27 Sep 2024
The 2024 Clinical Data Management Innovation Summit convened in San Francisco, bringing together renowned clinical research experts and institutions from around the world to discuss industry trends, technical challenges, and global regulatory policies. Taimei Technology was invited to participate.
In the discussion session, Yuan Shou, Global Solutions Director at Taimei Technology, and Sam Xu, Head of Business Development for the Overseas Division, delivered a keynote presentation. They shared Taimei Technology’s insights and practical cases on advancing clinical research intelligence, drawing significant attention from the experts present.
How is AI Driving Clinical Trial Transformation?
For years, clinical research has been held back by complex processes, collaboration challenges, low efficiency, and high costs, limiting the quality and effectiveness of medical innovation. The emergence of AI offers new possibilities to address these long-standing issues.
During a keynote titled “AI-Driven Innovation: Automate Trials, Accelerate Success,” Yuan Shou, Global Solutions Director at Taimei Technology, emphasized AI’s transformative role across various aspects of clinical research. The technology is now proving valuable in areas like CRF form creation, automated testing, data audits, intelligent coding, and custom function development, significantly enhancing the efficiency of Taimei’s EDC products.
Traditionally, database setup required substantial manpower and time; however, with AI support, database creation in certain disease areas can now be automated, reducing months of work to just weeks. Automated testing further shortens trial timelines, speeding up study initiation. In data auditing and verification, AI efficiently identifies potential issues, empowering data managers with a robust tool to enhance productivity.
As the volume and complexity of research projects grow, extracting value from real-time data has become a new challenge. Intelligent analysis enables real-time risk alerts and high-quality corrective guidance, allowing managers to gain actionable insights and build a valuable data repository that fuels organizational growth.
Yuan highlighted that AI can efficiently process and analyze unstructured data of varying sources, types, standards, and quality to extract valuable information. Taimei’s eCollect 6 iMensa report tool leverages these capabilities, providing project managers with real-time data governance and anomaly detection to proactively address risks. Yuan expressed confidence that AI will continue to advance and serve as a powerful assistant in the future of clinical research.
