Aqemia is a next-generation pharmatech company generating one of the world's fastest-growing drug discovery pipeline. Our mission is to scale the drug discovery process, by leveraging a unique-in-the world technology combining quantum-inspired physics and machine learning.
Unlike usual AI-based platforms that need experimental data to train on, Aqemia tackles drug discovery projects from their earliest stage by generating its own data with unique quantum physics algorithms from 12 years of research at Oxford, Cambridge and ENS/CNRS. The unprecedented pace - 10 000x faster - and accuracy of our physics algorithms enable us to guide efficiently our generative AI to discover innovative drug candidates more rapidly, and scale drug discovery projects as tech projects.
Aqemia started in 2019 as a deeptech spin-off from École normale supérieure, with a unique, multi-awarded physics theory in the rough. In only 3 years, the company has grown to an amazing team of 50+ people, built and extended repeatedly collaborations with large pharmaceutical companies, and started its own drug discovery pipeline with multiple projects ranging from hit generation to vivo assays. Aqemia's goal is to massively accelerate research projects to be able to scale to dozens of wholly or partly owned drug candidates, placed into a constellation of biotech spin-offs to carry out the clinical trials.
Aqemia Raises €30M to Scale its Deep Physics and AI Enabled Drug Discovery Pipeline
Servier and Aqemia extend collaboration on undruggable target in immuno-oncology
Aqemia is selected by NEA as one of “the 21 most promising health tech startups of 2022 according to VCs” in Business Insider.
“None [of CNRS start-ups] sounded more cutting-edge than Aqemia” according to Fiercebiotech in a special report based on a Nature study on top academic institutions in the world.
At Aqemia you will work in a multi-disciplinary team of passionate drug hunters, AI engineers and developers who are committed to our mission of finding drugs at high pace, to cure diseases.