Build Smarter and Faster Real-World Data Analytics

Turning Cost into Compounding Advantage

Learn how leading pharma organizations are switching to open-source R to modernize analytics, cut license spend, and unlock faster regulatory-grade workflows without sacrificing compliance or reproducibility.

Key Insights You Will Gain:

• Regulatory Proof, End to End : See how Federal Drug Administration reviewers successfully reproduced R submissions, including Tables, Listings, and Figures, and how R Consortium pilots established practical paths for Shiny apps and WebAssembly in submissions.
• Real Efficiency at Scale : Understand the measured 47.3 percent time reduction across data refresh tasks, how demographics and clinical characteristics hit over 50 percent improvement, and why automated report generation with Quarto reduces manual errors.
• The Business Case in Plain Numbers : Review the model for a 55-person team. Annual license savings of 698,500 United States dollars. Total first-year savings of 2.81 million United States dollars. Payback in 1.2 months. Three-year return on investment of 8.15 million United States dollars.
• Modern Data Science without Friction : Explore how R’s ecosystem of more than twenty thousand packages, Machine Learning integration, and the Tidyverse enable reproducible, publication-quality analytics, from big-data connectors to automated reporting.
• Migration That De-Risks Delivery : Walk through a step-by-step playbook for teams of fifty to sixty programmers. Pilot non-regulatory work, validate packages with risk-based methods, stand up version control and package management, and phase regulatory submissions as capability grows.
• Case Evidence You Can Reuse : See how ChatGPT-assisted migration accelerates macro rewrites, why vectorized R functions outperform legacy macro patterns, and how direct data-to-report pipelines remove transcription errors.