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Quantum Inspired Paris Startup Applying Statistical Mechanics Designed to Unearth Therapeutic Molecules

Catching Sight

Current approaches in computational chemistry that may benefit the development of new or better drugs for people can be handled by classical computers. To date, quantum technologies have little or no influence on outcomes. Still, as time goes by and quantum information science (QIS) becomes ever more practical and implementable on a wider scale, it will start to find its uses. Some industry experts already predict improvements in areas such as lead optimization and target identification in drugs.

Quantum technology startups ApexQubit, EntropicaLabs and a dozen others see a niche on the market. Larger pharmaceutical corporations, too, are catching sight of the role quantum technologies can play in their multibillion-dollar a year business. And the ongoing COVID-19 pandemic (sorry for mentioning it, guys) is only compounding the fact of how important new drug discoveries will be to us.

Aqemia, a Paris-based in silicon drug discovery startup founded in 2019, uses deep physics and AI to unearth novel, world-beating therapeutic molecules using statistical mechanics algorithms.

But what sets Aqemia apart from some of its competitors? Simply put, it’s in its approach:

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

Aqemia

A spinout of the Ecole Normale Supérieure Paris, Aqemia’s team combines experts in medicinal chemistry, statistical mechanics and AI working together with groundbreaking algorithms from nearly a decade’s worth of research. Heading the startup are the founders, Maximilien Levesque and Emmanuelle Martiano.

The startup’s CEO is Levesque, who is a former researcher at the Ecole normale supérieure. It was his research team’s hard work in high-performance code/ML in the field of in silico early-stage drug discovery which became the basis for Aqemia’s IP and product. With a Ph.D. in quantum mechanics for solid-state physics, amazingly Levesque also conducted research at the University of Cambridge, the Sorbonne and the University of Oxford.

COO Martiano’s path was somewhat different: she gained an MS in transport and business management from Imperial College London before becoming a consultant for the likes of BC Consulting and giant BCG. A decade of that saw her move into the tentative world of entrepreneurship and cofounding Aqemia with Levesque.

 

So far her decision has been the right one. In 2019, the startup managed to raise a total of €1.6M during a Pre-Seed round led by Elaia Partner (with assistance from business angels), an investment fund focused on deep-tech startups. With this astonishing amount of money so early on, Levesque and Martiano will be able to hire key people to build out the technology.

The Future of Materials Discovery: Reducing R&D Costs significantly with GenMat’s AI and Machine Learning Tools

When: July 13, 2023 at 11:30am

What: GenMat Webinar

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Jake Vikoren

Company Speaker

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Deep Prasad

Company Speaker

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Araceli Venegas

Company Speaker

James Dargan

James Dargan is a writer and researcher at The Quantum Insider. His focus is on the QC startup ecosystem and he writes articles on the space that have a tone accessible to the average reader.

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The Future of Materials Discovery: Reducing R&D Costs significantly with GenMat’s AI and Machine Learning Tools

When: July 13, 2023 at 11:30am

What: GenMat Webinar

Picture of Jake Vikoren

Jake Vikoren

Company Speaker

Picture of Deep Prasad

Deep Prasad

Company Speaker

Picture of Araceli Venegas

Araceli Venegas

Company Speaker

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