Archives: Agenda

These collaborative team-building exercises, provide a focused opportunity to work alongside your peers to tackle common clinical data management challenges and develop practical, actionable solutions. Each session begins with a concise 10-minute problem statement presented by the session lead, setting the context and clarifying the key question to solve.

Participants then move into a 30-minute “whiteboard” working session, where each table co-develops a draft framework or potential solution to the challenge. To close, each table briefly summarizes its proposed approach, allowing the wider group to compare perspectives and walk away with multiple actionable solution pathways.

Traditional clinical trial execution suffers from costly efficiency losses and heavy monitoring burdens due to manual data transcription. This session introduces a simplified, integration-free EHR-to-EDC approach that streamlines the clinical data flow. Attendees will discover how this solution enables universal site adoption, cuts transcription time by up to 80%, and achieves near 100% data accuracy at the point of entry.

Concept: This is an audience-led panel where data experts respond in real time to the most pressing data management challenges attendees are dealing with today. The conversation is driven by live Q&A with questions that have been submitted on Slido during the session

Takeaway: Attendees will leave with a clear view of the most pressing data management challenges impacting organizations right now and leave practical, immediately usable strategies to address them

• Traditional data management focuses on harmonization and data standards; but AI now requires rich metadata, semantic context, and governed relationships to effectively understand data as humans do
• Embedding and centralizing metadata, governance, and business context directly into the data platform’s process (“shift-left”) improves consistency and accuracy of context capture
• Applying this approach to SDTM and clinical submission data can help accelerate FDA submission activities by enabling AI-assisted generation, validation, traceability, and review of regulatory deliverables using a governed clinical context.

Case report forms are the foundation of clinical data collection. They determine what data is captured, how it is captured, and how much confidence there can be in the result. Yet in many organizations, forms are still built in Excel, Word, or ad-hoc formats that rarely align with EDC requirements or with each other.

This session examines how that inconsistency can affect the clinical data lifecycle from study build through regulatory submission, and explores the role of high-quality CRF design, standards, reusable content, and technology in improving consistency, efficiency, and traceability. The session will also demonstrate how these concepts can be put into practice through CRF creation and EDC execution, supported by a real-world case study.

Concept: This first session introduces a structured, repeatable approach to predicting trends and future needs in clinical data management. Through guided discussion, participants will establish a simple method to score impact vs. likelihood vs. time-to-materialize and connect forecast outputs to practical planning choices

Takeaway: Attendees will leave with a clear, step-by-step forecasting framework that they can use to consistently predict and prioritize what’s next in clinical data management