Aqemia combines machine learning and quantum-inspired statistical mechanics algorithms, derived from 8 years of fundamental research to generate better and more innovative leads for a given target.

Our approach

We do de novo, structure-based design of lead-like molecules by combining two technologies: 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.

In a nutshell, Aqemia's AI learns from the physics to generate better molecules.

Our differentiation

De novo drug design 

Our generative AI learns from physics rather than data. As a result, it can innovate far beyond known chemical libraries, that is, it is able to explore a large and diverse chemical space to design novel lead-like molecules for a given target. Our molecules are unique.

Structure-based approach

As we combine our AI with unique physics-based algorithms inspired from quantum, we can generate lead molecules directly from the target structure. Unlike most other AI-enabled drug discovery companies, we are not dependent on experimental datasets.

Technological breakthrough

We achieved a breakthrough in physics-based technologies, as our affinity predictor is both accurate and 10,000x faster than our competitors. Our technology is based on 8 years of research led by Aqemia's co-founder.

Accelerated discovery phase

Our AI generates in silico lead-like molecules that have better chances of meeting the target product profile, since it is guided by our high-performing affinity predictor.

Our research papers

Our technology is originally based on quantum and statistical mechanics. At its heart is a theoretical framework to compute free energies of binding between a molecule and a target in water. This theory and the underlying algorithms rely on 8 years of academic research led by Maximilien Levesque, CEO of Aqemia, while he was a research group leader at École normale supérieure — PSL / CNRS, Cambridge and Oxford. The technology is described in more than 40 peer-reviewed articles in international journals and received several awards, for instance from the American Institute of Physics.