Building a Digital Twin Ecosystem for Clinical Trial Operations
Session details:
For digital twin applications to move beyond dashboard concepts, clinical operations teams need predictive systems that convert forecasts into executed actions. This session demonstrates how a digital twin plus agentic AI ecosystem addresses the core operational challenge: reducing critical path days while maintaining inspection readiness. Drawing from clinical operations experience, we'll examine the convergence of data integration, probabilistic modeling, and governance frameworks that make operational prediction feasible today.
- Economic foundation: Why critical path time drives OPEX exposure and timeline risk
- Three operational themes: Activation intelligence, operational synchronization, and protocol modernization
- Technical enablers: Event-driven data integration, probabilistic forecasting, and human-in-the-loop governance
- Implementation pathway: Moving from reactive reviews to proactive execution
- Guardrails and controls: Maintaining oversight while enabling intelligent automation
Stat/Standout Insight: Cancer centers show systematic activation timeline variance that's predictable rather than random, enabling operational optimization through structured forecasting and pre-approved interventions.
Key Takeaway: Organizations don't need perfect systems to begin; transparent analysis of operational realities and measured optimization can deliver measurable critical path reductions with existing infrastructure.
