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ICH E6(R3), Demystified Part 2 | Defining Critical-to-Quality

Ethical and Actionable Trial Outcomes 

ICH E6(R3) is more than just an update to Good Clinical Practice (GCP). It represents a fundamental shift in how the industry defines quality and requires sponsors and CROs to show intelligent oversight focused on what’s Critical-to-Quality (CtQ). 

E6(R3) specifically calls for prospectively defining CtQ factors and associated risks. In this article, we explore how to identify and document CtQ factors that drive risk management and how to create a CtQ register that connects design to oversight. 

It is the second chapter in our ICH E6(R3) Demystified series which translates each core principle and training module into practical steps for sponsors, CROs, and quality leaders.
Across seven installments, we’ll show how to move from theory to action using data-driven oversight and explainable analytics – anchored in the real-world application of CluePoints’ Central Monitoring Platform (CMP).

Principles of Good Clinical Practice 

E6(R3) reinforces the ethical, scientific, and operational considerations integrated in clinical trials, emphasizing participant safety, data integrity, and regulatory compliance.  

At its core is Quality by Design (QbD) and the identification and assessment of CtQ factors and associated risks during the design of study protocols. This means study teams must define, early and explicitly, the aspects of a study that matter most and manage them proportionately to risk. 

CtQ factors are defined as trial attributes essential to protecting participants and ensuring reliable results. These factors vary by study design and context, emphasizing the need to avoid one-size-fits-all approaches. For example, in a vaccine trial, specimen handling may be a CtQ factor; in oncology, imaging consistency may be CtQ; and in decentralized trials, audit trail integrity and eCOA compliance may be CtQ. 

Implementing CtQ in Clinical Trials 

Process  Steps for CtQ implementation 
QbD  Iterative risk assessments conducted during protocol design. A cross-functional team identifies and addresses key risks associated with CtQ factors. 
Pre-Study Risk Planning  Focus on CtQ factors to frame discussions and ensure decisions are practical and data driven. Guide the study team with a critical question: “What can go wrong?” 
SDV/SDR Planning  Once site compliance is confirmed, reduce reliance on source data verification (SDV) and review (SDR). Use periodic sampling, prioritizing critical patient data. 
Risk-Based Data Management (RBDM)  Focus reviews and data checks on critical data. Use centralized analytics and machine learning to detect discrepancies efficiently and direct reviewer attention to the data that matters most. 

Running an Effective CtQ workshop 

A strong CtQ workshop is cross-functional, structured, and focused on what truly matters. E6(R3) and E8(R1) both emphasize multidisciplinary engagement — this is where that principle becomes operational. 

Who to involve 
  • Clinical Operations 
  • Data Management 
  • Biostatistics 
  • Clinical Development 
  • Medical/Safety Review 
  • Quality / GCP 
  • Central Monitoring/RBQM Lead 
  • BioMarker Management 
  • IMP Management 
  • CRO partners (when applicable) 
What to capture  Each CtQ should be documented with: 

  • The CtQ factor and rationale (scientific, operational, ethical rationale) 
  • Related critical data and processes 
  • Associated risks 
  • Severity, likelihood, and detectability 
  • Controls and mitigations 
  • KRIs and QTLs, that align to CtQs 
Question to guide the discussion 
  • What aspects of the trial must go right for interpretable results? 
  • What could go wrong and how would we know? 
  • Can risks be detected through central data or do they need to be reviewed on site? 
  • Which deviations would compromise patient safety or reliability of trial results? 

The output becomes your Study Risk Assessment, the anchor for your risk management strategy. 

Making CtQ Practical With CluePoints 

Our Central Monitoring Platform (CMP) operationalizes proportionate, data-driven oversight. The Risk Assessment module enables teams to document CtQ factors, associated risks, and controls with full version management and auditability. 

Once defined, CtQ factors are linked to risks that are monitored through KRIs and QTLs, with structured follow-up tasks supporting centralized statistical monitoring activities. This ensures that CtQs inform where and how data-driven review is applied, keeping oversight systematically focused on what matters most. 

CMP then analyzes underlying clinical and operational data using explainable statistical methods and machine learning, surfacing early signals related to CtQs and enabling rapid follow-up through the integrated Signals & Actions workflow.  

What Comes Next 

In Part 3, we’ll dive into Quality Tolerance Limits (QTLs) – how they support risk management and how to turn acceptable ranges into actionable triggers. 

Catch Up 

Part 1 of our ICH E6(R3) Demystified series focused on the shift to principle-based, proportionate oversight and the importance of building quality in.  

Catch up on Part 1 here.

Closing Thought 

Proper identification and management of CtQs through central monitoring increase the likelihood of achieving ethical and robust trial outcomes. 

CluePoints enables continuous, proactive management of CtQ risks, strengthening clinical trial quality, integrity, and operational success. 

Guide

A Comprehensive Guide to Adaptive Site Monitoring

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