OCS Life Sciences will once again be present at the CDISC Europe Interchange. This year, the event will take place on 20–21 May in Milan, Italy. The 2026 theme is “The Future is Connected: Standards and AI Powering Digital Transformation.” Our colleagues have submitted three abstracts, and we hope that all of them will be selected. You can read the submitted abstracts here, and we look forward to discussing them with you at the event.
Simplifying CDISC queries through
user-friendly RAG-driven Copilot agents
by Luis Andre Soriano
By using Retrieval-Augmented Generation (RAG) through Copilot agents, users can streamline queries on CDISC standards. These agents allow for focused queries on foundational standard documents (e.g. SDTM Model) while being customizable to integrate user-provided knowledge bases, client standards, study-specific decisions, and system prompts. This presentation demonstrates how to create these agents and easily incorporate them into daily CDISC-related workflows to reduce the manual extraction of information from multiple documents. It presents various use cases to illustrate its practical impact on efficiency.
The data machinery behind exploratory
biomarkers
by Caro Sluijter and Ine Wolfs (argenx)
Biomarker data is fundamental for understanding disease mechanisms, assessing treatment responses, and facilitating future exploratory research. Clinical protocols commonly include the following single sentence: "Biomarker data will be collected for exploratory research." Yet this seemingly simple phrase represents a sophisticated operational and scientific framework involving data generation, coordination across multiple vendors, and complex data processing workflows encompassing ingestion, standardization, analysis, and interpretation. At argenx, we are co-creating a dedicated biomarker data team and robust process to support these data processing workflows. This presentation aims to outline strategies and challenges identified in our journey. Focus is put on data acquisition (i.e. tailored Data Transfer strategies to accommodate diverse capabilities of our vendors), data transformation and standardization (i.e. bridging scientific needs when they are ahead of CDISC SDTM), and data analysis (ADaM). We will conclude by outlining future directions to overcome current challenges and exploring opportunities for future automatization of the process.
Use case: Using CDISC standards for exploratory biomarker research
by Tom Smeets
What should be done when large volumes of unstructured exploratory biomarker data, generated to gain insight into disease mechanisms and treatment response rather than for regulatory submission, are received from multiple vendors in different formats and require analysis? The solution is data standardization, for which we applied CDISC standards. Applying CDISC standards provided a robust framework for harmonizing and organizing the data, enabling efficient and consistent analyses and thereby meeting the needs of scientists who collaborated in the design of the CDISC-like biomarker datasets. A main advantage of using CDISC standards was that the already available clinical SDTM and ADaM datasets could be seamlessly integrated with the biomarker data, supporting the biomarker analysis. This presentation will describe the strategies and solutions used to successfully address the challenges of integrating unstructured exploratory biomarker data within the CDISC standards framework.