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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 Cormar 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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Status Update: R Validation Hub at R/Pharma 2021

By Juliane Manitz on October 19, 2021

Our favorite meeting of the year is approaching: R/Pharma 2021 will be held virtually November 2-4th, 2021. Also watch out for workshops the week before. Since the R validation Hub is closely associated with R/Pharma, we would like to highlight some of the presentations inspired by the R validation Hub, partner initiatives, or generally related to the topic of validation. Tuesday: November 2, 2021 11:00am “R Package Validation at Roche” by Coline Zeballos, Roche 11:20am “Statistical Analysis and Pathway to a Risk-based Assessment of R packages at Merck KGaA/EMD Serono” by Juliane Manitz, EMD Serono 1:50 PM “Panel Discussion – Validation” with representatives of the R validation Hub” Wednesday: November 3, 2021

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Status Update: MSA Framework by TransCelerate

By Juliane Manitz and Joe Rickert on May 20, 2021

TransCelerate has published “Modernization of statistical analytics (MSA) Framework”. With goals similar to the R Validation Hub, the TransCelerate MSA framework seeks to demonstrate software reliability by establishing principles of accuracy, traceability, and reproducibility for a modern analytical software environment. The MSA framework is centered around risk-assessment and mitigation practices to demonstrate reliability of software. This framework suggests assessing the accuracy of a software library via a confidence measure built on risk metrics such as published source code, issue management, usage, maturity, etc.

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Participating Organisations

Members of the following organisations are participating in this project