Several lines of evidence have 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, genetic manipulation, heterochronic parabiosis, caloric restriction, and even the use of existing drugs like Metformin. We can reproducibly use such techniques to significantly increase the lifespan of animals while delaying the onset of multiple diseases — and this evidence has been built up by world-class scientists at UCSF, Stanford, and more of the world's best labs.
We've built a machine learning platform to accelerate experimentation for discovering therapies for aging and its related diseases. While the science of aging research is full of promising results, 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, arthritis, and more. Spring Discovery's machine learning-based experimentation platform solves this. We're applying a novel computational approach to one of the most important problems in the world: battling aging and disease.
Creator: Ben Kamens