Discovering drugs with Deep Physics and AI
What we do
Aqemia is an in silico drug discovery start-up, whose ambition is to discover rapidly more innovative therapeutic molecules with better chances of success.
How? Just like an AI can learn to play chess, Aqemia’s generative AI learns to invent relevant compounds thanks to unique Statistical Mechanics algorithms predicting drug-target affinity among other properties.
Aqemia's differentiation lies in its affinity prediction both accurate and 10 000x faster than competition, enabling us to guide efficiently our generative AI towards compounds with better chances to become drugs.
Aqemia is a spin-off of the École Normale Supérieure Paris leveraging disruptive algorithms from 8 years of research. Aqemia’s team is composed of a dozen of high profiles at the crossroads of Medicinal Chemistry, Statistical Mechanics and Artificial Intelligence.
We are a mix of Science and Business, and we love solving difficult problems on topics that matter.
I have worked as a Researcher for the past 9 years at ENS, CEA Saclay, Cambridge, Oxford, CNRS.
I specialize in statistical mechanics and artificial intelligence. I developed Aqemia core technology with my research team.
I love science, gifs and complicated stories made simple.
I have worked as a strategy consultant at BCG in the past 9 years.
I designed and executed projects with my teams for Pharma and B2B software company leaders.
I love discovering new topics and people, diving and bringing impact through science.