Astromech Raises $20 Million at $3.8 Billion Valuation to Forecast Biology’s Future
The founders of Colossal Biosciences have raised $20 million for a company that reads 3.8 billion years of evolution to predict where living systems will fail. It is valued at $3.8 billion, based on one retrospective validation and a map of 46 longevity genes.
August 21, 2026 – 4:56 pm
Astromech Founders: Ben Lamm & George Church
Credit: Colossal Biosciences
Astromech has secured $20 million at a $3.8 billion valuation to build AI that predicts how living systems will change. The company claims its models learn from 3.8 billion years of biological history. The valuation and training window align, though no one has confirmed if it’s a coincidence.
Bob Nelsen led the round, with Peak 6, NeoGenesis Capital, Builders VC, and CAZ Investments participating, as reported by GamesBeat. Total funding now stands at $60 million.
About the Founders and Their Background
Astromech was founded by Ben Lamm and George Church, the duo behind Colossal Biosciences. Colossal aims to bring back the woolly mammoth, while Astromech focuses on forecasting biology’s next moves rather than reconstructing its past.
The Dallas startup originated within Colossal, inheriting its data, including:
- A genome bank of extinct and living species
- Tools built for large biological datasets
- Ancient-DNA capability comparing old genomes with living ones to track changes over time
Astromech’s Approach and Technical Claim
Lamm describes Astromech as a forecasting solution, akin to predicting the weather using specific technology and datasets.
The platform accepts three types of input: genomic, evolutionary, and functional, and generates three types of output:
- Where a genome or population is heading
- Where it is most likely to break
- The regulatory circuits driving the change
Astromech employs ancestral state reconstruction, going beyond simple sequence inference. It reconstructs the ancestral regulatory state, including chromatin accessibility, gene expression, and functional annotation, then runs this through a Bayesian framework for calibrated confidence.
Church explains the significance:
“Most of the variations that matter for complex traits, for example, morphology and longevity, are regulatory rather than coding, so reconstructing the ancestral regulatory state, not just the ancestral protein, has the crucial explanatory power.”
Demonstrations and Achievements
Currently, Astromech is in its deep research and development phase. Its initial public demonstration maps 46 longevity-associated genes across a time-calibrated tree of life, comparing species that solved similar problems differently, such as:
- Asian elephants that resist cancer despite their size
- Bowhead whales that live over 200 years
- Brandt’s bats weighing a few grams and living past forty
- Tasmanian devils vulnerable to a transmissible cancer