Ångström AI (YC S24) - Gen AI molecular simulations that reproduce wetlab results

Founders

Laurence Midgley

I'm the co-founder of Ångström AI which substitutes wet lab experiments with physically accurate GenAI molecular simulations for clients in Pharma and BioTech. Before founding Ångström AI, I was a research engineer at InstaDeep (acquired by BioNTech 2023), and pursued a PhD at the University of Cambridge in generative AI models for molecular systems. I love coding and surfing, reach out if you are in the Bay Area and want to catch some waves.

Javier Antoran

Co-founder of Ångström AI, accelerating drug discovery+ development by substituting wet lab experiments with GenAI molecular simulations. My background is in probabilistic modeling and machine learning research (PhD University of Cambridge) with experience as a researcher at Google, Microsoft, and in Quant Finance. I am interested in meeting fellow founders or other people from the industry - reach out if you want to grab a virtual coffee!

About Ångström AI

Angstrom AI builds GenAI-based molecular simulations to substitute wet lab experiments in the pre-clinical drug development pipeline. We are a team of 2 PhD's and 2 Professors from the University of Cambridge who decided to start a company together after we realised how to combine breakthoughs in our research in quantum-accurate models of physics and generative AI models.

Our Biotech/Pharma clients can verify the efficacy and safety of new drug candidates using our computer simulations, which match the accuracy of wet lab experiments, but are over 100x faster. We achieve this accuracy by constraining our genAI-based simulations to obey the laws of physics, avoiding the hallucinations seen in other GenAI technologies.

Since joining YC, Angstrom AI has developed the first physically accurate gen-AI based simulation of multiple molecules interacting. We have published the first molecule water solubility results with accuracy within the error range of wet lab experiments. We have also kicked-off a 150K pilot project with a pharma company to apply our tech to estimating solubility in their drug development pipeline.