Interview with Christina Brennan SVP Clinical Research at Northwell at Veeva R&D and Quality Summit

This video directly addresses critical operational challenges within clinical research, a core area of the pharmaceutical and life sciences industries. The discussion extensively covers the role of technology, AI, and data engineering in optimizing clinical trial operations, particularly patient recruitment, while also touching upon regulatory compliance and the need for efficient, integrated software solutions.

This video explores persistent operational bottlenecks in clinical trials, with a strong emphasis on patient recruitment challenges and the transformative role of technology and AI in addressing them. Dr. Christina Brennan, SVP Clinical Research at Northwell, discusses the need to leverage electronic medical records (EHRs) and advanced AI techniques like Natural Language Processing (NLP) to move beyond simple diagnosis codes and accurately identify eligible patients based on complex inclusion/exclusion criteria. The conversation also highlights the critical need for greater site input in protocol design to ensure feasibility and alignment with standard of care, thereby reducing protocol deviations. A significant theme is the increasing burden on study coordinators due to a proliferation of disparate technology platforms, leading to burnout, and the importance of implementing workload acuity tools to manage responsibilities effectively. Finally, the discussion touches on the evolving sponsor-site relationship, emphasizing communication and partnership, and cautiously explores the potential for AI agents to assist with protocol-related inquiries while underscoring the necessity of human oversight.

Key Takeaways:

• AI and NLP for Enhanced Patient Recruitment: There is a significant opportunity to utilize AI and Natural Language Processing (NLP) to analyze detailed EHR notes, moving beyond basic diagnosis codes to precisely identify patients meeting complex clinical trial eligibility criteria, thereby addressing a major bottleneck in trial timelines.
• Mitigating Technology-Induced Coordinator Burnout: While technology is essential, the sheer number of unintegrated platforms often creates more work for study coordinators. Sites and sponsors must prioritize technologies that genuinely reduce administrative burden and streamline workflows, rather than adding new layers of complexity.
• Criticality of Site-Centric Protocol Design: Sponsors often overlook valuable site input during protocol development, leading to designs that are impractical or misaligned with standard of care. Early and consistent engagement with sites, particularly for schedule of assessments and through revived investigator meetings, is crucial for designing feasible and compliant trials.
• Workload Acuity for Staff Retention: To combat study coordinator burnout and maintain study quality, sites should implement workload acuity tools. These tools must consider not just the number of trials, but also their complexity, screening effort, and ongoing regulatory demands to ensure fair and sustainable workload distribution.
• Human Oversight in AI-Powered Clinical Support: While AI agents show promise for assisting with protocol-related questions and data access (e.g., in line with E6R3 principles), human oversight remains paramount. In clinical research, where patient safety and regulatory compliance are critical, AI should function as a tool to augment, not replace, human expertise and accountability.