3-day Virtual Seminar

AI for Pharmacovigilance Teams

Overview

AI for Pharmacovigilance Teams introduces the opportunities and limitations of generative AI from a drug-safety workplace perspective. The session considers information-heavy activities where AI may provide support, including organising suitable material, summarising information for internal use, structuring working content, assisting with knowledge retrieval and improving routine team productivity.

The webinar then turns to the safeguards needed in a safety-critical function. Participants will consider hallucinations, source verification, sensitive information, data quality, governance and the importance of keeping qualified professionals responsible for review and decisions. It also places these issues in the context of current regulatory developments, including the growing attention being given to AI in pharmacovigilance by major medicines regulators.

Examples and scenarios are explained within the presentation so the session remains useful without relying on live access to external AI platforms.

Why you should Attend

In drug safety, an AI-generated error is more than an inconvenience. Important context can be lost during summarisation, an output can sound authoritative while being inaccurate, and inappropriate handling of safety information can create privacy, quality and compliance concerns.

At the same time, ignoring AI completely may leave teams spending valuable time on tasks where carefully controlled AI support could improve efficiency. This webinar helps pharmacovigilance professionals understand that balance: where AI may assist, what risks require attention, and why verification and human oversight remain essential.

Areas Covered in the Session

• Understand how AI is beginning to influence pharmacovigilance and why major medicines regulators are actively examining its use
  
• Identify suitable information and productivity tasks where generative AI may support pharmacovigilance teams
  
• Explore AI-assisted approaches to summarising appropriate material, organising information, knowledge retrieval and preparing internal working content
  
• Use more controlled prompting techniques to improve context, structure and relevance when working with safety-related information
  
• Recognise hallucinations, omissions and loss of context that can make AI-generated safety information unreliable
  
• Apply source checking, human review and clear accountability before AI-assisted outputs influence subsequent work
  
• Consider privacy, confidentiality, sensitive safety information and data-quality risks when selecting AI tools or inputs
  
• Understand the importance of governance, documented processes and proportionate oversight when AI is introduced into a regulated safety function
  
• Keep AI in the role of support rather than allowing automation to replace the professional judgement required in pharmacovigilance
  

Who Will Benefit

• Pharmacovigilance Professionals
  
• Drug Safety Specialists and Managers
  
• Safety Operations Teams
  
• Pharmacovigilance Quality and Compliance Professionals
  
• Medical Information and Safety Support Teams
  
• Regulatory Affairs Professionals working with safety information
  
• Pharmacovigilance Systems and Operations Professionals
  
• CRO Safety and Pharmacovigilance Teams
  
• Managers responsible for AI adoption within drug-safety functions