Review—Quantum Biosensors: Principles and Applications in Medical Diagnostics

Originating at the intersection of physics and biosensing, quantum biosensors (QB) are transforming medical diagnostics and personalized medicine by exploiting quantum phenomena to amplify sensitivity, specificity, and detection speed compared to traditional biosensors. Their foundation lies in the fusion of biological entities like DNA, proteins, or enzymes with quantum sensors, which elicits discernible alterations in light emissions when interacting with sample molecules. Their prowess in identifying disease-linked biomarkers presents an avenue for early diagnoses of conditions like Alzheimer’s and cancer. Beyond this, they enable real-time monitoring of treatment responses by capturing the dynamism of biomarkers, but QB still faces challenges, such as issues of stability, reproducibility, and intricate quantum interactions. Moreover, seamless integration into prevailing diagnostic frameworks necessitates careful consideration. Looking ahead, the evolution of QB navigates uncharted territories. Innovations in fabrication techniques, interdisciplinary collaborations, and standardization protocols emerge as pivotal areas of exploration. This comprehensive discourse encapsulates QB’s principles, diverse iterations, and burgeoning medical utilities. It delves into inherent challenges and limitations, shedding light on the potential trajectories of future research. As QB continues to evolve, its potential to redefine medical diagnostics becomes increasingly tangible. The saga of QB resonates with possibilities, poised to reshape the diagnostic landscape profoundly.

2][3][4] It involves leveraging the unique properties of quantum systems to develop highly sensitive and precise techniques for detecting biological molecules, pathogens, or other biological entities.QB detects and tracks the movement of individual molecules or even single atoms within biological samples, providing valuable insights into various biological processes.It empowers us to achieve pinpoint accuracy in measuring response data, achieved by delicately detecting nuances in the magnetic and electrical fields' dynamic motion.What sets it apart from classical scientific approaches is that it draws its output data and signals from the realm of single atoms, a stark departure from the conventional reliance on massive atomic ensembles. 5QBs are a fascinating field of research that leverages principles from quantum mechanics (nanoscale materials and structures) to detect and analyze biological molecules with high sensitivity and precision. 4In general, it is defined as a biosensor that uses quantum mechanical concepts to improve its sensitivity and functionality.7][8] To increase sensitivity, accuracy, and selectivity in the identification of biological entities, QBs make use of quantum phenomena.Many material properties, including temperature, strain, thermal conductivity, electric and magnetic fields, and pH, may be measured by a potential range of sensing materials that have been developed using quantum processes.Quantum dots (QDs), nanoparticles, and other quantum materials can be used to apply quantum mechanics to biosensors.For instance, semiconductor nanocrystals known as QDs show quantum confinement characteristics.In biosensing, QDs can be functionalized with biomolecules like antibodies or DNA strands.
When these QDs meet target biomolecules, such as proteins or DNA, there is a change in their optical properties, such as fluorescence.The intensity or wavelength of the emitted light can be measured to quantify the presence and concentration of the target biomolecules.High-sensitivity detection may be achieved using this feature in several applications, such as biosecurity, environmental monitoring, and medical diagnostics. 9Devices known as quantum resonators use the laws of quantum mechanics to quantify variations in mass or other physical parameters.The mechanical characteristics or resonant frequency of a quantum resonator are altered when biomolecules attach to its surface.It is possible to identify and link this shift with the bound biomolecules' identification or concentration.
