Tahoe Therapeutics Raises $30M to Build World’s Largest Dataset for Training AI Models of Human Cell

One billion cells to power the next generation of AI models in biology

SAN FRANCISCO--(BUSINESS WIRE)--Tahoe Therapeutics today announced $30 million in new funding to build the definitive foundational dataset for training Virtual Cell Models. With this, the team will generate one billion single-cell datapoints, mapping one million drug-patient interactions, a scale previously impossible. The dataset will support the discovery of new precision medicines for cancer and beyond. Tahoe will also select a single partner to share the data and accelerate translation to clinical outcomes.

The round was led by Amplify Partners, joined by a distinguished group of investors including Databricks Ventures, Wing Venture Capital, General Catalyst, Civilization Ventures, Conviction, Mubadala Capital Ventures, and AIX Ventures.

The raise follows the release of Tahoe‑100M, the world’s first gigascale perturbative single-cell dataset, which has become foundational for teams building virtual cell models, ranging from major AI labs to focused research institutions. Open-sourced just a few months ago, Tahoe-100M has been downloaded nearly 100,000 times. The dataset and the models trained on it have already led to the discovery of promising new therapeutic candidates for major cancer subtypes as well as novel targets across multiple modalities.

Tahoe is now expanding on that foundation: the company plans to generate one billion single-cell datapoints, mapping how tens of thousands of drug molecules interact with human biology. This new dataset will expand the boundaries of biological foundation models, aiming to reduce clinical trial failure rates and accelerate the development of precision medicines.

“Building Tahoe-100M required us to invent new ways to generate single-cell data,” said Nima Alidoust, co-founder and CEO of Tahoe Therapeutics. “Now, we’re applying that superpower to go 10x further. This next phase is about using these massive datasets to bring about the GPT moment for AI models of human cells, translating insights to clinical readouts, and developing new medicines with much lower clinical failure rates.”

With the new capital, Tahoe is advancing its own therapeutic programs toward the clinic, while also launching a new model of strategic collaboration. The company will select a single partner, a pharmaceutical or AI company with complementary strengths, to access the forthcoming dataset. Together, the goal is to develop the first medicines powered by virtual cell models, combining Tahoe’s data with the partner’s clinical or modeling expertise.

“While structural models have accelerated molecular design, they rarely translate to clinical success — a problem that remains one of the biggest challenges in drug development,” said Sunil Dhaliwal, General Partner at Amplify Partners. “Tahoe Therapeutics is uniquely positioned to move the industry past this bottleneck by generating massive drug-patient datasets and training high-dimensional, cell-based AI models. We’re proud to back this exceptional team as they combine biology and computation to accelerate clinical impact.”

Tahoe founders, Nima Alidoust, Johnny Yu, Hani Goodzari, and Kevan Shokat hold deep experience in single-cell genomics, ML, and drug discovery. The company’s platform makes large-scale, single-cell drug screening across diverse patient contexts not only possible, but scalable. Built on scientific breakthroughs at UCSF, Tahoe is creating the raw materials needed to train disease-relevant foundation models of human cells and chart a new course for precision medicine.

To learn more, visit: www.tahoebio.ai

About Tahoe Therapeutics

Tahoe Therapeutics is building AI-powered models of the human cell to design better drugs for more patients. Its technology platform generates large-scale, perturbative single-cell datasets that enable a new generation of biological foundation models. Based in South San Francisco, Tahoe was founded by a team of scientists and technologists advancing the frontiers of drug discovery, genomics, and machine learning.