Blank Bio develops RNA foundation models that learn from the molecular complexity of tumor transcriptomes to improve patient-level prediction in oncology. The company deploys its models across predictive biomarkers, prognostic biomarkers and patient trajectory modeling, and clinical diagnostics to support patient stratification, biomarker discovery, and improved test sensitivity and specificity. Blank Bio plans to use its recent seed financing to continue model development, expand collaborations with pharma and diagnostic partners, and generate new long-read RNA-seq datasets. As part of a strategic collaboration with PacBio, Blank Bio will produce PacBio HiFi long-read bulk RNA sequencing data from up to 100 fresh-frozen tumor samples, with sequencing performed at Seattle Children’s Research Institute and Kinnex libraries automated on the SPTLabtech firefly+ platform. The team includes AI scientists and engineers from Recursion, Deep Genomics, DeepMind, and Amazon and researchers from institutions including Memorial Sloan Kettering Cancer Center, Stanford, and the Vector Institute, and has published work in Nature Methods, Nature Genetics, Nature Biotechnology, ICML, and NeurIPS. The company is headquartered in San Francisco and intends to apply its models to support pharmaceutical trial design and RNA-seq–based diagnostics.

Total raised

$7M

Funding rounds

1

Latest round

Seed

Latest activity

May 2026