QBs are still a relatively young and rapidly evolving field of research.As technology advances and our understanding of quantum phenomena improves, QBs are expected to find more practical applications and contribute significantly to the advancement of biotechnology and healthcare. 10In contrast to traditional biosensors, which often rely on macroscopic observations, QBs leverage quantum mechanical phenomena such as quantum interference, or quantum entanglement to detect and measure biological entities of very low concentrations of biomolecules, even at the singlemolecule level shown in Fig. 1. 13 This emerging research paradigm promises to surpass the limitations of conventional techniques, such include the requirement for complex production methods and the possible toxicity of some quantum materials, enabling the exploration of events within biology that resemble the movements of ions and subatomic particles. 14,15Firstly, drift, or the accumulation of inaccuracies brought on by noise and manufacturing flaws is a problem with traditional sensors.For instance, temperature can cause metal sensor parts, like springs, to expand and contract.This might influence measurement results and need recalibration due to drift.The Standard Quantum Limit, which is the error or noise in data from a typical sensor, is random and confined by 1n, where n is the number of observations.This is because ordinary sensors conduct separate measurements. 16QB with extreme sensitivity can measure a wide range of physical characteristics, including electric, magnetic, and thermal fields, among others.Due to their small size, current sensors are unable to acquire data that QBs can.The demands that can be satisfied by applying QBs are not even justified by using tiny sensing devices.QBs provide a descriptive way to study modern biological components and interactions and uncover their applications in many domains with outstanding sensitivity and subcellular resolution.QBs are systems that employ quantum coherence, entanglement, and interference to measure certain physical properties.They can be single systems or groups of systems.However, advances in quantum technology and physics suggest that a new generation of biological sensors with far better performance is on the horizon. 10Moreover, when it comes to the detection and measurement of biological analytes, QBs can offer increased accuracy.These biosensors' quantum qualities enable the fine-tuning of detecting settings, leading to more precise measurements.Nanoscale design is possible for QBs, which makes them more miniaturized.Applications where space is constrained, like lab-on-a-chip platforms or portable diagnostic devices, benefit from this.Real-time monitoring of biological processes may be possible with QBs due to their quick reaction times.This is important for applications like medical diagnostics where quick information is critical.
Quantum dots (QDs) are examples of materials that display the quantum confinement phenomenon.This phenomenon happens when the material's dimensions approach the wavelength of the wavefunctions of the electrons.Due to the distinct energy levels that result from this phenomenon, nanoscale quantum materials are extremely sensitive to changes in their surroundings, including interactions with biological molecules.The nanoscale dimensions of quantum materials typically result in high surface-to-volume ratios.This large surface area makes it easier to interact with target molecules, which raises the sensitivity of biosensing applications. 1uring fabrication, quantum materials' size may be carefully regulated.The electrical and optical characteristics of the materials are impacted by this size control.When it comes to biosensing, the tiny size facilitates fast interactions with target molecules, which results in faster reaction times than with larger-scale materials.One may easily adjust the optical and electrical characteristics of quantum materials.This tunability makes it possible to optimize the material's reaction to certain biological analytes in biosensing applications.Lower detection limits are made possible by the capacity to precisely adjust the characteristics, making it possible to detect even minute quantities of target molecules.For instance, the size and makeup of QDs can affect the wavelengths at which they produce light.Using separate QDs that emit different colors in response to different target molecules, this characteristic allows for multiplexed detection.This feature boosts the biosensing platform's effectiveness by enabling the simultaneous detection of several analytes in a single test.Because quantum materials may be designed to be stable and biocompatible, they can be used in biological settings.They perform better in multiplexed detection as a result, which helps complicated biological samples have lower detection limits.
Despite promising characteristics, with only a few active clinical trials, QBs remain a long way from being used in hospitals.QB generates complex and often high-dimensional data.Artificial Intelligence (AI) techniques, such as machine learning (ML) and deep learning (DL), can be used to analyze this data effectively.AI algorithms can identify patterns, correlations, and anomalies in the data, aiding in the detection of specific biological molecules or changes in biological processes.The usage of medical biosensors in conjunction with AI is discussed.To grasp the fundamental challenges associated with the fabrication of QBs, we first discuss their recent characterization in this paper.Then, we go through a few biomedical uses for QBs, their position in the healthcare industry, and the difficulties they provide.This review explains how AI and QBs are being used to create therapeutic robots, nanomedicine, and pharmaceuticals.As quantum sensing advances, it holds the potential to unveil new dimensions of information within biological systems, propelling our understanding of life's complexities to unprecedented levels.

