Quantum computers to solve core problems in drug development

Kvantify, Atom Computing and AU Department of Chemistry are joining forces to pave the way for quantum computers to be able to solve challenges within molecular simulations. The research and innovation project will also accelerate the use of the technology within drug development. Innovation Fund Denmark is investing 30 million kroner in the project.

Medicine is a crucial factor for global health and the economy, but the industry is challenged by low success rates, 10-15 year-long development processes and costs of an average of 15 billion kroner for the development of each new drug.

Computer simulations of molecular processes are a vital tool for drug development, and new and more precise methods are essential for developing solutions to current challenges.

- Quantum computers offer hope that we can push the practical limit of numerical simulations and are therefore also a promising technological way out of the problems that limit the development of new medicine. But there is a need for new precise chemical methods, developed based on the special properties of the quantum computer, which can form the basis for hardware-optimized quantum algorithms, says Ove Christiansen, professor at the Department of Chemistry at Aarhus University.

These methods must then be implemented and made available to industry specialists through software that can be easily integrated into existing workflows.

Quantum computers can push the boundaries of molecular simulations

One of the pressing problems in drug development is to accurately predict how strongly a given ligand molecule binds to its biological target, which is most often a protein. The molecule's so-called binding affinity is a central parameter for screening candidate molecules for new drugs. This problem is the focus of the interdisciplinary consortium behind the new project, EarlyBIRDD, which is made possible by an investment from Innovation Fund Denmark.

Through breakthroughs in chemical computational methods, co-development of quantum hardware and algorithms, and implementation in efficient user-centric software, the consortium will provide the pharmaceutical industry with access to new technology that exploits the full potential of quantum computing to determine protein-ligand binding affinities.

"Molecular simulations are extremely challenging for conventional computers. But they translate more naturally into the language of quantum computers. This makes chemistry a really interesting place to look for the first applications of quantum computers that represent real value creation," says Nikolaj Thomas Zinner, CSO and co-founder of Kvantify and project manager for EarlyBIRDD.

Potential for major savings in industry

It is estimated that breakthroughs in computer-assisted drug development could reduce the industry's development costs by up to 50 percent. EarlyBIRDD contributes directly to this development and will ultimately create economic growth by making quantum computers a lever for innovation in the pharmaceutical industry, which alone contributes 10 percent of Denmark's GDP.

- Quantum computing hardware will continue to be developed in the coming years, but with the early fault-tolerant quantum computers, we are on the threshold of a regime where we expect the technology to have an impact on industry. Unleashing the first part of the emerging business potential requires dedicated and targeted co-development across the entire technology chain – from problem and method formulation to algorithm development, hardware implementation and software development, elaborates Nikolaj Thomas Zinner.

Collaboration between research, technology and industry

With the investment from Innovation Fund Denmark, EarlyBIRDD can establish the necessary connections between Aarhus University's expertise in theoretical quantum chemistry, Kvantify's quantum software and algorithms, and Atom Computing's scalable quantum computing hardware. This will bring the development together around a single focused project.

To ensure coordination between development and customers, a forum of industry stakeholders will be established to provide the consortium with input on functionality and performance requirements. The Alexandra Institute will contribute its expertise in user interface development as a subcontractor to EarlyBIRDD.

EarlyBIRDD is an ambitious project focusing on a rapidly developing global research area. The project will contribute to strengthening Denmark's position within quantum technology and creating new knowledge and solutions for the benefit of both developers and users of the technology.

Facts

• Innovation Fund Denmark's investment: DKK 30 million
• Total budget: 37.7 million DKK
• Duration: 4 years, starting in April 2026
• Official project title: Early fault-tolerant quantum computing – Bringing Impact by Revolutionizing Drug Discovery (EarlyBIRDD).

About the project partners

Quantify

Kvantify is a Danish startup focused on developing software and algorithms that combine the speed and precision of quantum computing with the computing power of conventional cloud computing with the aim of transforming the discovery of new molecules. The company was founded in 2022 and now employs over 40 experts in quantum algorithms, chemistry, drug discovery and computer science.

Atomic Computing

Atom Computing is an internationally leading developer of quantum computing hardware based on trapped neutral atoms. The company is based in Boulder, Colorado, and has over 100 employees. Atom Computing has recently established itself in Copenhagen and is the supplier of the Danish quantum computer Magne, which will be inaugurated in late 2026.

AU Department of Chemistry

The AU Department of Chemistry is home to one of the world's most advanced scientific environments for theoretical chemistry. Crucial to the project, the AU Department of Chemistry contributes leading expertise in quantum chemistry and the development of force fields, which will form the cornerstone for achieving faster computational speeds and developing new quantum algorithms.