Archives: Agenda

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.

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

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.

• Key trends reshaping clinical data management and how leading teams are responding
• Looking at the biggest operational and technology challenges and overviewing practical solutions
• What to expect over the next 3–5 years and how to stay ahead in capability, speed, and quality

• Defining agentic AI and its capabilities to understand how it works and how it differs from automation and traditional rule-based workflows
• Understanding where it fits in regulated clinical environments and how it could be used to enhance clinical processes
• Evaluating real-world use cases and identifying actionable opportunities to scale and apply Agentic AI in data teams

• Turning unstructured data transfer agreements and operational workflows into validated, version-controlled intake configurations
• Automating schema mapping, transformation, reconciliation, quality control, and schema-drift detection
• Combining AI-assisted configuration with deterministic execution, traceable evidence, and human exception review