Archives: Agenda

For emerging biotechs and biopharmas, the path from early-phase trials to global development is filled with operational and strategic risk. Increasing protocol complexity, fragmented vendor landscapes, and varying regulatory expectations add layers of uncertainty. In this talk, Adam Marsh will outline key inflection points where risk can be proactively mitigated, from study design through execution and scale-up. Attendees will leave with a clearer framework for reducing execution risk while enabling faster, more confident decision-making.

• What are the biggest barriers preventing patients from enrolling in clinical trials today?
• How can sites and sponsors improve recruitment strategies to reach the right patients faster?
• What role can digital tools, data, and patient engagement play in accelerating enrollment?
• How can collaboration between sponsors, CROs, sites, and patient communities transform recruitment outcomes?

• Full regulatory compliance supported by robust documentation and end‑to‑end traceability
• Complete transparency with no hidden or unexpected costs or fees
• Streamlined management designed to avoid any additional workload for study teams

Concept

Participants work through a real inspection finding scenario using an interactive training approach that combines regulatory requirements, audit observations, and AI-supported decision-making.

Takeaway: Transferable methodology for training teams to prepare for inspections using AI while maintaining audit trail and regulatory compliance.

Artificial intelligence (AI) is transforming R&D procurement from a transactional function into a strategic, data-driven discipline across all industries. As the backbone of clinical business operations, vendor management processes are equally impacted, including onboarding, qualification, risk tracking, and governance. This session will explore how AI-enabled solutions are set to redefine traditional Excel-based workflows, promising efficiency, scalability, and strategic decision-making.

This session will explore:

• How AI transforms R&D procurement from transactional to strategic.
• New trends: Excel-based workflows are being replaced by intelligent automation.
• Vendor onboarding, risk, and governance become data-driven and scalable.
• Procurement shifts from cost control to value creation.

• Addressing logistical challenges in clinical trials for blood sample processing
• Implementing solutions to stabilize biomarkers at collection and simplify workflows

Paediatric trials bring amplified risks, tighter regulations, and higher stakes for patient safety – but the lessons learned extend far beyond children’s studies. In this case study, we examine the unique challenges of conducting a paediatric clinical trial and explore how its insights can be applied to improve planning, safety oversight, and operational efficiency in any therapeutic area.

• Navigating Complex Risk Profiles: Managing safety, dosing, and ethical considerations in vulnerable populations.
• Pharmacovigilance in Practice: Meeting rigorous monitoring and reporting demands under high scrutiny.
• Recruitment and Engagement Strategies: Overcoming barriers to participation with patients, caregivers, and advocacy groups.
• Transferable Takeaways: Applying lessons from paediatric research to accelerate and safeguard trials in all therapeutic areas.

Discover how artificial intelligence is transforming clinical research by streamlining processes from protocol design to regulatory submission. This session explores practical AI applications for overcoming recruitment challenges, ensuring ethical implementation, and shaping the future of oncology trials.

• Overcome Bottlenecks: Learn how AI breaks cycle inefficiencies in trial design and patient screening.
• Accelerate Recruitment: See how AI-driven models and molecular matching reduce screening time and failures.
• Implement Ethically: Understand frameworks for bias mitigation, data privacy, and regulatory compliance.
• Future Trends: Explore next-decade innovations like digital twins and foundation models.