Oncology clinical development leaders face mounting pressure to move faster, often while making critical decisions with limited information. Predictive models and digital twins powered by real-world data (RWD) offer new ways to inform those decisions, helping accelerate timelines and improve probability of success.
This panel brings together perspectives from across the ecosystem to explore how these tools are being applied in go/no-go calls, biomarker strategy and trial design and analysis. Panelists will discuss where they already deliver value today, why data quality and transparency matter as much as the models themselves, and what's still standing in the way of broader adoption, along with strategies to address those barriers.
What you’ll learn:
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Where RWD-powered predictive models are already being used in clinical development and how they support decisions across the asset lifecycle
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What to look for in a predictive modeling solution, including data quality, methodology, and transparency
- Practical strategies for navigating data, regulatory, and adoption challenges
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