$30M Round Fuels Tahoe Therapeutics’ Virtual Cell Model Ambitions

In early 2025, Tahoe Therapeutics released Tahoe-100M, a dataset of more than 100 million data points detailing how cancer cells respond to over 1,000 molecules. Within months, it had been downloaded nearly 100,000 times by AI labs and research institutions. The nonprofit Arc Institute used it to build an open-source virtual cell model that doubled the predictive accuracy of earlier systems. For the San Francisco-based startup, it was validation for their goals: digitally replicating the complexity of living cells to improve the odds of developing effective drugs.

Tahoe was founded in 2022 by chief executive Nima Alidoust, chief scientific officer Johnny Yu, and established University of California scientists Hani Goodarzi and Kevan Shokat. All four have backgrounds spanning single-cell genomics, machine learning, and drug discovery. The company’s premise is that while AI has advanced in protein modeling, attempts to simulate an entire cell have been limited by the availability of large, high-quality datasets.

Creating Massive, High-Resolution Cellular Datasets

Tahoe’s primary offering is Mosaic, a platform that organizes patient-derived cancer cells into “cell villages” to reduce variability and data quality issues. The cells are exposed to small molecules, many of which form the basis of medicines, and their reactions are measured using single-cell RNA sequencing. This method, known as scRNA-seq, produces more granular data than older single-cell transcriptomics techniques.