PharmaSUG US 2026

Presenter: Kristin Kelly

The imminent release of the CDISC SDTMIG v4.0 / SDTM v3.0 represents a pivotal moment for SDTM standards. As a major version update, it introduces significant changes that sponsors should begin preparing for now.

Key updates include support for Multiple Subject Instances (MSI), the transition from SUPPQUAL to Non-Standard Variables (NSVs), and metadata restructuring aligned with SDTM Model v3.0. The –BLFL variable has been removed and Sections 1–4, which provide guidance across SDTM domains, have been reorganized for improved clarity and usability.

Variables are now organized into Variable Groups, enhancing structure and interpretation. New domains such as Event Adjudication (EA) and Gastrointestinal Findings (GI) further expand the ability to handle more types of data. Also noteworthy are updates to the Protocol Deviations (DV) domain and specimen-based Findings domains.

This paper will explore what’s new in SDTMIG v4.0 and provide practical guidance to help sponsors navigate this era of transition.

Author: Seiko Yamazaki

In recent years, the increasing use of high-frequency data such as eDiaries and wearable devices has led to cases where direct conversion into SDTM results in an extreme increase in record counts and very large datasets. Under these circumstances, running CDISC compliance checks using validation tools can require excessive execution time or even fail to complete due to memory limitations or timeouts. Regulatory authorities may encounter similar challenges when receiving and reviewing such datasets, potentially causing delays in the regulatory review process. From this perspective, this presentation will discuss practical strategies that can be implemented at the SDTM design and mapping stage to reduce validation runtime, enabling attendees to manage the validation process smoothly and efficiently while avoiding memory, timeout, or execution errors.

Author: Julie Ann Hood

Behind every high-quality, CDISC-compliant SDTM dataset lies a team of data-driven heroes, each with their own unique skillsets and battle-tested expertise. In today’s clinical trials, creating and validating submission-ready datasets is rarely a solo mission. It’s a full-scale, multi-role operation that calls upon the powers of Data Managers, Standards Managers, Clinical Programmers, and Biostatisticians, each bringing something special to the fight for clean, conformant data.

Our heroes may hail from different domains, but they share a common trait: a working knowledge of CDISC standards. Whether it’s SDTM variables on an aCRF, CDASH-structured EDC systems, or routine exposure to standardized specs, each role is already familiar with the tools of the trade. This foundational knowledge becomes their secret weapon: breaking down long-standing silos and enabling smarter, more collaborative workflows than ever before.

In a world of evolving standards, AI-assisted processes, and increasing expectations for speed and accuracy, the path to submission success isn’t always linear. There’s no single “right way” to create SDTM datasets, but there are more efficient ways. Understanding the strengths of each role opens up opportunities to rethink traditional processes, distribute tasks more effectively, and innovate workflows that better leverage individual expertise.

This poster will present our SDTM Squad, outlining the signature skills and superpowers each role brings to the clinical trial data lifecycle, supercharged by emerging contributions of AI. By highlighting the strengths of this dynamic team, we’ll demonstrate that with the right strategy and collaboration, regulatory compliance can be both faster and more heroic.