State of Art of Quantum Biosensing
Biosensors are among the most fortunate tools available in the biomedical and international fields of healthcare today for the diagnosis of diseases, identification of multidrug-resistant organisms, identification of emerging epidemics, and recognition of very low concentrations of poisons and microorganisms in potable water or food.However, there are certain serious challenges that scientists and engineers working on these issues must overcome.For instance, if biosensors are to increase the precision and effectiveness of medical diagnosis, they must be sensitive enough to detect even trace amounts of germs in blood or other biological samples.The QB has several potential uses, such as tracking a medication across a cell's cytoplasm and membrane or accurately drawing tumor borders during therapy.The QB may be able to track a single ion moving across a cell membrane, measure the electrical pressures at a neuronal synapse, or record the movement of peptides among small organelles inside a cell-all tasks that are challenging to observe with the naked eye.Technology connected to biology and quantum engineering has the potential to fundamentally alter our understanding of medicine.By gathering and utilizing finer statistics to provide improved data results, the informatics gathered via QB delivers more precision that can improve the usefulness and application of current sensing technologies.For instance, solidphase devices and atoms and molecules that exist in free space can be used to produce QB, although quantum optics typically relies on measurements using various aspects of photons or light. 17QB offers healthcare providers clinical diagnostic scans that are less costly, more accurate, and less likely to have negative clinical outcomes. 18ne of the most useful tools currently accessible in the biomedical and international fields of healthcare is the use of biosensors to diagnose illnesses, spot organisms that are resistant to multiple drugs, spot emerging epidemics, and detect extremely low concentrations of toxins and microorganisms in food and drink. 19In this area, we try to highlight notable research that established various QB types with a strong potential for clinical use.
Concept of diamond Nitrogen-Vacancy (Nv).-Theenhanced sensitivity that results from quantum phenomena is one benefit of using quantum sensors.Some quantum sensors can produce unequalled spatial resolution since they can be as tiny as a single atom. 2 The substitutional nitrogen atom next to an open lattice site makes up the NV center, a flaw in the diamond lattice.It has a special electronic structure with excited and ground states.The main actor in this event is the NV center's electrical spin. 20The NV center has a ground state with three energy levels, labeled ms = 0, +1, and −1, which correspond to the electronic spin projections along the crystallographic axis.It can function as a magnetometer because of its electronic spin, which renders it sensitive to outside magnetic fields.The NV centers' spin polarization is the first step in the procedure.A strong laser pulse is used to optically excite the NV centers and polarize their spins into the bright ms = 0 ground state.This polarization enhances the fluorescence emission of the NV center.The NV centers begin to stochastically decay once the laser pulse is turned off into an equilibrium mixture of various magnetic states (ms = 0, +1, −1).This relaxation process is influenced by the surrounding magnetic environment, also known as spin noise. 14The greater interaction of the NV center spin with varying magnetic fields from the surroundings is what causes the quicker decay with greater spin noise levels.As the system transitions from the polarization condition to the equilibrium state, the fluorescence intensity diminishes.][23] In the advanced version of the technique, microwaves are used to manipulate the NV center's spin states.By applying microwave pulses, the NV center can be brought into the ms = +1 or −1 states.Monitoring the transition from these dark states to the brighter states enables controlled monitoring of relaxation.There are several uses for the relaxometry method that makes use of the NV centers in diamonds for detecting different physical parameters, such as magnetic fields, temperature, and strain.This is made possible by the NV center's spin states' sensitivity to outside influences that alter the relaxation dynamics.The environment surrounding the NV center may be inferred using the concentration-dependent relaxation rate.NV centers are used in relaxometry to make use of their quantum characteristics for sensing and measurement. 24,25Key characteristics of quantum technology include quantum coherence, sensitivity to external disturbances, and the capacity to control spin states using light and microwaves.][28][29] In summary, the relaxometry technique based on NV centers in diamonds combines the principles of quantum spin dynamics, optical spectroscopy, and quantum coherence to enable precise sensing of local magnetic environments and other physical quantities.This demonstrates the integration of quantum concepts into practical technological applications.There is a visual representation of some of these concepts in Fig. 2. Because nanodiamond (ND) is nanoscale in size, chemically inert, and biocompatible, it is a safe and non-invasive instrument for intracellular sensing.In recent years, NDs have been synthesized using several primary techniques, including chemical vapor deposition (CVD), high pressure and high temperature, high energy ball milling, and laser ablation.In biosensing applications, HPHT NDs (High-Pressure High-Temperature Nanodiamonds) have become the most often employed sensing materials. 30When NDs are surface functionalized, they can acquire remarkable features that make it possible to create QBs with a range of detecting functions.The use of NDs as temperature sensors offers the benefits of biocompatibility, non-invasiveness, and stability over extended periods.They are also nearly impervious to changes in ionic concentration, pH, and molecular interactions. 31,32ollowing the widespread COVID-19 pandemic, we recognize the critical role that effective, practical, and precise viral detection ECS Sensors Plus, 2024 3 025001 techniques play.There is a lot of promise for use in the development of hybrid sensors for virus detection because of the NV centers' exceptional magneto-optical qualities and steady fluorescence emission in ND.Li et al. 33 created a quantum sensor to detect the RNA in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).
