Enterprise-Scale Transition from SAS to R in Regulated Clinical Environments: Implementation Framework, Validation Strategy, and Lessons from a Global Pharmaceutical Deployment

Abstract

—The pharmaceutical industry is at an inflection point in clinical statistical programming, with growing 
momentum to transition from proprietary SAS software to open-source R. While R offers compelling advantages in 
reproducibility, flexibility, and cost reduction, the shift in a GxP-regulated environment introduces substantial 
challenges: computer systems validation, regulatory acceptance, change management, and quality assurance at scale. 
This paper presents a structured implementation framework derived from a real-world enterprise-wide SAS-to-R 
migration executed at a leading global pharmaceutical company. The programme resulted in the design, validation, and 
deployment of CARP, a proprietary R-based clinical reporting platform built on more than 50 validated R functions, 
serving over 300 global users across five functional departments. Cumulative software licensing savings exceeded $50 
million over an eight-year projection, while reporting turnaround times decreased by an average of 55 percent across 
key clinical deliverables. Quality metrics including reproducibility scores, error rates, and audit trail completeness 
showed material improvement post-migration. The paper documents the platform architecture, the Computer Systems 
Validation (CSV) approach adopted under 21 CFR Part 11, EU Annex 11, and GAMP5 guidelines, and the four-phase 
change management strategy that enabled organisation-wide adoption. The framework described herein is intended as 
a practical reference for statistical programming organisations contemplating a similar transition in regulated clinical 
environments.