LUMI-lab: A foundation model-driven autonomous platform enabling discovery of ionizable lipid designs for mRNA...

Integrating AI with robotics offers a promising approach to molecular discovery and optimization, enabling efficient exploration of vast chemical spaces. However, its application in emerging fields is often constrained by sparse historical data. Here, we introduce LUMI-lab, a self-driving platform that integrates a transformer-based foundation model with an active-learning experiment workflow to address the challenges of data scarcity. To demonstrate its potential, LUMI-lab autonomously synthesized and screened over 1,700 lipid nanoparticles (LNPs), identifying ionizable lipids with enhanced mRNA transfection potency in human bronchial cells. It discovered brominated lipid tails as a feature that improves mRNA delivery. Intratracheal administration of LNPs formulated with LUMI-6, the top-performing lipid, to mice achieved 20.3% gene editing efficacy in lung epithelial cells. These findings demonstrate LUMI-lab as a powerful, data-efficient platform for autonomous discovery and optimization of molecules, highlighting the potential of AI-driven robotic systems to advance next-generation RNA delivery technologies.