Backed by Wellcome Leap program funding and selected to advance to final-stage demonstrations, Infleqtion moves forward with quantum-enabled biomarker discovery for precision oncology

Infleqtion, a global leader in quantum sensing and quantum computing powered by neutral-atom technology, announced that its quantum software team, together with collaborators at the University of Chicago (UChicago) and Massachusetts Institute of Technology (MIT), has been selected to advance to Phase 3 of the Wellcome Leap Quantum for Bio (Q4Bio) Challenge, a global program focused on demonstrating quantum-enabled solutions for human health. The news comes as Infleqtion prepares to go public through a merger with Churchill Capital Corp X (NASDAQ: CCCX).

“Phase 3 allows us to test quantum-enabled biomarker discovery end to end,” said Pranav Gokhale, CTO, Infleqtion. “We’re applying our hybrid quantum–classical workflow to real oncology data and evaluating whether quantum methods can improve feature selection on today’s hardware, not in simulations.”

Biomarker discovery, identifying molecular, genetic, or image-based features that help diagnose cancer, guide treatment, or predict patient response, requires analyzing high-dimensional, multimodal clinical datasets. Traditional tools often struggle to capture subtle or higher-order interactions across these data types. The Wellcome Leap Q4Bio program targets this challenge directly, supporting teams working to demonstrate quantum-enabled methods for human health within the next five years.

“This project only works because clinicians, biologists, and quantum scientists are designing the solution together,” added Gokhale. “That collaboration ensures the algorithms address genuine clinical needs while remaining implementable on near-term quantum hardware.”

Across Phases 1 and 2, the Infleqtion-led team built a hybrid quantum–classical workflow designed to handle the complexity of modern biomedical data. The approach combines organized preprocessing of DNA, RNA, and pathology image features with a higher-order optimization method that can capture interactions often missed by traditional techniques. The team also developed Hyper-RQAOA, a quantum routine tailored to current and near-term hardware that leverages parameter transfer techniques to greatly improve efficiency. Together, these components provide a practical way to test quantum-enabled feature selection on datasets that matter in real clinical settings.

Phase 3 transitions the effort from controlled simulations to experiments on real quantum processors. To succeed, teams must show meaningful performance on current devices and demonstrate how their methods will scale to the next generation of quantum systems. Infleqtion’s team will use this stage to tackle a more complex clinical question: forecasting treatment response in head-and-neck cancer using a curated cohort from UChicago. The goal is to determine whether quantum-in-the-loop analysis can reveal small, clinically useful biomarker sets that support precision oncology decisions.

Today’s announcement follows the release of the team’s flagship research paper, Toward Quantum-Enabled Biomarker Discovery: An Outlook from Q4Bio, now available on arXiv.

For more information, including technical details, publications, and collaboration opportunities, visit Infleqtion.com.

About Infleqtion

Infleqtion is a global leader in quantum sensing and quantum computing, powered by neutral-atom technology. Infleqtion designs and builds quantum computers, precision sensors, and quantum software for governments, enterprises, and research institutions. Infleqtion’s commercial portfolio includes quantum computers as well as quantum RF systems, quantum clocks, and inertial navigation solutions. Infleqtion is the partner of choice for governments and commercial customers seeking cutting-edge quantum capabilities. Infleqtion announced in September 2025 it plans to go public via a merger with Churchill X (NASDAQ: CCCX). For more information, visit Infleqtion.com or follow Infleqtion on LinkedIn, YouTube, and X.

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