3-day Virtual Seminar

AI in Clinical Research Operations

Overview

This webinar examines generative AI through the lens of clinical research operations. Instead of focusing on AI models used to generate clinical evidence or make clinical decisions, the session concentrates on the operational productivity opportunities surrounding the research process.

Attendees will explore how AI may assist with appropriate activities such as organising study-related information, preparing internal working content, summarising suitable materials, structuring communications and turning unstructured information into clearer actions or themes. The session then looks at the safeguards surrounding those uses, including accuracy checks, confidentiality, data integrity, human review and consistency with organisational procedures.

Why you should Attend

The pressure to make clinical research faster and more efficient is increasing, and AI can look like an immediate solution. But introducing it into operational work without understanding its limitations can create duplicated effort, unreliable information, confidentiality concerns and inconsistent practices across teams.

The real advantage comes from knowing where AI adds value and where it adds risk. This session helps attendees make that distinction, giving them a practical understanding of how to approach AI-supported work without losing the review, judgement and accountability expected in clinical research.

Areas Covered in the Session

• Understand where generative AI may add value across information-heavy and administrative areas of clinical research operations
  
• Explore AI-supported approaches to organising information, summarising suitable material and turning unstructured content into clearer actions or themes
  
• Consider how AI can assist with internal planning, working drafts and routine operational communications
  
• Improve the quality of AI outputs by using prompts that clearly define the task, context, boundaries and required format
  
• Recognise hallucinations, missing context and other AI limitations that can make apparently useful outputs unreliable
  
• Identify situations involving sensitive data, formal trial records, clinical judgement or regulated processes where additional controls are required
  
• Apply human review, source checking and accountability to AI-assisted operational work
  
• Consider how team guidance, governance and consistent usage boundaries can reduce fragmented or inappropriate AI adoption
  
• Evaluate AI use according to the task and its potential impact, rather than assuming one level of risk or oversight fits every clinical research activity
  

Who Will Benefit

• Clinical Research Operations Professionals
  
• Clinical Project and Programme Managers
  
• Clinical Trial Managers
  
• Clinical Research Associates (CRAs)
  
• Study Start-Up and Site Management Professionals
  
• Clinical Trial Assistants and Coordinators
  
• Vendor and Study Support Teams
  
• CRO and Sponsor Operations Professionals
  
• Managers introducing AI or digital productivity tools into clinical research functions