Quantum optical biosensor.-Theuse of photons to quantum information communication problems is the main emphasis of photonic QB.Furthermore, this discipline studies entanglement and quantum physics to provide new uses for quantum information.Ultrabright quantum light sources with reduced noise and entanglement, as well as the development of novel methods for creating practically applicable quantum states and measurements, have revolutionized photonic quantum sensing in recent years.Semiconductor nanocrystals are extremely light-absorbing and luminous nanoparticles whose absorbance start and emission maximum change to higher energy with decreasing particle size owing to quantum size effects. 34For quantum-enhanced sensing, compressed light levels and quantum-correlated photon states can also be employed.A quantum optical-electrical phenomenon known as an optical biosensor is based on the ability of photons of light to transmit energy to electrons in a metal.The specific metal and the surroundings of the lit metal surface determine the wavelength of light at which coupling takes place.By measuring the quantity of light reflected by the metal surface, this transfer may be seen.A metal-coated optical prism is the most popular practical implementation of an optical biosensor, although additional effective implementations have been shown using metal-coated diffraction gratings, optical fibers, and planar waveguides. 35The use of nanoscale quantum emitters as tags for tracking biomolecular interactions is still constrained by their omnidirectional emission, blinking nature, and high numerical aperture objectives.Cancer-related miRNA biomarkers with single-molecule resolution and single-base mutation selectivity are one illustration. 36By mixing highly luminous materials, Ueda et al. 37 has created an incredibly sensitive photonic crystal (PhC) sensor that enables detection by single wavelength fluorescence intensity shift in the visible wavelength area.
Quantum plasmonic biosensors use surface plasmon resonance changes to detect biomolecules with high sensitivity and without the need for labels.These sensors make use of the simultaneous localization and amplification of electromagnetic fields near the metal-dielectric contact. 38The key problems in using plasmonic biosensing for quick, real-time, and label-free probing of physiologically relevant analytes are to detect tiny compounds at extremely low concentrations and create compact devices for point-of-care (PoC) analysis. 39Recently, it has been shown that quantum approaches can perform better than conventional sensing techniques and attain sensitivity below the so-called shot-noise limit. 40Surface plasmon polaritons (SPPs) with gold coating are used in Peng et al.'s 41 improved taper-based QBs, which work below the standard quantum limit (SQL) and offer a novel approach to biological engineering, disease diagnosis, and single molecule label-free detection.The plasma-sputtering device is used to create a gold covering with a 50 nm thickness.The quantity of photons transmitted also varies with the bovine serum albumin (BSA) content in the vicinity of the proposed QBs.
Quantum dots (QDs) can be used in the development of biosensors.QDs are a novel class of fluorescent nanomaterials that consist of an inorganic nucleus with organic molecules bonded to its surface having a dimension of between 2 and 10 nanometers and 103 to 105 atoms.In addition to their broad excitation spectrum, tunable particle sizes, constrained emission spectra, ability to emit various fluorescence hues, superior signal brightness, and longer fluorescence lifespan, QDs have exceptional optical and chemical features that make them distinctive.Because QDs have many functional groups, it is simple to create hybrid nanomaterials with good analytical performance.Through the hybridization of QDs with nanomaterials, functionalized sensing devices enable the sensitive and selective detection of metal ions, biomarkers, and antibiotics. 42s are thought to be the perfect material to utilize in the creation of biosensors that detect antibiotics.The recognition methodologies of QD-based sensing applications, such as immunosensors, aptamers, and molecularly imprinted polymers (MIPs), are categorized in. 43he application of such sensors in biomedicine has great promise for identifying abnormalities in the body's complex molecular proteins, which can cause metabolic problems and incite abnormalities in nearby proteins. 44arbon nanotubes (CNTs) are hollow tubes with widths of nanometers and lengths of micrometers that are formed by rolling up graphene sheets into cylindrical shapes.Special one-dimensional quantum confinement phenomena lead to remarkable mechanical, optical, and electrical characteristics.With their great sensitivity and quick reaction times, CNTs are employed in biosensors as sensitive transducers for the electrical detection of biomolecular interactions. 