SpatialAgent: An Autonomous AI Agent for Spatial Biology
Hanchen Wang*, Yichun He*, Paula P. Coelho*, Matthew Bucci*, Abbas Nazir, Bob Chen, Linh Trinh, Serena Zhang, Kexin Huang, Vineethkrishna Chandrasekar, Douglas C. Chung, Minsheng Hao, Ana Carolina Leote, Yongju Lee, Bo Li, Tianyu Liu, Jin Liu, Romain Lopez, Tawaun Lucas, Mingyu Derek Ma, Nikita Makarov, Lisa McGinnis, Linna Peng, Stephen Ra, Gabriele Scalia, Avtar Singh, Liming Tao, Masatoshi Uehara, Chenyu Wang, Runmin Wei, Ryan Copping, Orit Rozenblatt-Rosen, Jure Leskovec, Aviv Regev
(* Equal contribution)
Apr 3, 2025
Abstract
Advances in AI are transforming scientific discovery, yet spatial biology, a field that deciphers the molecular organization within tissues, remains constrained by labor-intensive workflows. Here, we present SpatialAgent, a fully autonomous AI agent dedicated for spatial-biology research. SpatialAgent integrates large language models with dynamic tool execution and adaptive reasoning. SpatialAgent spans the entire research pipeline, from experimental design to multimodal data analysis and hypothesis generation. Tested on multiple datasets comprising two million cells from human brain, heart, and a mouse colon colitis model, SpatialAgent’s performance surpassed the best computational methods, matched or outperformed human scientists across key tasks, and scaled across tissues and species. By combining autonomy with human collaboration, SpatialAgent establishes a new paradigm for AI-driven discovery in spatial biology.
Type
Publication
bioRxiv