R Validation Discussion: Metric Repos for Open Quality Assessment

Building a pre-built database of metrics for software validation

Validation

Discussion

Advanced

Author

Doug Kelkhoff (R Validation Hub)

Overview

Advanced Validation GxP

The R Validation Hub has built a Metric Repository - a pre-built database of metrics to support the software validation process. This discussion workshop explores the industry outlook for this open validation database and gathers community input on standardization and implementation.

Discussion Topics

🗄️ Metric Repository overview
🔧 Standardizing compute environments
📊 Quality standards for packages
🏢 In-house package validation
🔮 Future of R validation

Key Packages

{riskmetric}

{riskassessment}

{riskscore}

{val.meter}

{val.criterion}

Workshop Links

Resources

Regulatory Repo WG: github.com/pharmaR/regulatory-r-repo-wg

val.meter: github.com/pharmaR/val.meter

val.criterion: github.com/pharmaR/val.criterion

Key Questions

1. Environment Standardization

How do we standardize compute environments to make metrics useful across organizations?

2. Quality Thresholds

What should we do when a package doesn’t meet our standards?

3. In-House Packages

How can organizations supplement the database with validation of internal packages?

4. Industry Adoption

What barriers prevent adoption of shared validation databases?

Metric Repository Concept

library(riskmetric)
library(riskscore)

# Assess package risk
pkg_ref <- pkg_ref("dplyr")
pkg_risk <- pkg_assess(pkg_ref)

# Calculate risk score
score <- riskscore(pkg_risk)

# Store in shared database
# Organizations can query and contribute

Learning Outcomes

✅ Understand metric repository approach
✅ Contribute to standardization efforts
✅ Plan validation strategy for your organization
✅ Network with industry validation experts

Similar Workshops

Building R Packages - Create packages to validate
pointblank - Data validation

Next Steps

Industry standards: Validation Maturity trends

Last updated: November 2025 | R/Pharma 2025 Conference

--- title: "R Validation Discussion: Metric Repos for Open Quality Assessment" subtitle: "Building a pre-built database of metrics for software validation" author: "Doug Kelkhoff (R Validation Hub)" categories: [Validation, Discussion, Advanced] --- ## Overview [Advanced]{.badge .badge-advanced} [Validation]{.badge .badge-category} [GxP]{.badge .badge-category} The R Validation Hub has built a **Metric Repository** - a pre-built database of metrics to support the software validation process. This discussion workshop explores the industry outlook for this open validation database and gathers community input on standardization and implementation. ### Discussion Topics - 🗄️ **Metric Repository** overview - 🔧 **Standardizing compute environments** - 📊 **Quality standards** for packages - 🏢 **In-house package validation** - 🔮 **Future of R validation** ## Key Packages ::: tool-tag {riskmetric} ::: ::: tool-tag {riskassessment} ::: ::: tool-tag {riskscore} ::: ::: tool-tag {val.meter} ::: ::: tool-tag {val.criterion} ::: ## Workshop Links ::: callout-note ## Resources **Regulatory Repo WG:** [github.com/pharmaR/regulatory-r-repo-wg](https://github.com/pharmaR/regulatory-r-repo-wg) **val.meter:** [github.com/pharmaR/val.meter](https://github.com/pharmaR/val.meter) **val.criterion:** [github.com/pharmaR/val.criterion](https://github.com/pharmaR/val.criterion) ::: ## Key Questions ### 1. Environment Standardization How do we standardize compute environments to make metrics useful across organizations? ### 2. Quality Thresholds What should we do when a package doesn't meet our standards? ### 3. In-House Packages How can organizations supplement the database with validation of internal packages? ### 4. Industry Adoption What barriers prevent adoption of shared validation databases? ## Metric Repository Concept ``` r library(riskmetric) library(riskscore) # Assess package risk pkg_ref <- pkg_ref("dplyr") pkg_risk <- pkg_assess(pkg_ref) # Calculate risk score score <- riskscore(pkg_risk) # Store in shared database # Organizations can query and contribute ``` ## Learning Outcomes ✅ Understand metric repository approach\ ✅ Contribute to standardization efforts\ ✅ Plan validation strategy for your organization\ ✅ Network with industry validation experts ------------------------------------------------------------------------ ### Similar Workshops - [Building R Packages](building-r-packages.qmd) - Create packages to validate - [pointblank](../clinical-reporting/pointblank.qmd) - Data validation ### Next Steps - **Industry standards:** [Validation Maturity trends](../summary/trends-insights.qmd#3-regulatory-evolution-) ------------------------------------------------------------------------ *Last updated: November 2025 \| R/Pharma 2025 Conference*