Tahoe Therapeutics has raised $30 million in new funding to expand its large-scale single-cell profiling efforts aimed at advancing virtual cell modeling for drug discovery. The company plans to generate a dataset comprising one billion single-cell datapoints, characterizing approximately one million drug–patient interactions.
The new initiative builds on Tahoe-100M, released earlier this year, which was described as the first gigascale perturbative single-cell dataset. Containing 100 million datapoints, Tahoe-100M has been accessed nearly 100,000 times since being made open-source. Early use cases have included AI-driven therapeutic target identification for multiple cancer subtypes and other disease contexts.
The planned billion-cell dataset will map cellular responses to tens of thousands of small molecules across diverse patient-derived samples. This scale is expected to enhance the training of biological foundation models with the goal of improving predictive accuracy for clinical outcomes and reducing failure rates in drug development.
“Our initial dataset required developing new methods for high-throughput single-cell perturbation profiling,” said Nima Alidoust, co-founder and CEO of Tahoe Therapeutics. “This expansion is intended to provide the raw material for high-dimensional AI models of human cells, enabling more robust in silico predictions of drug efficacy and safety.”