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Quantum leaps in drug discovery? NobleAI joins forces with Microsoft while King’s College London aligns with Kvantify

By Brian Buntz | October 25, 2023

View of Businessman holding Quantum computing concept with qubit icon 3d rendering

[Production Perig/Adobe Stock]

The word “revolutionize” gets thrown around a lot in describing the potential of emerging technologies. But quantum computing could make good on the promise to disrupt healthcare applications ranging from drug discovery to medical imaging. Theoretically, a quantum computer with 300 quantum bits (qubits) could crunch more calculations in an instant than there are atoms in the visible universe. Because qubits can exist in multiple states at once, quantum computers can bring powerful parallel processing to fields where exploring a vast solution space is required, including drug discovery and material science.

It’s no wonder that the computing branch, which remains in its infancy, is attracting a growing amount of attention as it inches towards practical applicability. In May, Insilico Medicine said it was exploring the use of quantum computing and generative AI to help identify lead drug discovery candidates. In June, Alphabet spinoff SandboxAQ introduced a quantum-inspired computing division known as AQBioSim to speed drug discovery.

NobleAI forges collaboration with Microsoft Azure Quantum Elements

Most recently, NobleAI announced a collaboration with Microsoft Azure Quantum Elements. The deal will unite Microsoft’s high-performance computing and quantum computing with NobleAI’s science-based AI chemical and material informatics offerings. Specifically, it will integrate Azure Quantum Elements, a cloud-based service from Microsoft with offerings for chemical and materials science, with the NobleAI Reactor platform, which supports the secure experimentation of custom machine learning models trained using their own data.

The partnership aims to use the computational capabilities of Azure Quantum Elements to select promising candidates considerably faster than with traditional CPU-based simulation technology. The alliance will also unite NobleAI’s ability to model formulations and systems and Azure Quantum Elements’ high-performance molecular modeling, enabling R&D teams to model important aspects of their product, from molecules to devices to systems.

“Azure Quantum Elements aims to compress 250 years of chemistry into the next 25,” said Dr. Nathan Baker, product manager of Azure Quantum Elements, in a press release.

King’s College London aligns with Kvantify on quantum computing in drug discovery

Similarly, the Department of Chemistry at King’s College London has partnered with Danish quantum computing start-up Kvantify to explore quantum computing in drug discovery for neurological conditions such as Alzheimer’s and Parkinson’s disease. As part of the collaboration, Kvantify will provide funding and experts to work with academics and students at King’s.

In a strategic collaboration, three quantum computing experts from Kvantify are joining the Department of Chemistry at King’s College London to focus on integrating quantum technologies in research and teaching. In addition to facilitating academic and practical exposure to quantum computing for faculty and students, Kvantify will fund a postgraduate researcher focused on furthering quantum technology for drug discovery and offer internships to undergraduate students.


Filed Under: clinical trials, Data science, Drug Discovery, machine learning and AI, Neurological Disease
Tagged With: drug discovery, Healthcare Technology, high-performance computing, King's College London, Kvantify, Microsoft, molecular modeling, NobleAI, Pharmaceutical Innovation, quantum computing, R&D collaboration
 

About The Author

Brian Buntz

As the pharma and biotech editor at WTWH Media, Brian has almost two decades of experience in B2B media, with a focus on healthcare and technology. While he has long maintained a keen interest in AI, more recently Brian has made making data analysis a central focus, and is exploring tools ranging from NLP and clustering to predictive analytics.

Throughout his 18-year tenure, Brian has covered an array of life science topics, including clinical trials, medical devices, and drug discovery and development. Prior to WTWH, he held the title of content director at Informa, where he focused on topics such as connected devices, cybersecurity, AI and Industry 4.0. A dedicated decade at UBM saw Brian providing in-depth coverage of the medical device sector. Engage with Brian on LinkedIn or drop him an email at bbuntz@wtwhmedia.com.

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