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Quantum Information Science & Technologies for Biomedical Applications
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Topic Description
Post Date: April 9, 2026
Expiration Date: April 9, 2027
Quantum technologies harness the principles of quantum physics to make measurements at the sub-atomic length scale to extend and enhance classical capabilities. Their coherence-driven properties deliver unprecedented spatial resolution and sensitivity, enabling near-term, real-world biomedical applications. These approaches can detect subtle biological changes, simulate complex biomolecules, and power next-generation imaging, diagnostic, and computational platforms.
Although many emerging quantum technologies have yet to be fully explored in biomedical contexts, continued development and optimization could dramatically enhance biomedical and clinical research. This creates unique opportunities to advance biomedical discoveries through both the development of novel quantum approaches and the integration of quantum technologies with classical systems, extending their capabilities for human health in ways not previously possible.
Topics of interest:
- Quantum-enhanced imaging methods and other innovative approaches that enable new biologically relevant measurements and facilitate early disease detection.
- Next-generation quantum diagnostics, including in-vitro platforms such as lab-on-a-chip and microfluidic systems, for highly precise and sensitive biological and point-of-care measurements.
- Optoelectronic biointerfaces utilizing quantum technologies for monitoring and modulating human physiology
- Quantum control and sensing to modulate and read very weak biological signals toward personalized medicine and therapy.
- Quantum algorithms and computational tools to simulate biomolecular interactions, analyze complex datasets, and accelerate therapeutic discovery beyond classical capabilities.
- Novel and innovative quantum approaches that push the boundaries of biomedical and clinical research beyond those listed here.
Participating ICOs
NIBIB’s interests include the development of quantum technologies and their integration into bioengineering, sensing, imaging, and computational frameworks to improve human health and medical care. NIBIB supports development of quantum technologies that are expected to be applicable to a broad spectrum of disorders and diseases. Projects that use a single tissue, organ, disease, or physiological condition as a model system to enable the development of broadly applicable quantum technologies are within the NIBIB mission.
ICO Scientific Contact:Afrouz Anderson, PHD
[email protected]
NCATS encourages submissions from multidisciplinary teams with expertise in quantum science, biomedicine, and engineering to leverage quantum-enabled sensing and computing technologies for biomedical research and clinical applications, aligning with the NCATS mission.
Quantum sensing includes technologies like atomic magnetometers, diamond color centers, quantum-enhanced microscopy, spectroscopy, and imaging approaches.
Quantum computing includes quantum algorithms and hybrid methods that improve data processing, analysis, and predictive modeling.
Key areas for quantum-enabled biomedical applications include, but are not limited to, the following:
- Advancing drug and therapy development
- Enabling early disease detection
- Improving diagnostic approaches
- Improving health monitoring strategies
- Advancing data analytics
Geetha Senthil, Ph.D.
[email protected]
NCI is interested in quantum-enabled sensing, compute, and imaging technologies that extend existing cancer research, diagnostics, and treatment capabilities. These efforts are encouraged to use established NCI resources where appropriate such as the Cancer Centers Program, the NCI Clinical Trials Network, the Frederick National Laboratory for Cancer Research, the Cancer Imaging Program, and the Cancer Data Ecosystem.
Priority areas include:
- Sensitive detection of cancer biomarkers to support early diagnosis and monitoring
- Advanced imaging approaches that improve metabolic, structural, and functional tumor characterization, and
- Real-time assessment of the tumor microenvironment and treatment response that accelerate mechanistic biological insights
Emphasis is placed on enabling technologies that augment current imaging, modeling, and diagnostic platforms, align with clinical workflows, and support translational research, data integration, and use across NCI’s mission.
ICO Scientific Contact:Eric Johnson, Ph.D. (Cancer Biology)
[email protected]
Chris Siwy, Ph.D. (Computing)
[email protected]
Jeff Buchsbaum, M.D., Ph.D. (Translational)
[email protected]
Specific areas of interest to NEI include but not limited to the following:
- Novel quantum technology imaging systems to improve detection and diagnosis of diseases that affect the visual system, especially those that are relevant to NEI’s Strategic Plan.
- Quantum computer algorithms and quantum-classical computational solutions to improve disease diagnosis and classification.
Tony Gover, Ph.D.
[email protected]
NHLBI is interested in advancing quantum technologies to support research and product development aligned with its vision including, but not limited to:
- Next-generation quantum imaging to improve detection and diagnosis of heart, lung, blood or sleep (HLBS) diseases
- Portable ultrasensitive quantum sensors for non-invasive measurements of early HLBS biomarkers (e.g., fetal magnetocardiography)
- Quantum technologies to understand biology of HLBS diseases, track progression and treatment (e.g., sickle cell disease vaso-occlusive crises, lung fibrosis)
- Innovative quantum sensing approaches including hyperpolarized MRI, photon-counting CT, and quantum Optical Coherence Tomography
- Quantum technologies for developing lab-on-a-chip and microfluidic systems for Point-of-Care diagnostics and screening new therapeutics
- Novel algorithms and quantum-classical computational solutions for enabling quantum technologies, biomanufacturing tools and in-silico discovery of personalized treatments
Julia Berzhanskaya, PhD
[email protected]
John Haller, PhD
[email protected]
NIDCR encourages investigator-initiated research leveraging quantum information science and enabling quantum materials to advance dental, oral, and craniofacial (DOC) health across prevention, early detection, diagnosis, and treatment. Priority areas include quantum-enabled biosensing and biointerfaces for ultrasensitive, minimally invasive measurement of DOC biomarkers and physiology (e.g., saliva, breath, intraoral-device–based sensing); quantum-enhanced imaging approaches that improve characterization of oral disease, craniofacial biology, and treatment response; and quantum/hybrid quantum-classical algorithms and workflows for biomolecular simulation, materials/therapeutic optimization, and analysis of complex multimodal DOC datasets. Applications are encouraged to emphasize fit-for-purpose benchmarking against state-of-the-art classical methods, reproducibility, scalable device integration, and clinically realistic data pipelines aligned with NIDCR strategic priorities.
Orlando Lopez, PhD
[email protected]
NIGMS is interested in applications that include quantum inspired technologies in the institute’s mission-supported scientific areas. Applications to NIGMS may focus solely on technology development for use by the broader scientific community or may incorporate quantum inspired technologies to advance understanding of NIGMS mission relevant basic science and clinical areas.
Alvin T. Yeh
[email protected]
ODSS is specifically interested in quantum computing approaches for biomedical research. ODSS encourages the development and application of quantum algorithms, hybrid quantum–classical workflows, and computational frameworks that address computationally challenging biomedical problems beyond the practical limits of classical computing. Areas of interest include quantum methods for biomolecular simulation, optimization, and pattern discovery, as well as rigorous evaluation of their potential advantages relative to classical approaches. ODSS also encourages applications that emphasize benchmarking, scalability, reproducibility, and integration with existing AI/ML and cloud-based biomedical research infrastructures to facilitate responsible development and long-term impact.
Fenglou Mao
[email protected]
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