Uploaded December 2024 | Updated September 2026, 3 weeks ago
Appsilon and ERA Sciences were recently engaged to implement a GxP-compliant instance of RStudio for a mid-size life sciences company, providing a robust environment within AWS for developing complex, reproducible statistical models in support of pharmacometric studies within Clinical Pharmacology. This case study outlines the risk-based approach to GAMP standards, classifying the statistical software installation as GAMP Category 1 infrastructure to streamline compliance. By leveraging an implementation partner like Appsilon, the team was able to utilize efficiently perform platform qualification, reducing the validation workload and ensuring a lean, efficient setup that enhances the Clinical team’s capabilities for FDA-compliant drug development and submission processes.
Key takeaways
- RStudio implementations supporting GxP decision-making must adhere to established company validation processes to ensure compliance and data integrity.
- Classifying the base installation of statistical software as GAMP Category 1 (infrastructure) enables the development and the validation of pharmacometric models, streamlining compliance efforts for the business.
- Engaging an implementation partner like Appsilon enables life sciences companies to efficiently deploy a compliant statistical platform, reducing the overall validation workload and accelerating development.
Looking for more? Our free resources are just a click away: go.appsilon.com/resources-appsilon
⚠️ If you're serious about meeting FDA and EMA standards for your R and Python code, our GxP audit can help you get there. See how it works and start today: go.appsilon.com/yt-gxp-audit
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0:00 – Introduction and Session Overview
2:45 – Statistical Software Often Installed Without GxP Compliance
6:10 – Statistical Software in the Cloud
8:27 – Case Study: Installing a Qualified Instance of RStudio on AWS
14:05 – Separating Platform Qualification from Model Validation for Sustainable Compliance
16:54 – Closing Remarks
17:35 – Q&A
Appsilon and ERA Sciences were recently engaged to implement a GxP-compliant instance of RStudio for a mid-size life sciences company, providing a robust environment within AWS for developing complex, reproducible statistical models in support of pharmacometric studies within Clinical Pharmacology. This case study outlines the risk-based approach to GAMP standards, classifying the statistical software installation as GAMP Category 1 infrastructure to streamline compliance. By leveraging an implementation partner like Appsilon, the team was able to utilize efficiently perform platform qualification, reducing the validation workload and ensuring a lean, efficient setup that enhances the Clinical team’s capabilities for FDA-compliant drug development and submission processes.
Key takeaways
- RStudio implementations supporting GxP decision-making must adhere to established company validation processes to ensure compliance and data integrity.
- Classifying the base installation of statistical software as GAMP Category 1 (infrastructure) enables the development and the validation of pharmacometric models, streamlining compliance efforts for the business.
- Engaging an implementation partner like Appsilon enables life sciences companies to efficiently deploy a compliant statistical platform, reducing the overall validation workload and accelerating development.
Looking for more? Our free resources are just a click away: go.appsilon.com/resources-appsilon
⚠️ If you're serious about meeting FDA and EMA standards for your R and Python code, our GxP audit can help you get there. See how it works and start today: go.appsilon.com/yt-gxp-audit
___________________
0:00 – Introduction and Session Overview
2:45 – Statistical Software Often Installed Without GxP Compliance
6:10 – Statistical Software in the Cloud
8:27 – Case Study: Installing a Qualified Instance of RStudio on AWS
14:05 – Separating Platform Qualification from Model Validation for Sustainable Compliance
16:54 – Closing Remarks
17:35 – Q&A
