Patricia Dorling

Senior Director - Health Economics, Outcomes Research & Gene Therapy Portfolio Lead Insmed

Patricia Dorling, PharmD, MS, PhD, is a global leader in Health Economics and Outcomes Research (HEOR) and Real-World Evidence (RWE), with 15+ years across oncology, rare diseases, gene therapy, and internal medicine. As Senior Director of HEOR Gene Therapy Portfolio Lead at Insmed, she leads evidence strategy for gene therapies. Previously Vice President and Head of Global HEOR & Medical RWE at Chiesi, she scaled functions for rare disease portfolios. An expert in evidence generation, HTA, and RWE innovation, she drives launches, speaks at conferences, and champions diversity through D&I networks.

Seminars

Wednesday 28th October 2026
Understand Why Evidence That Follows Guidance Still Fails to Deliver Predictable Regulatory & HTA Outcomes
11:30 am
  • Understand why aligning regulatory requirements for safety and efficacy with HTA expectations for value and cost remains inherently challenging, even with integrated evidence planning
  • Identify how subjectivity, interpretation, and uncertainty in HTA committee decision-making drive divergence between published RWE guidance and real-world acceptance
  • Design evidence strategies that realistically manage where alignment is possible, where divergence is unavoidable, and how predictability can be improved across markets and decision bodies
Tuesday 27th October 2026
Designing Decision‑Grade Real‑World Evidence That Holds Up Across Regulators, Payers & Clinical Decision-Makers
9:00 am

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

Tuesday 27th October 2026
AI/ML & Digital Innovation for Evidence Generation & Enterprise Implementation From Transparency, Trustworthiness, Governance, to Risk Mitigation
1:00 pm

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
Patricia Dorling