. This paper reflects on our white paper; provides an overview of our {riskmetric} package and Risk Assessment application; and summarises our 2022 case studies (which you can now find on our Case Studies page).

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Status Update May 2022

It’s time to bring another update to you on the current status of the R validation hub:

• The riskmetric R package has been stable on CRAN. Recent work has focused on structuring “cohort metrics” – metrics that are conditioned on the package library or execution environment available to R. In R, package behaviors are often dependent on the rest of the R installation, and this new feature will help to make metrics more inspectible and reproducible, as well as allowing us to ask new questions like, “What would be the effect of installing a new package into an R environment?”. Within riskmetric, cohorts will represent our way of capturing this information to help make the context of each metric more explicit. Eric Milliman has been leading this effort, representing the next major feature enhancement for the riskmetric package.

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Risk Assessment App Update

This is a re-post. The original post from the R Consortium can be found here

Recent update by Marly Gotti on the Risk Assessment Shiny App. Marly is an executive committee member of the R Validation Hub where she advocates for the use of R within a biopharmaceutical regulatory setting, and Senior Data Scientist at Biogen.

The Risk Assessment App is an interactive web application serving as a front end application for the riskmetric R package. riskmetric is a framework to quantify risk by assessing a number of metrics meant to evaluate development best practices, code documentation, community engagement, and development sustainability. The app and riskmetric aim to provide some context for validation within regulated industries.

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