Explore the Agenda
9:00 am Designing Decision‑Grade Real‑World Evidence That Holds Up Across Regulators, Payers & Clinical Decision-Makers
This interactive workshop brings together leaders across epidemiology, biostatistics, HEOR, and market access to examine where RWE breaks down in practice, and how to design evidence that consistently delivers decision impact.
This workshop will gather experts to discuss:
- Identifying where RWE fails to translate into regulatory, payer, and clinical decisions despite strong methodology
- Understanding how different stakeholders interpret uncertainty, bias and evidence strength, and why alignment breaks down even with high-quality data
- Balancing data complexity with clarity by ensuring analytical approaches, including advanced methods and AI, remaining interpretable and decision‑relevant
- Applying statistical and epidemiological rigor to improve comparability, mitigate bias, and ensure outputs are credible across use cases
- Designing evidence strategies earlier in development that align with downstream
decision needs to reduce rework, delays, and missed impact
12:00 pm Lunch Break & Networking
1:00 pm AI/ML & Digital Innovation for Evidence Generation & Enterprise Implementation From Transparency, Trustworthiness, Governance, to Risk Mitigation
This interactive workshop moves beyond theoretical AI discussions to focus on practical, regulated, decision‑grade adoption of AI (including agentic AI) in real‑world evidence environments. The session will emphasize governance tradeoffs, enterprise implementation realities, and lessons learned from what has genuinely scaled, and what has failed.
This workshop will gather experts to discuss:
- What Has Fundamentally Changed with AI, Agentic AI, and Digital Innovation in RWE
- Trust, Transparency, and Trustworthiness Across the Data Lifecycle
- From Generic AI to Pharma‑Specific, Decision‑Grade Use Cases
- Governance, Validation, and Risk Mitigation in Regulated Environments
- Enterprise Implementation Lessons on Where AI Has Delivered & Where It Has Failed
- Building organizational readiness for AI‑enabled RWE