QT Sense is developing Quantum Nuova, a quantum-based platform that measures cellular stress in living cells in real time, enabling researchers to observe biochemical activity at the single-cell level and better understand disease and drug response.
Dutch-based startup QT Sense has raised €4 million to advance Quantum Nuova, a quantum-based platform that monitors cellular stress in living cells at single-cell resolution. The funding includes a €3 million seed round led by Cottonwood Technology Fund, alongside follow-on funding from QDNL Participations and an angel investor. The total funding includes a €0.6 million ONCO-Q grant to fast-track oncology applications, along with €0.4 million from the Quantum Forward Challenge to support collaborative deployment and validation of Quantum Nuova in real research environments.
While traditional biological methods typically analyse fixed tissue or non-living cells, QT Sense’s Quantum Nuova platform measures biochemical activity in living cells and tissues in real time, enabling new approaches in spatial biology.
The platform uses fluorescent nanodiamond quantum sensors to detect oxidative stress, metabolic changes, and free radical activity—signals that are central to disease processes but have been difficult to observe directly.
By providing a live view of cellular behaviour at the individual cell level, Quantum Nuova allows researchers to study how cells respond to drugs, adapt to stress, and differentiate into distinct subpopulations, offering insights beyond those available through genomics, proteomics, or conventional imaging.
The technology has already been used to study the mechanisms of action of FDA-approved drugs. With support from the ONCO-Q grant, it will now be applied to colorectal cancer research, with the aim of mapping oxidative stress and metabolic vulnerabilities in tumour models to support future diagnostic and therapeutic development.
The new investment will support the transition of Quantum Nuova from a high-performing prototype to a deployable discovery platform.
Planned developments include improvements in hardware robustness, throughput, and integrated analytics to support real-world use. Early-access systems will be deployed with strategic partners to enable mechanism-of-action studies, functional heterogeneity analysis, and rapid, label-free measurements across multiple samples.