Alexander Cole
Executive Director & Head of Epidemiology & Real-World Science Alexion Pharmaceuticals
Seminars
Thursday 29th October 2026
Understanding the Invisible Patient & Mapping Rare Disease Journeys Beyond Diagnosed Populations
9:50 am
- Addressing undiagnosed and misdiagnosed patients that remain invisible in traditional RWD
- Using epidemiology to inform earlier diagnosis and targeted outreach strategies
- Balancing methodological rigor and operational feasibility in rare disease evidence generation
Wednesday 28th October 2026
Panel Discussion: Breaking Down Organizational Silos Between Strategy, Science & Execution for RWE With AI
4:30 pm
- Why do AI‑driven RWE initiatives so often succeed technically but fail organizationally, and where do most companies get stuck?
- How can RWE/HEOR leaders better align data scientists, analysts, and medical experts around shared goals, methodologies, and accountability?
- What practical approaches are teams using to validate AI outputs without slowing delivery or undermining confidence in the evidence?
- How should organizations address cultural resistance and skills anxiety when AI drastically changes timelines, roles, and workflows?
- Who ultimately owns AI‑generated evidence and what governance models support innovation while protecting scientific and regulatory credibility?
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
Thursday 29th October 2026
Chair’s Opening Remarks
8:30 am
Thursday 29th October 2026
Chair’s Closing Remarks
4:00 pm
