The healthcare industry is drowning in AI hype, yet pharmaceutical companies remain stuck with HEOR methodologies that were designed for a pre-AI healthcare landscape. HEOR is a €1.6+ billion market growing at a 12%+ annually, resulting in a significant investment for pharma already today but even more in the future, as the market is projected to reach €3-5 billion by 2031. While everyone talks about OpenAI, Microsoft, and Anthropic turning healthcare analytics upside down, the reality is that broad-based LLMs are fundamentally unacceptable for healthcare, particularly pharmaceutical cost-effectiveness modeling due to critical data security and regulatory compliance barriers.
Traditional HEOR modeling faces a critical bottleneck: static, time-intensive analyses that take at least 3-9 months to develop, cost millions, and cannot adapt to real-time market dynamics. Meanwhile, cloud-based AI solutions require exposing proprietary patient/cost data to third-party servers - a non-starter for regulated companies navigating complex pricing negotiations and value-based care contracts.
Because of these critical questions, pharmaceutical companies are in need of dynamic solutions that allow them to rapidly process and interpret sensitive clinical trial, patient, and cost data on-premise, saving time and resources without compromising their competitive advantage and reputation.
This presentation outlines a new architectural approach that tackles these problems: enabling real-time, conversational health economics intelligence while keeping all sensitive data secure and compliant with regulatory requirements.
We will demonstrate how next-generation HEOR can transform treatment selection and therapy reimbursement negotiations where traditional cost-effectiveness models fail to capture patient heterogeneity and rapid treatment / cost evolution.Learning objectives:
1. Understand limitations of current HEOR modeling approaches in dynamic healthcare markets
2. Explore how edge AI addresses pharma's data security concerns while enabling necessary analytics for drug development and commercial strategies
3. See practical applications of conversational HEOR in complex therapeutic areas
4. Identify opportunities for pilot partnerships to validate next-generation health economics approaches
Target audience: Market access directors, HEOR analysts, health economics consultants, and digital health leaders seeking to modernize evidence generation workflows while maintaining regulatory compliance and data security.
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