用大模型模拟医械监管博弈，看懂合规与创新的动态平衡
Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework
- 构建监管方、厂商等多智能体，结合大模型实现动态交互仿真
- 揭示监管变化如何影响企业合规策略与市场创新行为
- 为监管机构和厂商提供可落地的合规优化与战略决策参考
全球监管政策日益复杂，给医疗器械制造商带来持续合规与市场准入挑战。同时，监管机构需有效监控企业响应并制定战略监督方案。本研究采用增强型大语言模型的多智能体建模方法，模拟监管动态，分析监管机构、制造商及竞争者等关键主体的适应性行为。各智能体在基于监管流理论的仿真环境中运行，捕捉监管变动对合规决策、市场适应及创新策略的影响。研究揭示了监管变革对产业行为的深层影响，识别出优化监管实践、提升合规效率与促进创新的战略机遇。通过融合多智能体系统与大语言模型，本研究为应对医疗器械行业不断演进的监管环境提供了新视角与可操作洞察。
原文摘要 · Abstract (English)
The increasing complexity of regulatory updates from global authorities presents significant challenges for medical device manufacturers, necessitating agile strategies to sustain compliance and maintain market access. Concurrently, regulatory bodies must effectively monitor manufacturers' responses and develop strategic surveillance plans. This study employs a multi-agent modeling approach, enhanced with Large Language Models (LLMs), to simulate regulatory dynamics and examine the adaptive behaviors of key actors, including regulatory bodies, manufacturers, and competitors. These agents operate within a simulated environment governed by regulatory flow theory, capturing the impacts of regulatory changes on compliance decisions, market adaptation, and innovation strategies. Our findings illuminate the influence of regulatory shifts on industry behaviour and identify strategic opportunities for improving regulatory practices, optimizing compliance, and fostering innovation. By leveraging the integration of multi-agent systems and LLMs, this research provides a novel perspective and offers actionable insights for stakeholders navigating the evolving regulatory landscape of the medical device industry.
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