CASE STUDY 4 University of Chicago and Wellcome Leap Q4Bio – quantum biomarker algorithms for multimodal cancer data Biomarkers are essential for cancer care, helping doctors identify the type of cancer and choose the right treatment. Yet finding reliable biomarkers that fully use the vast and complex amount of biological data collected from patients remains one of the hardest problems in oncology. Today’s approaches often rely on hundreds or thousands of data points, which are costly to measure, difficult to interpret and not always accurate. The result is an industry that spends tens of billions of dollars each year on biomarker discovery and testing, without a clear path to decreasing costs and increasing precision. With support from the Wellcome Leap Q4Bio programme, researchers at the University of Chicago, Massachusetts Institute of Technology (MIT) and Infleqtion are exploring whether quantum computing can provide a step forward. The team has concentrated on feature selection, the process of identifying the smallest set of data points that are most predictive of cancer outcomes. Their approach has shown that it may be possible to classify dozens of cancers using as few as 10 to 35 genes, instead of hundreds or thousands. Smaller, more focused biomarker sets could dramatically reduce the cost of testing, make the results easier to interpret and improve how well findings translate into real-world clinics. Early results are promising. The team has demonstrated that quantum methods can highlight patterns across large, complex cancer datasets that are hard to uncover with today’s best tools. This work is now being benchmarked against leading classical approaches and scaled towards demonstrations on new generations of quantum hardware. If successful, it could help doctors more easily determine the tissue of origin in cancers that have already spread and, in the future, predict which patients will respond best to specific therapies. We can now begin to see what resources will be needed, and how quantum could change the way we discover and use biomarkers in cancer. Alexander T. Pearson, Director, Data Science and Head/Neck Cancer Programs, University of ChicagoCASE STUDY 3 Mayo Clinic – quantum magnetocardiography for cardiac diagnostics Cardiovascular disease remains the leading cause of death globally, yet the diagnostic tools available to clinicians often face trade-offs in speed, resolution and cost. Electrocardiography (ECG) is the gold standard method to diagnose acute ischaemia in patients with chest pain. ECG does, however, have considerable limitations that contribute to over- and under-diagnosis in up to 25% of patients. Mayo Clinic is using longstanding leadership and partnerships to investigate a new modality: MCG. In collaboration with SandboxAQ, Mayo is running an observational study in Rochester, enrolling 150 patients with suspected acute coronary syndrome. The study hypothesizes that a novel quantum MCG device (CardiAQ®; SandboxAQ) and AI analysis can improve the diagnosis of coronary artery disease. Unlike traditional methods, MCG measures the magnetic fields generated by the heart, the strongest bio- magnetic source in the human body. Introduction of MCG devices in clinical settings could open up possibilities for simplified workflows, data-rich outputs and potentially earlier detection of cardiac abnormalities. The clinic now has two MCG machines on site and expects major outcomes within the next year. Mayo’s cardiology team, working closely with AI researchers, is examining how MCG data can be integrated into existing reporting and electronic medical record systems with minimal infrastructure overheads. The key challenges that have been identified are twofold. First, completing rigorous clinical research to prove MCG’s distinct advantage and cost effectiveness; second, positioning MCG as a credible platform technology within an ecosystem of competing modalities. As Mayo’s representative noted, the pathway resembles a platform adoption curve (early validation followed by network effects) as hospitals and clinics adopt the technology at scale. Looking forward, Mayo envisions two tracks. In the near term (3–5 years), MCG could become a standard fixture in major clinics, enabling effective triaging of chest pain patients. In parallel, “blue sky” research led by SandboxAQ imagines portable devices deployed in pharmacies or homes, extending preventive care into community settings. Such a proliferation could shift cardiac care from reactive interventions to proactive prevention, while also offering cost efficiencies that are critical to healthcare systems worldwide. Quantum Technologies: Strategic Imperatives for Health and Healthcare Leaders 20

Quantum Technologies Strategic Imperatives for Health and Healthcare Leaders 2025