Archives: Agenda

Statistical computing environment (SCE) is the analytical backbone of drug development — yet many organizations still operate across disconnected platforms, inconsistent language ecosystems, and fragmented data architectures that undermine reproducibility, traceability, and speed to insight. This session traces Regeneron’s end-to-end journey of engineering a validated, cloud-native statistical computing environment that unifies SAS, R, Python and Databricks, under a single governed platform using SAS Viya and Posit. Central to this transformation was reimagining how data is stored and made accessible using a shared storage layer and future ready for establishing coherent data flows and fit-for-purpose data management practices that serve both GxP-regulated submissions and exploratory analytics without duplication or drift. We examine the architectural decisions that shaped the computing and data layers, the governance and validation strategies anchored in a product-based framework, and the change management required to migrate teams from legacy, siloed workflows to a modern, standardized environment.

• Exploring practical strategies for outsourcing CDM functions to support successful clinical study delivery
• Establishing clear governance and communication models with vendors to enhance efficiency and maintain data quality and oversight
• Leveraging vendor capabilities effectively while sticking to budget and without compromising operational control

As clinical trials grow more complex across CROs, vendors, and data sources, sponsor teams are under increasing pressure to review data faster while maintaining clear oversight, traceability, and control. At the same time, many review workflows still depend on fragmented tools, manual listings, and programming queues that slow issue detection and make decisions harder to defend.

This session will explore how sponsor organizations can operationalize agentic AI in a governed, human-in-the-loop model to strengthen clinical oversight without compromising quality or compliance. We will examine a practical approach that connects data review, issue management, and decision documentation in a sponsor-controlled environment, while using AI to accelerate custom listings, triage, and review preparation.

Attendees will learn how this model can help teams move from manual, disconnected review to faster, more traceable oversight across studies and partners. The discussion will also highlight how AI-augmented workflows can support earlier signal visibility, clearer follow-up, and more inspection-ready documentation in the context of modern GCP expectations.

• Deciding which visits can safely move outside the site
• Supporting investigators with hybrid delivery
• Exploring what can be checked or verified remotely
• Integrating telemedicine into regulated studies
• Practical lessons from recent hybrid rare disease trials