THOUGHT LEADERSHIP

Building a robust and efficient electronic data capture system (EDC) for today’s complex clinical trials is a major undertaking. The elements of the EDC must be carefully planned, the programming must be succinct, and the risks to data integrity must be considered. Clearly, these crucial requirements demand careful thought and can be time-consuming. An option for the timely initiation of a trial may be to split the release (a.k.a., the “go-live”) of EDC elements in a controlled and considered manner. PROMETRIKA’s Data Management team has extensive experience with planning and executing successful split-release EDCs.

Sponsors of global trials face many challenges. One of the most sensitive concerns is appropriate collection and handling of clinical data. Data managers face variation in data collection methods and clinical trial practices among the countries or regions participating in a global trial. PROMETRIKA’s successful approach to data integrity includes strong global oversight and advanced technology and processes.

The PROMETRIKA team attended the Fierce Biotech Week conference, which offered a front row seat to the evolving landscape of clinical research, where innovation is not just a buzzword but a driving force. The conversations centered around the growing adoption of Risk-Based Quality Management (RBQM) and the ongoing evolution of the Trial Master File (TMF) as a critical tool for inspection readiness. These topics not only dominated sessions and panels, they sparked dynamic roundtable discussions, signaling a shift in how the industry is approaching trial efficiency, compliance and data integrity.

At PROMETRIKA, we continuously evaluate how emerging technologies can strengthen clinical trial execution, compliance, and data integrity. As trials become more complex and adaptive, systems like Interactive Response Technologies (IRT) - also known as Randomization and Trial Supply Management (RTSM) – need to adapt accordingly to keep up with the increased demands of these trial designs.

The development of ‘artificial intelligence’(AI)-driven tools for data management has accelerated in the past few years. The promise of these systems is to provide a more intuitive experience for data management and sponsor teams, making it easier to track trends, spot anomalies, and generate near-real time data reports. These features, combined with AI’s ability to learn from data, make these tools a modern essential for improving data quality and accelerating clinical trials.