Uploaded December 2024 | Updated September 2026, 1 week ago
Test automation can help streamline the validation process, thus allowing products to be delivered to market faster and at lower costs. The challenge in using R for regulatory submissions lies in proving that the results generated are accurate, reproducible, and traceable. It can be proved through manual processes or highly automated systems with detailed audit trails.
Errors can lead to costly delays, therefore, robust testing strategies are essential for ensuring error-free submissions. Automated continuous integration (CI) pipelines provide early feedback on potential issues, while testing techniques such as snapshot tests ensure the accuracy and compliance of submitted reports. Test automation can significantly improve testing efforts by handling a vast number of scenarios that would be impossible to manage manually.
Automated testing not only reduces costs by reducing the need for manual oversight but also enhances scalability, handling large datasets and complex analyses. Moreover, it ensures software compatibility across various operating systems, and supports the reliability of open-source R packages used in regulatory environments. Test automation improves traceability by generating comprehensive logs for audits, creating confidence that the data is correct and trustworthy, especially as the software evolves.
By leveraging automation, the pharmaceutical industry can achieve consistent, reliable results, ultimately improving patient safety and accelerating the delivery of new medicines.
Interested in exploring further? Our free resources are available here: go.appsilon.com/resources-appsilon
✔️ Make sure your R and Python code meets FDA and EMA standards — explore the GxP audit: go.appsilon.com/yt-gxp-audit
___________________
0:00 Introduction and Session Overview
2:36 Economics of Test Automation
6:19 Tests as Specification
21:35 Good Automated Testing
22:47 What’s Next?
24:14 Q&A
Test automation can help streamline the validation process, thus allowing products to be delivered to market faster and at lower costs. The challenge in using R for regulatory submissions lies in proving that the results generated are accurate, reproducible, and traceable. It can be proved through manual processes or highly automated systems with detailed audit trails.
Errors can lead to costly delays, therefore, robust testing strategies are essential for ensuring error-free submissions. Automated continuous integration (CI) pipelines provide early feedback on potential issues, while testing techniques such as snapshot tests ensure the accuracy and compliance of submitted reports. Test automation can significantly improve testing efforts by handling a vast number of scenarios that would be impossible to manage manually.
Automated testing not only reduces costs by reducing the need for manual oversight but also enhances scalability, handling large datasets and complex analyses. Moreover, it ensures software compatibility across various operating systems, and supports the reliability of open-source R packages used in regulatory environments. Test automation improves traceability by generating comprehensive logs for audits, creating confidence that the data is correct and trustworthy, especially as the software evolves.
By leveraging automation, the pharmaceutical industry can achieve consistent, reliable results, ultimately improving patient safety and accelerating the delivery of new medicines.
Interested in exploring further? Our free resources are available here: go.appsilon.com/resources-appsilon
✔️ Make sure your R and Python code meets FDA and EMA standards — explore the GxP audit: go.appsilon.com/yt-gxp-audit
___________________
0:00 Introduction and Session Overview
2:36 Economics of Test Automation
6:19 Tests as Specification
21:35 Good Automated Testing
22:47 What’s Next?
24:14 Q&A
