Archives: Agenda

KEYNOTE: A New Chapter for UK Clinical Trials: Regulation Reform and the Rise of AI

  • The impact of the new UK clinical trial regulations coming into force in April 2026 and what they mean for sponsors, investigators, and trial delivery
  • Government priorities and progress across the UK clinical research ecosystem two years on
  • How artificial intelligence is transforming clinical trial design, feasibility, patient identification, and operational efficiency
  • Cross-sector collaboration between regulators, industry, and the NHS to strengthen the UK’s position as a leading destination for clinical research
  • Looking ahead: building a more agile, technology-enabled clinical trials environment in the UK

PANEL DISCUSSION Harnessing Real-World Data and Registries in Clinical Trials: UK & Ireland Perspectives

  • Overview of available RWD sources and disease registries across the UK and Ireland, and how they can support trial design.
  • Leveraging RWD to inform patient eligibility, site selection, and endpoint development.
  • Practical considerations for integrating registry data with trial datasets while ensuring data quality and regulatory compliance.
  • Case studies demonstrating how RWD and registries have accelerated clinical trial insights and improved patient outcomes.

SPOTLIGHT – Innovation in Rare Disease

 

  • Analysis of Real World (Audit) Data in driving drug discovery
  • Use of RWD in driving drug discovery in rare diseases
  • Leveraging therapeutics for rare disease to larger, multiple global applications

FIRESIDE CHAT Risks & Controversies of AI in Clinical Trials

  • Automation bias in practice: Real-world cases show dosing errors occurring when clinicians rely on AI outputs without independent verification.
  • Human oversight failures: Over-reliance on AI, combined with missed pharmacist checks, can directly compromise patient safety.
  • Cognitive deskilling risk: Persistent dependence on AI may erode critical thinking, clinical judgement, and professional expertise over time.
  • Long-term human impact: Growing concern that excessive cognitive offloading to AI could contribute to reduced mental resilience and potential long-term cognitive health risks, highlighting the need for balanced human – AI interaction.