Code that Cures: Validating GxP-Compliant R Shiny Apps for Clinical Decisions - Emily Yates

Abstract: GxP-relevant R Shiny application validation ensures compliance and data integrity in regulated industries. This complex process relies on three key pillars: people, technology, and processes. A cross-functional team is crucial, comprising an R champion to drive initiatives, technical experts to implement infrastructure, and QA partners to guide regulatory adherence. Essential technologies include validated infrastructure and packages, forming the foundation for reliable application development. Processes should align with GAMP 5 guidelines and incorporate risk-based Software Development Life Cycle (SDLC) principles, such as documented user requirements and robust code testing. This overview serves as a starting point for those interested in building validated R Shiny applications, highlighting the importance of collaboration, risk-based approaches, and continuous learning. By following these guidelines and leveraging available resources, organizations can successfully implement and maintain validated R Shiny applications in GxP environments, ensuring regulatory compliance and operational efficiency.

Resources mentioned in the talk:
- GAMP 5: Good Automated Manufacturing Practices [ Ссылка ]
- PHUSE Open Source Technology in Clinical Data Analysis - FAQs for using R in Pharma: [ Ссылка ]
- Regulatory Compliance and Validation Issues: A Guidance Document for the Use of R in Regulated Clinical Trial Environments [ Ссылка ]
- R Validation Hub [ Ссылка ]
- {renv} Project environments in R [ Ссылка ]
- A Risk-Based Approach for Assessing R Package Accuracy Within a Validated Infrastructure [ Ссылка ]
- Phuse Open Source Technology in Clinical Data Analysis [ Ссылка ]
- R Package Validation Framework [ Ссылка ]
- R Package Qualification: Automation and Documenttion in a Regulated Environment [ Ссылка ]
- External R Package Qualification Process in Regulated Environment [ Ссылка ]
- Atorus Openval [ Ссылка ]
- Software Development Life Cycle: A Description of R's Development, Testing, Release and Maintenance Process [ Ссылка ]
- R Package Oriented Software Development Life Cycle in Regulated Clinical Trial Environments [ Ссылка ]
- {testthat} Unit testing for R [ Ссылка ]
- {shinytest2} Testing for Shiny applications [ Ссылка ]

Presented at the 2024 R/Pharma Conference

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