The UN says we are in a year of quantum, celebrating 100 years since the development of quantum mechanics. While quantum computing is often the main talking point, the other areas of quantum tech, such as quantum sensors are getting increased attention as well. But what are they? And what relevance do they have to biotech and healthcare applications? Quantum sensors is a broad category of sensing devices that rely on quantum mechanical phenomena to improve their effectiveness compared to “classical” sensors. The main phenomena relied on are: Quantum interference – matter can display wave-like properties, in which particles interact with each other and add together or subtract from one another, creating patterns of interference. These patterns change when changes in the source of the wave signals occur. Minuscule changes can be detected readily by changes in the interference pattern. Quantum entanglement – when two particles become entangled, the measurements of one particle can be correlated with measurements of the other particle, even if separated by great distances. More than two particles can become entangled together Interfering Squids Interference-based quantum sensors rely on the measured interactions of two wave systems interfering with one another. A common form of interference-based sensor is a SQUID (Superconducting Quantum Interference Device). These ultrasensitive magnetometers detect the current which passes through a pair of superconductors via quantum tunnelling. Quantum tunnelling is a phenomenon where particles can pass through a barrier (whether a physical barrier or an energy requirement) even though considered as classical particles they should not be able to. The difference in phase of the current passing through each superconductor of the pair creates an interference pattern. External magnetic fields affect this interference. This can be used to detect even minute magnetic fields. SQUIDs have been used in brain and cardiac imaging to detect disease for decades. Neurons in the heart and brain have ion currents that produce magnetic fields which can be detected by arrays of SQUIDs outside the body. Such detection is called magnetocardiography, MCG (heart) and magnetoencephalography, MEG (brain). You may be familiar with the more commonly used EEG (electroencephalogram) or ECG (electrocardiogram) which use electrodes to measure electrical activity around and near the heart and brain. Both can be used to detect signal patterns in the tissue which are indicative of disease. Magnetic imaging has the advantage that body tissues are magnetically transparent such that magnetic fields propagate from inside the body to the outside without distortion. Contrastingly, electrical signals are heavily distorted by insulating tissues such as the skull. However, this magnetic transparency does present a difficulty of how to localise the signals to specific parts of the tissue. MEG systems often have arrays of hundreds of SQUID sensors to help overcome this problem. Furthermore, the need for cryogenic cooling and magnetic shielding from outside signals have slowed the adoption of this technology compared to ECG/EEG and MRI (magnetic resonance imaging). Tangled scopes Entanglement-based quantum sensors use two particles which have been “linked” or “entangled”. When entangled particles are measured, the measurements will be strongly correlated. Entanglement is of particular interest in quantum cryptography but there are quantum sensors which take advantage of this property as well. Light microscopes typically cannot resolve subjects smaller than half the wavelength of light used to illuminate the subject. For violet light, this means there is a classical limit where details smaller than 0.2 µm cannot be resolved and seen. This makes it difficult to see anything smaller than an organelle inside a cell. This can be overcome to some extent by using shorter wavelengths of light, pushing into the ultraviolet (UV) part of the spectrum. However, UV light tends to chemically modify substances, typically photobleaching and damaging cells. By using a coherent light source (like a laser) and “splitting” photons into entangled photon pairs, one photon in the pair can be used to image the sample and another photon can be directed to a separate detector. By comparing the measurements of the entangled photons, noise present in both detections can be identified and removed since the measurements are correlated. This leads to a significant improvement in signal-to-noise ratio, which can increase the angular resolution beyond the classical limit itself and/or reduce the intensity of illumination required. Such quantum light microscopes can observe significantly smaller parts of cells. This is particularly useful for imaging living cells as while electron microscopes have much higher resolution, the observed samples typically have to be prepared in ways that are damaging, if not lethal, to cells. These quantum microscopes have higher resolution without damaging the sample. Quantum diamonds Other quantum sensors rely on quantum states that are relatively stable, but are affected by the environment and can be read to provide measurements. For example, Nitrogen Vacancy (NV) centres use diamonds where two adjacent points in the diamond’s carbon-atom crystal lattice structure are different. For the first point, the carbon atom is missing; for the second point, the carbon atom is replaced with a nitrogen atom. The outer unbound electron on the nitrogen atom has 3 different spin states called 0, +1, and -1. The -1 and +1 states are higher energy than the 0 state and microwave photons can move the NV centre from 0 to -1/+1. These states fluoresce differently, allowing the spin state of the NV centre to be measured optically. Interestingly, the energy levels of these individual spin states are affected by the environmental conditions such as external magnetic and electric fields, temperature, and mechanical strain, causing their fluorescence to change. This allows these parameters to be measured. Like SQUIDs, NV centres may be used for MEG/MCG as discussed above. NV centres do not have the extreme level of sensitivity that SQUIDs do, but they are much easier to work with due to the reduced need for cryogenic cooling. NV centres are also being investigated for use as qubits in quantum computers. It’s important to understand that quantum sensors are not necessarily tied to quantum computers; existing quantum sensors typically feed their data into classical systems for analysis. However, as quantum computing matures, qubits may be able to directly process the quantum information measured by these sensors, potentially allowing them to interrogate the data more efficiently and with greater fidelity. So what is holding quantum sensors back in healthcare? Quantum sensors are a relatively developed part of the quantum technology landscape with many of these technologies becoming available in biotech research labs and specialist medical environments over the past decade or so. These tools have been used in areas like physics research, geological surveying, and timekeeping for much longer. However, the pipeline of tech transfer from the lab to commercially available medical device is not well established. Additionally, there are currently issues with cost and how delicate these sensors can be. Many quantum sensors rely on cryogenic conditions. Hospitals are somewhat used to managing the cryogenics of MRI machines at around 4 Kelvin but some quantum sensors require temperatures significantly closer to absolute zero. Quantum sensors can require more shielding to focus their sensitivity on the desired target e.g. magnetic sensors require significant shielding from external magnetic fields to make them effective. Looking to the future With continuing development, quantum sensors should help to significantly improve the ability to understand disease, particularly at the smallest scales e.g. measuring the magnetic/electrical activity of neurons across the whole brain to understand brain disease. In the future, we expect quantum sensors will see widespread use in healthcare comparable to classical sensors such as MRI and ultrasound. They may even supplant them in some cases! The significant interest in quantum sensors for military and space applications should also lead to acceleration of this technology area more generally and translate to useful technologies in the civilian world. Quantum sensors are of particular interest in the military for their radio frequency (e.g. radar) sensitivity, as well as in navigation technologies not reliant on GPS. By comparison, Infrared ear thermometers, LASIK (laser eye surgery), and of course the reflective “space blanket” were all derived from technologies developed for military and space applications. We are already starting to see translation of this technology to practical medical devices. Research by the University of Nottingham and its spin-out Cerca Magnetics into optically pumped magnetometers has allowed Cerca to produce a MEG system that is significantly more convenient to use (essentially a helmet rather than a large machine) that does not require cryogenic cooling. We expect to see continued development and commercialisation of this technology by Cerca, and a significant growth in quantum medtech-focused spin-outs, start-ups and scale-ups as the path to market is established. Investment and collaboration are needed to push quantum technologies into the forefront of medical care. We are already seeing this, such as with the December 2024 launch of the UK Quantum Biomedical Sensing Research (Q-BIOMED) hub led by UCL and the University of Cambridge with £24 million of government funding. Patents will play a significant role as a means to support and protect the commercialisation of these technologies. With a means to protect the R&D investment, intellectual property will help to build a pipeline of technology transfer from continuing research into commercialisation. How companies are building out their patent portfolios in this space will be explored in a future article.