Members of PROMETRIKA’s Data Management (DM) team attended the recent Society for Clinical Data Management (SCDM) conference, held in Boston this year. This annual conference brings together the global data management community for discussions of the latest developments and challenges faced by DM professionals.
A major focus of this year’s conference was how developments in ‘artificial intelligence’ (AI) can be successfully leveraged to improve DM integrity and efficiency in clinical trials. Recent improvements in AI-driven tools provide a more intuitive experience for data management and sponsor teams alike, 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.
But what are some of the challenges to building confidence among sponsors and data managers in the use of AI tools? Rightfully so, while sponsors appreciate the ability to access current data, they are concerned about data security. Across the industry, careful planning is addressing data security and integrity in AI-driven systems.
Data managers share data security and integrity concerns and have additional questions about the AI-augmented workforce. Some may visualize loss of control over data review and management decisions, others may wonder if AI will affect job opportunities or retention. The industry is addressing these issues with enhanced transparency, clearly-characterized AI models, and retention of data managers in data evaluation processes.
The SCDM conference showcased the latest innovations, technologies, and insights in DM, highlighting the growing importance of AI. As the industry continues to evolve, it’s clear that AI will play a vital role in enhancing data quality, accuracy, and efficiency. Responsible AI adoption and transparency are crucial for success. PROMETRIKA’s DM team will leverage these insights, technologies, and innovations to drive excellence in clinical data management.
