Aqemia raises €30M for AI-enabled drug discovery pipeline

artificial intelligence AI

Aqemia has raised €30 million ($29.5 million) in a series A funding round to scale up drug discovery, through a first-in-class technological platform combining quantum-inspired physics and machine learning.

The funding was led by Eurazeo and Bpifrance through its Large Venture fund, with the participation of previous investor Elaia.

In three years, Aqemia has grown from a spin-off of Ecole Normale Superieure to a team of 50. The company has built an innovation engine it calls the Aqemia’s Launchpad. The Launchpad has proven successful in several disclosed and undisclosed collaborations with pharmaceutical companies such as Sanofi, Janssen and Servier.

Drug discovery projects

The technology has already resulted in the launch of a proprietary pipeline of several drug discovery projects, which now range from in vitro to in vivo phases, especially in oncology and immuno-oncology.

Unlike AI-based platforms that need experimental data, Aqemia addresses drug discovery projects from the earliest stage. It does this by generating data using unique quantum physics algorithms derived from 12 years of research at the universities of Cambridge and Oxford in the U.K., and École Normale Supérieure and CNRS.

“The unprecedented pace – a whopping 10,000 times faster while maintaining costs – and accuracy of our deep physics algorithms, adding up to our generative AI, creates a unique combination that permits to generate innovative new drug candidates more quickly, and scale drug discovery projects as technology projects,” said Emmanuelle Martiano, co-founder and COO of Aqemia. 

Aqemia said its ambition is to optimize and accelerate early drug discovery projects on a massive scale in order to uncover dozens of proprietary new drug candidates. Those candidates will fuel a diversified therapeutic pipeline across a variety of targets and indications that Aqemia intends to advance into clinical trials alone through biotech spin-offs or with partners.

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