Selecting the right monitoring approach is a critical decision for sponsors designing a clinical trial. It impacts not only patient safety and data integrity but also regulatory compliance, cost, and operational efficiency. Two primary strategies dominate the space: Risk-Based Monitoring (RBM) and 100% Source Data Verification (SDV). In this blog, we’ll explore the differences between the two, highlight where each is most effective, and provide strategic insights to help sponsors make an informed choice.

What is Risk-Based Monitoring (RBM)?

Risk-Based Monitoring is a data–driven, adaptive approach that focuses monitoring efforts on the most critical aspects of a clinical trial. Rather than verifying all data manually, RBM uses centralized monitoring, risk assessments, and targeted site visits to identify and mitigate issues proactively.

Key features of RBM include:

• Real-time analytics and centralized data review
• Focus on high-risk data points and trial activities
• Scalable resource allocation based on trial needs

Benefits for sponsors:

• Reduced monitoring costs
• Faster identification of emerging issues
• Efficient use of internal and outsourced resources

However, RBM is not without its risks. It requires robust data infrastructure, effective cross-functional collaboration, and a thorough risk assessment. If these elements are lacking, there is a risk of missing critical data issues.

What is 100% Source Data Verification (SDV)?

100% SDV is the traditional standard in clinical trial monitoring, involving a manual, line-by-line comparison of every data point against source documents. It is widely regarded as the safest and most conservative approach—especially in early-phase or high-risk studies.

Key features of 100% SDV include:

• Comprehensive, manual review of all source data
• In-person monitoring visits at every site
• Complete traceability for each data point

Benefits for sponsors:

• High level of confidence in data accuracy
• Perceived regulatory assurance
• Consistency with long-established industry practices

However, this approach is resource-intensive, time-consuming, and costly. In many modern trials, it does not yield significantly better data quality compared to RBM, particularly in trials generating large volumes of electronic data.

When to Use RBM vs. 100% SDV

Choosing between RBM and 100% SDV depends on the design and context of your trial. Factors to consider include trial phase, size, complexity, therapeutic area, and regulatory requirements.

RBM is best suited for:

• Large-scale, multi-site trials
• Later-phase trials (Phase II/III)
• Studies using advanced EDC systems
• Sponsors seeking to improve operational efficiency

100% SDV is most appropriate for:

• Early-phase trials and first-in-human studies
• High-risk therapeutic areas
• Trials involving vulnerable populations
• Studies requiring granular oversight and traceability

A Hybrid Approach

In many cases, a hybrid model that combines the strengths of both RBM and SDV can offer the best of both worlds. Sponsors can apply 100% SDV to critical safety data or early trial phases, while using RBM principles to streamline broader monitoring across other aspects of the trial.

Conclusion

Risk-Based Monitoring and 100% Source Data Verification each have their place in clinical research. RBM provides a modern, cost-effective, and scalable model ideal for most contemporary trials, while 100% SDV remains valuable in scenarios that demand heightened scrutiny.

At dicentra, our clinical operations experts can help you determine the best monitoring strategy for your specific trial design and objectives. Whether you’re considering a fully risk-based model, a traditional approach, or a tailored hybrid solution, we can guide you through execution and compliance.

Contact us today to discuss how to build a monitoring plan that protects your data, your patients, and your bottom line.