Today we’re launching The Tahoe Blog. In the same open-source spirit that led us to release Tahoe-100M—our gigascale, perturbative single-cell dataset—we’re now sharing many of the discoveries it has enabled.
Tahoe-100M isn’t just a large-scale dataset that enables the next generation of AI models in biology. It’s a new modality of data for discovery. Instead of designing a new experiment for every question, you can ask hundreds of questions—across thousands of perturbations and cancer models—with high-content, single-cell data already in hand.
This changes the game. You can answer questions you weren’t even asking. Discoveries emerge before the hypothesis. It’s part of a larger shift: from hypothesis-driven to hypothesis-generating science, from narrow to panoramic views of biology.
Think of it like the transition from Recurrent Neural Networks (RNNs) to transformers in AI. On the surface, transformers might look like scaled-up RNNs—but their ability to operate across all contexts at once unlocked entirely new capabilities.
Tahoe-100M does something similar for biology. Measuring how a handful of cancer models respond to a drug or two is common. But scaling that across thousands of models and drugs—with the resolution of single-cell data—reveals relationships and mechanisms you’d otherwise miss. That’s what makes this data more than the sum of its parts.
In this blog, we’ll highlight discoveries that surprised even us—insights hiding in plain sight, enabled only by this new scale and structure of data. We’re sharing them in hopes they’ll spark new questions, inspire new therapeutic directions, and ultimately help patients.
We begin with one such finding: We discovered previously unknown mechanisms associated with Saquinavir; mechanisms that could have predicted its cardiovascular toxicity, which were later detected during its clinical usage. The drug, which had been developed by Roche, was later discontinued in the US due to these toxicities.
Read our first blog post and stay tuned for new ones once every couple of weeks. You could also subscribe to get notified when we publish new ones.
Enjoy!
P.S. Reach out if you would like to contribute as a guest.