45,46Typically, CNTs have diameters ranging from 1 nm to around a few tens of nanometers.Single-walled carbon nanotubes (SWCNTs) are made of a single layer of graphene rolled into a seamless cylinder, whereas multi-walled CNTs (MWCNTs) are made of many concentric layers of graphene rolled around a single axis.Depending on the number of walls, SWCNTs generally have diameters between 0.4 and 3 nm, while MWCNTs have greater diameters between 2 and 100 nm or more. 47Many fluorescence sensing technologies for dye-labeled biological molecule detection were developed based on carbon nanotubes, utilizing the noncovalent interaction between CNTs and DNA. 48A practical, sensitive, and selective biosensor based on DNA-CdS QDs sensitized carbon nanotubes was developed for the direct detection of microRNAs (miRNAs) by combining with cyclic enzymatic amplification. 49raphene is a single layer of carbon atoms arranged in a twodimensional honeycomb lattice that has a vast surface area, remarkable mechanical strength, and excellent electrical conductivity.Graphene quantum dots (GQDs) are a new class of zero-dimensional semiconductor nanocrystals that consist of small graphene particles with a size range of 1-50 nm.These GQDs offer an excellent platform for studying biomolecules including proteins, cells, and viruses since their sizes are similar to those of biomolecules.GQDs work in perfect harmony with electrochemical sensors to provide a more targeted and sensitive platform for the identification of cancer biomarkers.1][52] Acute myocardial infarction (AMI) can be effectively predicted at an early, reversible, and perhaps curable stage with the use of GQD-integrated electrochemical biosensors. 53MXenes is a newly emerged 2D platform for QB applications.MXenes-based QBs provide good repeatability of data over an extended duration of time due to their wide porous structure, strong biocompatibility, abiding resilience, excellent electrical conductivity and large surface area, which are advantageous for the immobilization of biomolecules and the detection of target analytes.MXenes and their composites exhibit improved elastic properties and adaptability with structural design, enabling a wide range of applications in the areas of wearable sensing devices, storing energy, and electromagnetic quantum shields. 54,55MXenes can exhibit QD-like behavior due to their quantum confinement effects, leading to size-dependent electronic and optical properties.This property makes MXenes attractive for various QD applications, including sensing, imaging, and optoelectronics.Due to its numerous beneficial qualities, surface plasmon resonance (SPR) biosensors may be developed with the help of smart MXene quantum dots (SMQDs), a novel class of nanomaterials that are emerging quickly.Furthermore, SMQDs are 2D inorganic segments that are two-dimensional and have a restricted number of atomic layers.They have outstanding qualities including strong conductivity, plasmonic, and optical capabilities.As a result, SMQDs are intriguing candidates for biomedicine due to ECS Sensors Plus, 2024 3 025001 their special qualities, which include biological sensing and imaging, antigen detection, cancer diagnosis and therapy, etc. 56,57 QDs are all-around adaptable nanomaterials with distinctive optical and electrical characteristics that make them useful for a variety of applications ranging from photovoltaics and display technologies to biological imaging and sensing.

Applications of Quantum Biosensors in Medical Diagnostics
Medical diagnostics has demonstrated considerable potential for QBs, which utilize the concepts of quantum mechanics.QBs are sophisticated sensing tools that use the laws of quantum mechanics to identify and examine biological components with extreme precision and sensitivity, including proteins, DNA, RNA, and tiny compounds.These materials are sensitive to changes in the local environment brought about by biomolecular interactions because they display quantum confinement effects, size-dependent optical characteristics, or remarkable electronic conductivity.The quantum material changes in electrical conductivity, surface plasmon resonance, fluorescence intensity, and other electronic and optical characteristics upon biomolecular interaction.The biological signal is transduced into a quantifiable output signal by this change in characteristics.Depending on the transduction mechanism used, several methods are used to detect and evaluate the quantifiable output signal from the QB. 5 These biosensors are very sensitive and precise biological molecule detectors that make use of quantum phenomena like superposition and entanglement.There are creative applications for QBs in a variety of fields, such as medicine, agriculture, and environmental monitoring. 58To determine possible applications, Chen et al. 59 looked at the surface changes and optical characteristics of QD in aquaculture pollution detection.Thanks to its unique adjustable optical features, which include a broad excitation spectrum, narrow emission spectra, tunable emission wavelength, and low photo-bleaching, this novel form of fluorescent marker has enormous potential in the biological and medical domains.Based on this marker, the detection technique is easy to use, fast, consistent, sensitive, and has a high throughput.Safarpour et al.'s 60 study developed a nano-based biosensing tool for detecting plant pathogenic fungi.They biofunctionalized QDs with a specific antibody against P. betae, conjugating the GST antibody to Tioglicolicacid-modified Cadmium-Telluride QDs (CdTe-QDs).The dye (Rhodamine) was attached to the GST, forming donoracceptor complexes.The immunosensor demonstrated high sensitivity and specificity of 100%, acceptable stability, and consistent results.QDs are thought to be the perfect material to employ in the creation of biosensors that detect antibiotics with exceptional sensitivity and specificity. 