Pharma and healthcare companies are among the earliest movers in quantum computing, with many — if not all — of the world’s largest 20 pharmaceutical companies investing in this space. Last year alone, pharma giants Merck, Johnson & Johnson, Roche and Amgen filed patents relating to quantum computing. In 2023, Moderna and IBM formed a partnership to explore quantum computing and generative AI, as did AstraZeneca and Sanofi with Alphabet spinoff SandboxAQ.

A superconducting quantum computer developed in Japan by a collaboration between the Riken Research Institute and computer giant Fujitsu. Credit: Aflo Co. Ltd. / Alamy Stock Photo

Quantum computing’s advantage is speed. In 2019, an experiment pitted a quantum computer against the fastest supercomputer to perform a mathematical task. It took the quantum computer 200 seconds to resolve what would have taken its classical counterpart 10,000 years. Today’s quantum computers are still limited in size and power, and there are still tough challenges to overcome, but quantum may affect health and medicine near term, delivering earlier diagnoses, reduced time for vaccine development, and personalized treatments sooner than other applications.

Because quantum algorithms can crunch through complex, large datasets and work with numerous variables that interact in complicated ways, the technology can integrate genomics, transcriptomics and all human ’omics to make more reliable predictions than traditional computers. Quantum computing can solve protein folding problems, forecast ligand–protein binding and solve secondary structures to accelerate drug design and discovery. By optimizing patient data, quantum computers could also solve real-world problems, speeding up clinical studies and ushering in precision medicine. In August 2023, Pfizer and IBM forged a collaboration focused on integrating generative AI and quantum computing to improve clinical trial performance and speed results — for instance, by predicting trial sites that will fail to recruit participants. The power of quantum systems could upend the industry, but it is early days. “Quantum computers are not a magic bullet that will solve all the world’s problems,” says Simon McAdams, chemistry product lead at quantum computing company Quantinuum.

It is the peculiar characteristics of quantum particles that could deliver those sought-after advantages. Regular or ‘classical’ computers are binary: they solve problems using ‘bits’, which are always in one of two physical states: either one or zero. Quantum computers instead rely on ‘qubits’, which, like Schrödinger’s cat, can exist in many states at once. In the famous thought experiment, while the box is sealed and the viewer cannot see inside, the cat is alive and dead simultaneously. For qubits, this ability to exist in many possible states gives quantum computers the capacity to process huge amounts of data and provide many more potential outcomes to a problem than traditional computers.

This ‘quantum advantage’ is what pharma aims to tap into, to enable rapid in silico evaluation of myriad drug molecule targets or to characterize protein folding at speed. Boehringer Ingelheim, for instance, is using quantum algorithms to investigate the behavior of small molecules in the vicinity of proteins to predict protein–ligand binding energies. “This is an area where I am convinced that the quantum description of molecules will yield better results,” says Christofer Tautermann, head of computational chemistry at Boehringer Ingelheim.

The hot ticket in the field is to identify those real-world situations where quantum computers can outperform their classical counterparts. On 4 March, Xprize Quantum Applications announced a $5 million prize for practical applications of a quantum computer with support from Google Quantum AI and the Geneva Science and Diplomacy Anticipator foundation. The United Kingdom’s Wellcome Leap, funded by the charitable Wellcome Trust and focused on research supporting health, has recently done the same with its Q4Bio Supported Challenge Programme. The program offers a total of $50 million in funding and prizes to researchers developing quantum algorithms to solve health challenges.

But before companies can dip into the quantum advantage through software, the hardware, which is still in its infancy, must also evolve. Scaling up the processing power of quantum computers to a usable level is difficult — a problem that also comes down to Schrödinger’s cat. When a qubit is in a superposition state of ones and zeroes, it is susceptible to noise, which can transform it back into a classical bit, just like opening the lid of the cat’s box. The quest today is for fault-tolerant, or error-resistant, quantum computers.

Denmark’s Novo Nordisk Foundation (NNF) is directly investing in building a usable quantum computer. The non-profit organization, which is linked to the Novo Nordisk pharma, awarded $200 million to the University of Copenhagen in 2022 to build such a computer. This March it created a Danish center for AI advancement with tech giant Nvidia. This center will house one of the world’s most powerful AI supercomputers, which will be instrumental in developing fault-tolerant quantum computing relying on Nvidia’s CUDA-Q, an open-source hybrid quantum computing platform. The goal is to use quantum computing to improve the efficiency of generative AI for drug discovery.

“We are in it for the long haul,” says Lene Oddershede, NNF’s senior vice president for natural and technical sciences. “We’re trying to take the difficult route by aiming to make a computer that can be used for real applications in the pharmaceutical and life sciences space.” NNF is also engaged in a 12-year program that began in 2022 to develop a generally applicable quantum computer, a project to which they have contributed $212 million. It also funds the Deep Tech Lab – Quantum, a dedicated quantum accelerator for incubating young companies that operates within the Bioinnovation Institute in Copenhagen. The accelerator has six startups and hopes to attract more.

