Risk-Based Quality Management (RBQM) is evolving from study-specific monitoring into an enterprise-wide capability that aligns strategic priorities with evidence generation that directly enables clinical development portfolios. Learn how organizations can scale from study-specific to enterprise RBQM. Participants will gain practical strategies to strengthen data-driven oversight, governance, and continuous learning, enabling sustainable, scalable quality management across functions and development programs. Ultimately, getting products through to patients faster through impactful risk management.

Asset- and project-level risk management is the connective tissue that starts with RBM's view of trial outcomes and widens the aperture to regulatory success and asset value across teams, functions, and organizational seams. Structured risk information, integrated with trusted operational data and continuous intelligence, activates the right workflows, shrinking the gap between knowing about a risk and acting on it—and improving the probability of success.

With study-level risk assessment firmly embedded in clinical development, organizations are increasingly recognizing the need for a broader perspective. This presentation explores how portfolio-, asset-, and process-level risk assessments uncover cross-study trends, strategic vulnerabilities, and operational challenges that may be missed at the study level alone. Learn how a multi-level risk approach can enhance decision-making, quality oversight, and development success.

Not every problem in quality and audit calls for AI. Deterministic logic, analytics, or pattern matching often beat generative models on speed, cost, and reproducibility. This session offers a practical framework for matching the tool to the problem: probabilistic versus deterministic logic, use cases from audit and disclosure workflows, new FDA expectations for documented human oversight of AI output, and a human-in-the-loop checklist attendees can apply.

Quality in drug development has long been reactive. AI offers something fundamentally different—quality that is predictive, connected, and embedded across the product lifecycle. But realizing that potential demands more than technology, it requires a shift in mindset, deliberate capability building, and a structured approach to experimentation. This talk draws on nearly three decades of quality and regulatory systems transformation to explore how organizations can move from isolated pilots to embedded AI capability across the full quality event lifecycle.

Is your quality management system trapped in a "digital illusion?" As R&D accelerates and global regulations multiply, static documents create silos that stall innovation and block the true potential of AI. This presentation outlines a strategic paradigm shift: replacing legacy file libraries with a dynamic, data-driven ecosystem. By deconstructing QMS content into granular, tagged data points, organizations can build a living, adaptable system. Join us to explore core concepts and industry use cases, and discover how structured data unlocks predictive AI, instant regulatory agility, and unprecedented operational efficiency.

ICH E6(R3) elevates Quality by Design and risk proportionality as foundational principles for clinical trial conduct, but adoption requires more than policy alignment. This session draws on FDA perspectives to explore what successful implementation looks like in practice: identifying Critical-to-Quality factors, applying fit-for-purpose quality frameworks, and aligning inspection approaches with risk-proportionate oversight. Attendees will gain actionable strategies to translate E6(R3) principles into operational reality across their organizations.

The regulatory landscape is evolving rapidly. Initiatives such as HHS's Operation Trialblazer and emerging proposals from FDA, MHRA, and other health authorities are signaling potential shifts in how clinical trials are designed, overseen, and executed. While many changes are still taking shape, today's policy discussions often become tomorrow's operational expectations. This session will explore emerging regulatory trends, their potential implications for clinical operations, and opportunities to rethink traditional approaches to trial execution. Participants will leave with practical insights and key questions to consider now in order to prepare for the future regulatory environment.

This presentation will share the journey of how a comprehensive training and change approach supported the shift from traditional oversight to risk-based thinking, helping teams build the knowledge, confidence, and behaviors required for successful RBQM adoption.

Centralized monitoring generates a significant volume of actions, but it can be difficult to know whether those actions truly reduced risk or simply closed a finding. This session shares a practical approach to measuring action effectiveness by connecting risks, signals, actions, and outcomes. I will discuss challenges, our work evaluating effectiveness, and how these insights can support more meaningful risk-based quality management.

Every signal tells a story, but not every signal represents risk. Today's CRAs are being asked to evaluate new types of data-driven insights, apply site context, and determine when action is truly warranted. This session explores how effective CRA evaluation goes beyond reviewing dashboards to uncover root causes, distinguish meaningful risk from operational noise, and make informed, consistent decisions. Attendees will gain practical strategies for translating insights into targeted actions that strengthen patient safety, data quality, site performance, and overall study execution.