61Similarly, QDs are a ubiquitous tool in the detection of pesticide and veterinary medication residues, and their widespread usage is one of the great successes of nanoscience. 62As seen by the rise of new companies in this field, quantum sensors are making the transition from the lab to the real world.At an unprecedented level of spatial sensitivity and accuracy are made possible by the atomic dimension scale of quantum sensors and their coherence characteristics.Although determining their potential effects might be difficult, these quantum technologies have clear potential in biological applications. 5,10,63antum biosensors in cell imaging.-Earlyillness detection is crucial for effective treatment and recovery.There are now several biosensors available that can detect illnesses with improved sensitivity, selectivity, quick reaction times, and inexpensive costs.Additionally, more advanced biosensors, also known as nano biosensors, have expanded the standard characteristics of biological sensors to provide a wider range of applications in the diagnosis of diseases. 64These biosensors utilize nanomaterials, aptamers, nucleotides, DNA/RNA, PNA/LNA, antigens, receptors, etc for enhanced detection.Recently, Chen et al. 65 created an optically detectable magnetic resonance (ODMR) wide-field microscope (Fig. 3) to illustrate the use of NV centers in quantum sensing by achieving magnetic imaging of tumor tissue.A 100 nm thick layer of dense NVs was utilized to photograph a tissue segment that had been tagged with magnetic nanoparticles to obtain micrometer-resolution magnetic imaging of biological tissues.
Quantum biosensors as wearables.-Dueto the ability to provide dynamic, non-invasive measurements of biochemical markers found in human fluids including tears, sweat, saliva, and interstitial fluids, wearable biosensors have attracted a lot of attention.Notably, both optical and electrochemical biosensors have advanced quickly recently.They have drawn particular interest since they have made advancements in the non-invasive monitoring of several indicators, including hormones, germs, and metabolites.To amplify user convenience and wearability, innovative strategies like multiplexed biosensing, microfluidic sampling, and transport systems have been seamlessly integrated into compact formats, often coupled with flexible materials. 66Wearable biosensors snoop on electrochemical and electro-physiological signals coming from the human body.The skin, as the largest and most accessible organ in the human body, contains biofluids rich in biomarkers useful not only in the diagnosis and monitoring of diseases but also in profiling an individual's well-being. 67Diverse biological processes yield electrical activities, encompassing heart function (ECG), muscle movement (EMG), and sweat gland responses (Electro-Dermal Activity or EDA).These signals, extracted either from wearable sensors or diagnostic apparatus, furnish critical insights into one's health status. 68,69In the context of optimized COVID-19 care, wearables prove invaluable for early identification of cases (including asymptomatic and pre-symptomatic instances), continuous patient monitoring, and extended tracking of COVID-19 progression (encompassing recovered patients and healthy individuals).Prototype sensors integrated into smartwatches, smart tattoos, rings, facemasks, nano-patches, and other devices are presently effective at monitoring vital physiological parameters including body temperature, pulse, heart rate, and oxygen levels. 70antum biosensors as disease diagnostics and drug monitoring.-According to predictions, heart disease and stroke will cause more than 20 million deaths worldwide in 2015, making cardiovascular disease (CVD) the leading cause of mortality.Lu et al. 71 proposed a variety of rapid, simple, and portable nanomaterialbased biosensors have been developed for measuring the level of lipids (TG and TC) and lipoproteins (LDL and HDL) towards the management of CVD at the point-of-care (POC).QDs are used in LDL biosensors due to their energy transfer, fluorescence brightness, and photostability.A label-free biosensor was integrated with cadmium sulfide QDs for bioconjugation and electrical signal amplification.Apolipoprotein B-100 antibodies (AAB) were used to bind L-cysteine-capped QDs on an Au substrate.CysCdS QDs increased the sensitivity of the AAB/CysCdS/Au biosensor, enhancing the angle change of surface plasmon resonance (SPR).An SPR biosensor with a measuring extent of 5-120 mg dl−1 was demonstrated.Again, Chauhan et al. 68 developed a nanostructured metal chalcogenide (molybdenum tetra selenide, nMo 3 Se 4 ) embedded on reduced graphene oxide (rGO) based electrochemical immunosensor for cardiovascular disease biomarker [cardiac troponin I (cTnI)] detection.
