1. Regulatory workflows are complex but structured.
The presentation highlights that regulatory processes—spanning data management, authoring, reviewing, publishing, and health authority queries—are intricate yet follow consistent patterns. They are highly collaborative, interdependent, and mission-critical to bringing therapies from candidate nomination to market
2. AI is powerful but needs context and precision.
While AI excels at understanding and summarizing information, it struggles with reasoning and lacks domain-specific (drug development) context. Effective use of AI in regulatory work requires clear task definition—large enough to matter, but small enough to manage
3. Human-AI collaboration transforms regulatory efficiency.
When applied thoughtfully, AI can make regulatory work up to 100× faster without compromising quality—reducing months of effort to hours. Studies with Takeda and partnerships with Parexel demonstrate how AI can accelerate timelines, elevate human expertise, and make portfolio knowledge computable across programs
