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Kvantify Launches Its First Product to Improve Drug Discovery

Pharmaceutical Research, Scientist holding multi well plate

Insider Brief

  • Danish quantum company Kvantify announced the launch of its first product, Kvantify Koffee.
  • The product aims to complement and reduce costly and time-consuming laboratory experiment.
  • Kvantify Koffee calculates Unbinding Kinetics, a critical parameter in screening and selecting new drug candidates.

PRESS RELEASE — In a groundbreaking advancement for computational drug discovery, Danish quantum company Kvantify is proud to announce the launch of its first product, Kvantify Koffee, today. This innovative product aims to complement and reduce costly and time-consuming laboratory experiments by calculating a critical parameter in screening and selecting new drug candidates: Unbinding Kinetics. Kvantify Koffee adds value using classical computers today and is poised to offer even greater value as quantum computer hardware matures.

With a vision to create value for both the business world and society by solving the world’s most complex computational challenges, Kvantify has specialized in optimization and simulation across multiple industries. This includes the pharmaceutical industry, financial services, logistics, and telecommunications. Now, they are launching their first commercial product, Kvantify Koffee, aimed at the discovery of new medications.

“Today, is a significant day for Kvantify. We view ourselves as problem-solvers, aiming to create groundbreaking tools that deliver value to businesses right now. Kvantify Koffee fits well within that mission. Our new product is pioneering as there is no commercial alternative available, and it can add value today through our classical computer algorithms and is prepared to deliver additional value as quantum computer hardware matures,” says Hans Henrik Knudsen, CEO and co-founder of Kvantify.

A Unique Opportunity for the Industry

Kvantify Koffee is the first commercial product designed to simulate unbinding kinetics, enabling faster and more accurate screening processes for finding new medications than before. The calculations for one molecule take minutes—the time it takes to make a cup of coffee—thus, the product can also save time and money for the pharmaceutical industry and help make new medications available faster.

“With Kvantify Koffee, we can significantly reduce the risk in the development of new medication by providing insights about a critical parameter earlier in the process. Currently, unbinding kinetics are typically calculated through laboratory experiments, which are expensive and time-consuming, or this crucial parameter is not used at all. Our long-term vision is to reduce the time from Hit-ID to lead optimization by 75% and to increase the success rates, which are currently very low. Kvantify Koffee is an important step towards this vision,” says Christina Krogsgård Nielsen, Head of Products & Strategy at Kvantify.

Kvantify has previously introduced their quantum algorithm FAST-VQE, particularly used within quantum chemistry, where the algorithm shows high precision with fewer resources than previous quantum algorithms such as ADAPT-VQE. Thus, FAST-VQE is an important contribution to the application of quantum computers for practical purposes.

For more market insights, check out our latest quantum computing news here.

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

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Matt Swayne

With a several-decades long background in journalism and communications, Matt Swayne has worked as a science communicator for an R1 university for more than 12 years, specializing in translating high tech and deep tech for the general audience. He has served as a writer, editor and analyst at The Quantum Insider since its inception. In addition to his service as a science communicator, Matt also develops courses to improve the media and communications skills of scientists and has taught courses. [email protected]

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