The likelihood of a cure increases with early cancer detection.Many cancers in today's world are not discovered until they have spread throughout the body.A biological substance (such as a protein, DNA, RNA, or exosomes) 69 is effectively converted by biosensors into an electrical signal that can be recognized and examined to identify a specific biological analyte. 72,73Diagnostics using DNA and RNA play a significant role in today's healthcare system.Nucleic acid oligomers, which may specifically attach to target DNA or RNA sequences, are the fundamental building blocks of these sensors.Synthetic nucleic acid analogues, such as peptide nucleic acids, offer higher sensitivity for detection and sequence specificity when compared to regular DNA or RNA ECS Sensors Plus, 2024 3 025001 oligonucleotides.QDs are used as fluorescent labels to detect DNA/ RNA biomarkers in fluorescence-based biosensors.QDs offer advantages such as high photostability, narrow emission spectra, and tunable fluorescence properties, enhancing the sensitivity and multiplexing capability of DNA/RNA detection assays. 74urthermore, the nanosensor based on QDs demonstrated outstanding selectivity.It can accurately identify pre-miRNA and mature miRNA in addition to single-base mismatched and random nucleic sequences.As a result, the nanosensor offers a wide range of applications in biological investigation and illness diagnostics. 75The active surface area is increased when functioning with graphene oxide (GO), expediting the functionalization procedure and enabling quick simultaneous identification of cellular and molecular markers, especially proteins associated with cancer. 76This setup also leverages Surface-Enhanced Raman Scattering (SERS) for multiplex detection purposes. 53,77Anatomical, physiological, biochemical, or molecular indicators that are linked to the existence and severity of a certain ailment are known as biomarkers. 78Gold nanoparticles, carbon nanotubes, and hydrogel composites were often used as biosensors to identify biomarkers for osteoarthritis (OA) early diagnosis.High-accuracy and low-cost biomarkers might be utilized to diagnose illness in its very early stages. 79,80Li et al. 81  Compared to imaging diagnostics or tissue examination, biomarker-based diagnosis is simpler and faster.A straightforward microfluidic device based on surface-enhanced Raman spectroscopy may be used to screen individual circulating tumor cells (CTC) in a dynamic state to understand the varied expression of multiple protein biomarkers in response to therapy. 82The early detection and treatment of illnesses are important topics for human health research.Finding biomarkers, which may offer accurate and real-time biological data, has shown to be an effective strategy for early diagnosis.Most of the biomarker detection is now done in regional, specialized labs with huge, automated analyzers, which increases waiting times and expenses.These time-consuming laboratory studies may be replaced with smaller, quicker, and less expensive equipment, making analytical data available as point-of-care diagnostics.Biosensor-based innovative techniques could make it possible to analyze biomarkers in a decentralized environment with confidence. 83In a nutshell, it provides high sensitivity and selectivity towards the target biomarker of Prostate cancer (PC). 84etection of biomarkers, which are distinctive molecules in biological fluids, involved in neurodegeneration processes, can allow early diagnosis of neurodegenerative diseases like Alzheimer's disease (AD), 85 , and Parkinson's disease (PD). 86Tseng et al. 87 have developed modern microbiological diagnostics, such as SERS integrating a new DL method, Vision Transformer (ViT), which is a sensitive, label-free, and quick bacterial detection method measuring specific bacterial metabolites.SERS QBs are a type of biosensor that uses the SERS effect to amplify the Raman signal of biomolecules.SERS QBs can be used to detect a wide variety of biomolecules, including proteins, nucleic acids, and viruses.A SERS biosensor has been developed to detect the protein alpha-fetoprotein, 88 which is a biomarker for liver cancer, to detect the DNA of the Zika virus and to detect the SARS-CoV-2 virus, which causes COVID-19. 89 viable replacement for the present therapeutic drug monitoring methods is continuous drug monitoring, which has the potential to transform our knowledge of pharmacokinetic variability and advance personalized medicine.Precision medicine makes the promise that the right medication will be administered to the appropriate patient at the proper time and in the proper dosage. 