San Francisco, California, United States of America
Ben Kamens
2017
11
Private company
Series A
22.3
The Longevity Fund, First Round, Sam Altman, Felicis Ventures, General Catalyst
machine learning for drug discovery
Several lines of research recently bolstered the belief that by understanding and treating the damage that accumulates in our bodies as we age, we will be able to slow or repair this damage with dramatic benefits for our health and lifespan.
The most studied lines of evidence for this claim are focused on the fields of senescence, caloric restriction, parabiosis, and even the use of existing drugs like Metformin. We can reproducibly use these fields to increase the lifespan of animals while delaying onset of multiple diseases — and this evidence has been built by world-class scientists at UCSF, Stanford, and more of the world's best labs.
While aging research holds enormous promise, it still takes far too long to run experiments. This significantly slows down the search for therapies that could one day reduce cardiovascular disease, neurodegenerative diseases, and more.
We’ve built a machine learning platform to accelerate experimentation for discovering such therapies, combining cell- and tissue-based assays with a novel computational approach to tackle one of the most important problems in the world: battling aging and its diseases.