As automation biology, hardware, and AI intersect, the vision of fully autonomous, self-driving labs is moving from science fiction to reality. This session explores the cutting-edge convergence of artificial intelligence, robotics, and synthetic biology—unlocking a future where biological workflows are continuously developed, executed, and optimized without human intervention. Join leading voices at the forefront of lab automation and AI-driven experimentation as they discuss the infrastructure, algorithms, and design principles required to build self-driving laboratories.

Consistent, reproducible results are the cornerstone of synthetic biology—and AI is making them more achievable than ever. This session explores how AI and automation systems are transforming lab workflows by identifying hidden variables, optimizing equipment performance, and improving reagent management. From predictions to analyses, we’ll dive into how machine learning is driving smarter decisions, greater reliability, and faster progress in experimental biology. Real-world case studies will highlight the tangible benefits of AI-powered data interpretation in streamlining operations and unlocking scientific breakthroughs.