{riskassessment}
applicationShiny Gatherings x Pharmaverse, 28 JAN 2025
Slides: 🔗 Follow Along!
On behalf of the R Validation Hub team:
Aaron Clark Arcus Biosciences
Jeff Thompson Arcus Biosciences
Any opinions expressed in this presentation and on the following slides are solely those of the presenter and do not necessarily reflect those sponsoring the work
The R Validation Hub is a collaboration to support the adoption of R within a biopharmaceutical regulatory setting (pharmaR.org)
Guidance on compliant use of R and management of packages
Building a public, validation-ready resource for R packages
Coline Zeballos
Connecting validation experts across the industry
Jaxon Abercrombie, Anuja Das, Antal Martinecz
{riskmetric}
Gather and report on risk heuristics to support validation decision-making
Eric Milliman
{riskassessment}
A web interface to {riskmetric}
, supporting review, annotation and cataloging of decisions
Aaron Clark, Jeff Thompson
{riskassessment}
App Workstream 5minReviewer POV
- The App’s Best Use Case 15minAdmin POV
- Configure for your org 20min
is a framework to quantify an R package’s “risk” by assessing several meaningful metrics designed to evaluate package development best practices, code documentation, community engagement, and development sustainability.
is a full-fledged R package containing a shiny front-end that augments the utility of {riskmetric}
. The application’s goal is to provide a central hub for an organization to review and assess the risk of R packages, providing handy tools and guide rails along the way.
Sometimes “quality” is measurable! Software dev best practices dictate an R-package should have:
18 total assessments (to date)!
Main goal: complement GxP “package inclusion requests” with data.
Main goal: complement GxP “package inclusion requests” with data.
Main goal: complement GxP “package inclusion requests” with data.
Main goal: complement GxP “package inclusion requests” with data.
Main goal: complement GxP “package inclusion requests” with data.
Main goal: complement GxP “package inclusion requests” with data.
Bonus / Secondary Perks:
{riskmetric}
{riskmetric}
on the same machine with the same environment – creating a central hub for reproducibility{riskassessment}
🥩 Reviewer
POV
{riskassessment}
Report(s)Jeff Thompson
thank you to our many contributors
our work is the product of the donated time of many passionate individuals
Slides: 🔗 For your Review
Over USD $1.4 Million
R Validation Hub, R-Ladies
Stanford Data Institute
R/Medicine, R/Pharma, useR!, LatinR, and more