Archives: Agenda

• Orchestration and model routing
• Logging, lineage and observability
• Guardrails and AI gateways
• Private AI vs public LLM trade offs

We move beyond demos and prototypes to examine what enterprise AI systems really look like under pressure, and whether firms are investing in the right problems at all.

• Where GenAI and agentic systems are genuinely delivering value today
• Why many AI programmes are optimising the wrong use cases
• The gap between lab performance and production reality
• What leading institutions are choosing not to build

Everyone’s talking about agents. We focus on what’s real, what’s working, and what still doesn’t hold up under pressure

• Where agentic capability is genuinely live in production
• Where positioning runs ahead of functionality
• The gap between demo environments and enterprise reality
• What buyers should be demanding as proof
• Technical and governance due diligence

GlobalData’s clinical trials data indicates that new trials initiated in H1 2025 has increased significantly over previous years. In addition to surprising Wall Street, this has shaken up the biopharma competitive landscape and created major opportunities for CROs, CDMOs, Pharma Tech, and consultancies. Behind the headlines, clinical trial reporting lags, shifting start dates, and withdrawals make it easy to miss where the real growth is happening.

This session breaks down what drove the surge, where the next wave is coming from, and how early signals can give you the edge on predicting future market shifts. Whether you run trials, manufacture at scale, or advise life sciences companies, this is about being prepared, before your competitors are.

• Overview of the T-cell immunotherapy landscape
• Trends in regulatory approvals and designations impacting trial timing and logistics
• Market outlook and projected growth through 2031 and the implications for supply planning
• Clinical trial insights, including leading countries and key challenges affecting trial execution

• Planning modular PMPF studies to generate evidence supporting claim refinement, new use settings, or population expansion
• Addressing gaps from initial submissions and identifying operational challenges
• Leveraging AI tools to streamline post-market data collection, identifying emerging risks earlier, and improving interpretation of real-world performance
• Using PMPF outcomes to support intended purpose expansion and/or claim updates