ritical to Quality (CtQ) factors, cited and explained in ICH E8 (R1), are designed to confirm that a clinical study is designed to answer the research questions and to focus on monitoring variables that matter. Application of CtQ factors, as part of Quality by Design, can eliminate nonessential activities and data collection from the study. This streamlined approach, from application of CtQ factors within the Common Technical Document (CTD) dossier, can assist Health Authorities with their review of a product application. However, during an interactive Content Hub at the DIA Global Annual Meeting 2024, the DIA Good Clinical Practice & Quality Assurance Community attendee survey revealed that only 10 of approximately 150 attendees (6.7%) stated that their company used CtQ factors.

Quality by Design and Critical to Quality Factors

ICH E8 (R1) [1], section 3.2, reads: “A basic set of factors relevant to ensuring study quality should be identified for each study. … These critical to quality factors are attributes of a study whose integrity is fundamental to the protection of study participants, the reliability and interpretability of the study results, and the decisions made based on the study results.” These CtQ factors can help define categories that matter to the study team and guide them to select variables that are critical to successful study conduct, with the goal of submitting a complete Common Technical Document (CTD) dossier to Health Authorities for product approval. CtQ factors are the bird’s-eye view principles that should be consistent across a portfolio of studies. Study-level application of the principles will then focus on the ground-level detailed identification of variables to be collected in the Electronic Data Capture (EDC) systems, laboratories, etc., consistent with these CtQ principles.

From the ICH E8 (R1) perspective, two goals of CtQ factors are evident:

1. Confirm that the study is designed to answer the research questions [section 3.3]
2. Focus monitoring and source data verification efforts to critical variables that matter and reduce efforts for all other variables. [section 3.3.2]

The DIA GCP-QA Community previously introduced Who Should Be in the Room? to define which functions should contribute to RBQM activities during protocol development, study conduct, or regulatory submission. The 2024 Content Hub focused on defining CtQ factors to guide study teams on what these functions should discuss “in the room.”

Before beginning the discussion about CtQ factors, assemble a multidisciplinary, cross-functional team to allow for a comprehensive CtQ discussion. Team members should acknowledge the variety of expertise needed to facilitate constructive dialogue. Team members such as Clinical Science, Statistics, Safety, Data Management, Quality, Clinical Operations, etc., should define which key members are vital to involve in which study phase.

After beginning these discussions about CtQs, team members should focus on defining a common set of variables that matter to include within each functional area and respective study plan.

Using the protocol Schedule of Events to define which data are study-specific critical variables often results in a data set too large to effectively monitor. Instead, the DIA GCP-QA Community Core Committee proposed five (5) target areas for CtQ factors:

• Eligibility criteria to establish the protocol population
• Randomization and stratification
• Allocation of correct treatment compliant with schedule
• Primary and secondary efficacy endpoints
• Safety endpoints, such as adverse events (AEs) and labs.

Even within defined CtQ areas, not all data collected are necessarily critical variables. Eligibility criteria include variables that confirm general health (e.g., blood pressure) and do not require focus as a variable that is fundamental for protection of study participants, data quality, or the reliability and interpretability of study results. The study team can select only those eligibility variables essential to establish the patient population such as biomarkers or line-of-therapy criteria, which would require a high level of monitoring. Likewise, many variables collected to support efficacy or safety assessments can be reduced by identifying which ones are used for statistical analyses. Most other variables are noncritical, bear a lower risk, and require a lower frequency or intensity of monitoring, which aligns with the ICH risk-proportionate philosophy.

CtQ factors ideally become company-wide principles instead of determined per asset, therapeutic area, phase, or study-specific indication. Companies can expand their CtQ list to include, for example, intercurrent events leading to statistical estimands or variables strategically positioning their product for Health Technology Assessment (HTA) in the EU.

Implementation of CtQ Factors by Industry

To explore the uptake of the ICH CtQ factors, the authors verbally surveyed attendees of the Content Hub by counting raised hands in their audience of about 150 attendees and asking two questions.

1) How many critical variables does your company use?

The answer options included:

• None, 1-10, 11-25, 26-50, <50.
• Result: Only 10 attendees (6.7%) said they used CtQ factors as a driver for selection of critical variables, with a range of 1-10 critical variables.

2) Which nonefficacy critical variables would you use?

Categories included biomarkers, safety [SAE/AESI/AE leading to discontinuation of treatment], completion/disposition, randomization/stratification, PK, Labs, ECG.

Results:

1. 10 attendees voted for biomarkers
2. 20 attendees voted for AE leading to treatment or discontinuation
3. 10 attendees voted for completion/disposition
4. 10 attendees voted for randomization/stratification
5. 10 attendees voted for PK
6. 10 attendees voted for ECG.

In a follow-up question, 0 attendees voted for biostatistical estimands or Health Technology Assessment (HTA).

Free-form responses were collected to identify additional areas to consider as CtQs:

• Clinical supply
• Dosing information
• Functional endpoints, depending on how they are administered.

Next Steps

ICH and Health Authorities support implementing Quality by Design in clinical trials and risk-proportionate data and site monitoring. Leveraging Critical to Quality (CtQ) factors allows selection of a limited number of critical data. They can be defined as part of the risk assessment and promulgated to all functional area plans including the Clinical Monitoring Plan, Data Management Plan, Statistical Analysis Plan, Medical Monitoring Plan, Risk-Based Quality Management (RBQM) Plan, etc. A common set of critical variables in all functional plans sets a common approach and defines which data require the greatest scrutiny.

Functional plans may include selected supportive variables to demonstrate the validity of critical variables, such as clinical monitoring of tumor assessments to confirm correct dates of tumor progression used in the time-to-event statistical analysis in oncology trials for solid tumors. Reducing data cleaning and monitoring efforts of noncritical variables decreases site, sponsor, and CRO burden. Risk assessment can then provide a predefined approach leveraging CtQ factors to justify selection of critical and noncritical variables as part of inspection readiness.