In the UK, Cambridge-based Quantinuum is working to develop quantum tools for drug discovery. It was formed by the merger of Cambridge Quantum and Honeywell Quantum Solutions, and markets its own quantum computers and algorithms such as InQuanto, a computational chemistry platform. Its industry partners include Roche, Amgen and AbbVie. “We start from the problems we want to solve and work backwards to understand the situations in which quantum computers could be useful,” says Quantinuum’s McAdams.

Amgen has used Quantinuum’s computer hardware as a first step toward computer-aided drug design. The algorithm classified peptides according to their binding affinity to a particular molecule to identify a therapeutic capable of regulating the immune response. The results, published in a preprint that is not yet peer reviewed, are a proof of concept toward the design of therapeutic proteins. A similar investigation with Quantinuum machines was conducted by AbbVie, and another by Roche to calculate protein–ligand binding energies for the BACE1 enzyme, involved in generating the β-amyloid deposits linked to Alzheimer’s disease.

Roche has also worked with quantum software company QC Ware and IBM to show that simulations run on a quantum computer, even with small-scale imaging datasets, could outperform classical computers to detect diabetic retinopathy.

“Life science is a key industry for quantum technologies,” says Frederik Flöther, chief quantum officer of QuantumBasel, part of the uptownBasel campus in Switzerland. The campus is a privately funded hub that aims to democratize access to quantum computing and build a center for quantum innovation. QuantumBasel hosts quantum computers from IBM, D-Wave Systems and IonQ, and one of its areas of interest is in health. QAI Ventures, an accelerator based in the uptownBasel campus that partners with QuantumBasel, was set up in 2023 to fund startups in quantum technology and to support the transition to quantum. In 2023, QAI Ventures invested in several companies, one of which was diagnostics company Moonlight AI. Moonlight aims to detect genetic biomarkers from high-resolution blood smear imaging. “There are lots of opportunities from an IP perspective,” says Flöther. “Quantum computing is a young technology. It’s emerging from the lab, it’s starting to come to industry, but it’s not quite there yet.”

Although commercial quantum computers are already used in a broad spectrum of applications, only one has a sole focus on health: the IBM Quantum System One, located at the Cleveland Clinic in Ohio. IBM and the Cleveland Clinic launched the computer in March 2023 as part of the Cleveland Clinic-IBM Discovery Accelerator, supported by a $500 million investment from the Ohio government and Cleveland Clinic. A similar machine is Germany’s IBM Q System One, located in Munich. It is jointly operated by IBM and the Fraunhofer Society, and it is available for researchers wanting to test whether a quantum approach will answer questions in precision oncology and more generally in the life sciences.

Finnish quantum life sciences company Algorithmiq uses the IBM-Cleveland Clinic system in combination with its own quantum AI software, Aurora, to develop light-activated drugs for cancer therapies. Aurora uses IBM’s quantum hardware for error correction, to make the software platform more practical for potential future applications. Sabrina Maniscalco, Algorithmiq’s co-founder and CEO, thinks that classical computational techniques are not sufficient to fully understand the processes at play in photodynamic cancer treatments. “We are starting to implement hybrid quantum–classical algorithms that give better performances when analyzing light–drug interactions,” she says.

The potential of quantum computing for healthcare may be clear, but investment speed bumps could slow progress. Warning signs of a ‘quantum winter’ emerged in 2023 as global spending in quantum computing halved. While blue sky investment remains high, venture capital funding is hard to come by for companies looking for later stage funding to translate into business applications. The race to the ultimate quantum computer also introduces uncertainties, as techniques such as single-photon qubits are being met with competing approaches such as neutral atoms.

“Even as a physicist, it’s hard to keep up with detailed knowledge of all the different quantum technologies, and it’s even worse if you’re an investor,” Oddershede of NNF says. In quantum, it can be hard to distinguish hot air from real content, which makes it hard to evaluate good opportunities.

What’s more, the paucity of scientists trained in deep tech could hold back the field’s growth. This is a problem that higher education institutions are keen to address. “We don’t have a sufficient number of PhDs in fields relevant for quantum technologies,” Maniscalco says. “We also see a very small percentage of women founders, especially in deep tech.”

Political obstacles are also likely to impact investment in quantum-enabled healthcare in the long-term, particularly in Europe. Because of the proprietary nature of much of the hardware involved in quantum technology, cross-platform collaboration may be difficult, which may hinder progress as innovation becomes siloed. Just as in the spheres of AI and machine learning, there will also be concerns about the confidentiality and handling of patient data and skepticism about results generated on quantum machines.

Despite the caveats, the industry remains optimistic about the timeline, with some estimates suggesting that we will start to reap the benefits of the technology by 2030. The combination of better hardware and more sophisticated quantum algorithms is lowering the barrier for progress in quantum computing. The technology may yet be too preliminary to have demonstrated significant translational benefits, but the community has confidence in the early steps that are being made, both in the technology and the software. As Oddershede concludes: “If we get exciting results, that’s enough for a start.”