Talk Risk-Based CDM · Clinical Data Competencies & Cross-Functional Interactions · Technology & Data Platforms · Clinical Trial Operations
Is It Time to Shift Gears in RBQM Implementation? – Arrival of RBQM 3.0
Tue, Sep 30, 2025 · 10:30–11:45 AM EDT Room 339+340, Baltimore Convention Center
About this session
Session chaired by Abby Abraham
Description:
Risk-based Quality Management (RBQM) has evolved since 2016 when ICH-E6(R2) was finalized, and many regulatory authorities adopted its principles since 2018. The initial stages of RBQM implementation faced challenges that were resolved through pilots and technology enablers like data analytics. Over time, training and change management initiatives, coupled with enhanced clinical data review processes, improved adoption in certain segments of the industry. In recent years, the application of AI and machine learning tools, along with better integration of technology with processes, has allowed for more seamless and enhanced central data monitoring. However, such implementation is yet to be democratized across the industry. Three key new developments appear poised to make RBQM the new normal and to spread its implementation more widely:
- New Guidelines: ICH-E6-R3 and downstream adoption by regulatory authorities
- Improved Accuracy in Risk and Signal Detection: Application of Small Language Models (SLMs), especially in specific therapy areas
- Agentic AI for Corrective Action: Use of agentic AI to escalate alerts for human review, particularly critical ones, through intelligent workflow automation. This supports modeling adaptive and targeted monitoring for sites and in general reducing cycle time and repetitive Tasks.
This session aims to will expand on the following:
- The impact of ICH-E6(R3) and how risk-based approaches in all activities are becoming mainstream, rather than RBQM/RBDM being a subset of the entire clinical trial execution.
- The concept of SLMs and agentic AI, exploring current use cases to demonstrate the adoption of such approaches.
- How automation facilitates the crossover from central data monitoring to more effective and holistic clinical data management, achieving RBDM.
The confluence of these three aspects can advance the model of RBQM and provide the much-needed impetus for its implementation across different functional areas, including holistic RBDM.
Speakers
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Vice President - Clinical Science and Centralized Monitoring · Precision for Medicine
Speaker
