One of the holy grails of biology is digitally simulating a living cell. If researchers can use computers to more accurately understand how new medicines would react in the body, that could give them greater confidence when they’re tested on animals and humans. But while large language models have led to breakthroughs in modeling how proteins act, applying the same technology to simulating all the complexities of an entire cell hasn’t been as fruitful. There’s simply not enough data. But in February of this year, a startup named Tahoe Therapeutics got one step closer to that goal with the release of Tahoe-100M, a collection of 100 million different datapoints showing how different kinds of cancer cells responded to interactions with over 1,000 different molecules. This type of data–called pertubations–is crucial to training AI models, because information on how cells respond to various molecules improves an algorithm’s ability to predict how they’ll be affected by others. “We believe that the Tahoe-100M was a Mars landing moment for single-cell datasets,” Tahoe CEO Nima Alidoust, 39, told Forbes. The company was able to build this dataset less than three years after it was founded thanks to its Mosaic platform, which lets the company take “cells from many different types of patients, from all different organs and then put them together,” rather than the conventional techniques, which test cells from only one individual at a time, explained CSO and cofounder Johnny Yu. “So every time we run an experiment, we’re generating massive single cell atlases of which drugs affect which patients.”

Full report : Tahoe Therapeutics, which is building AI models of living cells, raised $30 million led by Amplify Partners at a $120 million valuation, taking its total funding to $42 million.