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 differentiation lies in its affinity prediction both accurate and 10 000x faster than competition, enabling efficient guidance of generation towards compounds with better chances to become drugs.
Aqemia is a spin-off of École Normale Supérieure leveraging disruptive Quantum-inspired Statistical Mechanics algorithms from 8 years of research. Aqemia’s team is composed of high profiles at the crossroads of Medicinal Chemistry, Statistical Mechanics and Artificial Intelligence.
Machine Learning Quantum AI Artificial Intelligence drug discovery in silico drug design Structure-based Statistical Mechanics
TechnologiesAI Companies (Drug Discovery) Quantum Theory in Drug Discovery
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Aqemia has a unique quantum-inspired statistical mechanics algorithm that predicts the affinity between a compound and a therapeutic target accurately and 10,000 times faster than the competition. Aqemia also has an AI that generates better and better compounds by getting feedback from the affinity predictor.
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