Data surveillance in clinical trials: A strategic advantage in modern research

In today’s data-rich clinical trial landscape, real-time insight is no longer a luxury, it’s an expectation. As clinical trials become more complex, the need to actively monitor and interpret emerging data trends has given rise to data surveillance as a critical component of trial execution.

But data surveillance is not just a technological upgrade. It represents a shift in how sponsors, CROs, and clinical teams view their role in safeguarding data quality, enhancing patient safety, and accelerating trial success.

What is data surveillance?

Data surveillance is the continuous, proactive oversight of clinical trial data to identify signals, trends, and anomalies. It involves more than just data validation – it’s about interpreting the broader context of the data while the trial is ongoing. Instead of waiting until database lock to uncover issues, surveillance enables early detection to enable proactive action.

This approach moves beyond operational checks, and it requires data from multiple sources – such as labs, ePROs, safety reports, and site metrics – to be centralised and assessed holistically.

The goal? To mitigate risks, protect data integrity, and ensure trials stay on course.

Why it matters now more than ever

Regulatory frameworks such as ICH E6 and ICH E8 put the emphasis on sponsor data ownership and risk management. Regulators encourage a mindset that demands vigilance across the entire data lifecycle, not just at predefined milestones. They also recommend avoiding a narrow approach to data review, to ensure any signal is taken into consideration.

Data surveillance supports this evolution by enabling:

• Faster identification of issues, such as unexpected lab results or protocol deviations

• Timely intervention, reducing costly delays or amendments

• More confident decision-making, based on emerging patterns and outliers

This real-time intelligence can have a profound impact on the overall success of a study, particularly when signals come from data points that would typically only be reviewed during data analysis, where it is too late to act.

Surveillance enables faster, deeper insights

Traditionally, data review has been a linear, retrospective process. Surveillance changes that by offering parallel, continuous visibility into key data domains. With the right technology, trial teams can monitor everything from adverse event trends to lab value shifts in real time.

This speeds up statistical analysis by flagging areas for deeper exploration early on. Teams can refine their hypotheses, potentially adjusting strategies well before final analysis. Ultimately, this leads to a more accurate understanding of the true effect of a treatment, which is the cornerstone of every clinical trial.

Collaboration: The missing link

To fully realize the potential of data surveillance, cross-functional collaboration is essential. This includes data managers, biostatisticians, clinical operations, and medical teams working in unison.

Each discipline brings a unique lens:

• Data managers ensure the structure and quality of the data.

• Biostatisticians interpret the statistical meaning of signals.

• Clinicians bring the patient and therapeutic context.

• Clinical operations assess site-level implications.

When these perspectives come together around shared surveillance tools and processes, trial oversight becomes not just reactive but predictive and strategic.

Technology makes it possible. Strategy makes it valuable.

While technology platforms are fundamental to enabling real-time surveillance, the true value comes from having a clear surveillance strategy:

• What data domains are most critical to quality?

• What thresholds or patterns should trigger review?

• How will findings be communicated and acted upon?

The answers will vary by study, but the underlying principle remains: data surveillance is not about looking harder – it’s about looking smarter. It’s also about being open-minded, as trends may appear in unexpected areas.

Conclusion: A smarter future for clinical trials

Data surveillance should be treated as a core pillar of trial execution, not a peripheral function. It bridges the gap between raw data and meaningful insight, making trials more agile, responsive, and resilient.

As clinical research continues to embrace innovation, data surveillance will be key to ensuring that the speed of execution never comes at the cost of quality or safety. When embedded into the culture and workflow of a trial team, it leads to faster decisions, better outcomes, and a clearer, more controlled path to delivering treatments that make a difference.

Want to hear more about data surveillance from an expert in the domain?

Listen to this episode of the Clinical Data Talks podcast featuring Tanya du Plessis.