Noetik builds artificial intelligence models of tumours from huge sets of tissue images and molecular data, to predict which patients will respond to a cancer drug and to find new targets.
Noetik, founded in 2023 in South San Francisco, is an AI-native biotechnology company that has assembled one of the largest multimodal tumour datasets (spatial transcriptomics, proteomics, histology and genomics from patient samples) plus its Perturb-map in vivo functional genomics platform. On these it trains foundation models of the tumour microenvironment, including OCTO-VirtualCell, Celleporter and TARIO-2, which identifies likely responders to the checkpoint combination botensilimab plus balstilimab from routine pathology images (June 2026, following a 2025 biomarker collaboration with Agenus). Applications span trial enrichment, repositioning of clinical-stage drugs and novel target discovery. In January 2026 GSK licensed Noetik's foundation models in an anchor partnership reported at USD 50 million. Noetik raised a USD 14 million seed led by DCVC (2023) and a USD 40 million Series A (2024).
Shares Virtual cell models and in-silico perturbation screens, AI-driven drug & target discovery, Single-cell & spatial profiling.
Shares Pathology & radiology foundation models, AI in oncology roadmap: pattern readers → foundation models → agents in the workflow, AI-driven drug & target discovery.
Shares AI in oncology roadmap: pattern readers → foundation models → agents in the workflow, AI-driven drug & target discovery.
Shares Pathology & radiology foundation models, AI in oncology roadmap: pattern readers → foundation models → agents in the workflow.
Shares AI in oncology roadmap: pattern readers → foundation models → agents in the workflow, AI-driven drug & target discovery.
Shares Pathology & radiology foundation models, AI in oncology roadmap: pattern readers → foundation models → agents in the workflow.
Shares AI-driven drug & target discovery, Single-cell & spatial profiling.
Shares Pathology & radiology foundation models, AI in oncology roadmap: pattern readers → foundation models → agents in the workflow.