FAIR data principles are essential for effective collaboration in R&D. This article explores how to implement these principles in practice, with a focus on data management, sharing, and collaboration.
Delivering a compelling presentation is a key skill for scientists—and the opening minutes often matter most. New research shows that AI can evaluate just the beginning of your talk and still provide meaningful, targeted feedback. It’s a fast, low-effort way to sharpen your delivery where it really counts.
ICLR2025 showcased a surge of LLMs to diverse chemistry challenges, from retrosynthesis planning to materials discovery. A clear theme emerged — successful systems wrapped LLMs inside agentic workflows that orchestrate tasks, integrate chemical context, and refine outputs through feedback loops.
AI agents are modular, autonomous workflows powered by LLMs to solve complex tasks via a divide‑and‑conquer approach. They have the potential to automate tedious R&D tasks, such as patent analysis, freeing scientists to focus on genuine innovation.
Novo Nordisk's journey in ontology-based data management for Research & Early Development showcases the power of this approach in enhancing data accessibility, consistency, and governance.
