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ASA Biopharmaceutical report, Fall 2022

By Andy Nicholls on December 5, 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

By Juliane Manitz on May 20, 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?

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Risk Assessment App Update

By Joseph Rickert on February 3, 2022

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.

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Some Considerations on Trusted Resources

By Juliane Manitz, Yilong Zhang, and Andy Nicholls on January 7, 2022

There is a large variety of contributed R packages, which can be overwhelming when performing their accuracy assessment. These packages can be developed by anyone and may differ in accuracy. The white paper mentions the possibility to define “trusted resources” to simplify the assessment for some of the R packages. The idea follows vendor assessments / audits to explore the internal validation practices of the vendor for proprietary software. For open-source software such audits are not logistically feasible.

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Participating Organisations

Members of the following organisations are participating in this project