90QBs are highly sensitive, rapid, and accurate biomolecules that enable real-time monitoring of drug levels in patients.They provide immediate feedback on drug efficacy and toxicity, allowing clinicians to adjust dosage regimens promptly.QBs also offer exceptional sensitivity and specificity, allowing for the detection of drugs at low concentrations within complex biological samples.This allows for precise quantification of drug levels, even in patients receiving low doses or experiencing pharmacokinetic variability.They facilitate personalized dosage optimization by tailoring treatment regimens to individual patients based on their unique pharmacokinetic profiles.They can detect non-adherence to medication regimens by monitoring drug levels in patients' biological samples.QBs also aid in selecting the most appropriate drug therapy for individual patients by assessing drug metabolism and response in real-time.Therapeutic medication monitoring is one of the most efficient methods for ensuring that a patient receives the proper dosage and tailored treatment. 91Therapeutic drug tracking is a clinical strategy for keeping the drug concentration inside the patient's blood within a restricted therapeutic window by monitoring delivered drugs at certain intervals. 92Therapeutic drug monitoring is often done regularly at set intervals of time. 93apid diagnosis is one indicator of how well a medicine is working and how the disease is developing.This is an important part of stopping the spread of COVID-19.Platforms for electrochemical sensors are perfectly suited for the quick and extremely sensitive detection of biomolecules.One of the most promising and developing domains for identifying and measuring health indicators is point-of-care (POC) sensing. 94For patients monitoring the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, identification of possible biomarkers for illness diagnosis is essential. 95In this direction, Li et al. 33 proposed a susceptible quantum sensor for viral RNA detection from patient samples using a diamond NV center.This proposed model can detect as few as a hundred RNA copies of the COVID-19 virus with a false negative rate of less than 1%.The whole mechanism of the proposed diagnostic tool using the NV center of nanodiamonds has been depicted in Fig. 5.
Therapeutic drug monitoring (TDM), which involves the clinical measurement of medicine in a human bodily fluid (such as blood, saliva, or urine) at specific times throughout treatment, 96 is the first step toward customized drug therapy.Wearable sensors and in vivo sensors provide direct, dynamic, and continuous biosensing of medication concentrations, whereas nanomaterial-based electrochemical biosensors are currently only used in an in vitro environment.Wearable sensors undoubtedly constitute a possible and fascinating method for drug detection given that the entire procedure is automated, continuous, and non-invasive, or at least less obtrusive.After choosing a medicine, it is crucial to use a tailored drug therapy that adjusts the dosage, dosing intervals, and treatment duration to meet the specific needs of the patient. 97recision medicine, commonly referred to as personalized medicine, can significantly enhance a patient's quality of life.An individual's genetic profile is used in this developing medical technique to direct decisions regarding illness prevention, diagnosis, and therapy.Doctors can choose the best course of action and administer the right dosage or regimen by being aware of a patient's genetic profile. 96"The correct medicine for the right patient at the right dose and timing" is one of the key PM ideas.Modern strategic approaches to patient management, such as precision medicine, treat patients as individuals rather than as members of a larger population.It employs a holistic method of therapy whereby technology and data analysis play a crucial role in decision-making.
Integration of AI in quantum biosensors.-Inrecent years, there has been an increase in interest in adopting cutting-edge technology to help achieve this aim, including 3D printing and AI.For instance, in the era of digital pharmacy, a continuous, dynamic system of medication prescribing might be created by combining digital prescriptions, 3D printing, and cutting-edge point-of-care diagnostic and/or drug monitoring systems. 97A decentralized healthcare system is possible when connected to the Internet of Things (IoT), 98 enhancing healthcare access and lightening the workload for medical staff.In three key areas-disease prevention, individualized diagnosis, and personalized treatment-AI is anticipated to assist achieve the promise of precision medicine. 99It is anticipated that AI technologies will pave the way for efficient and individualized healthcare around the globe provided they are used freely, equitably, robustly, and near human intellect.In this regard, important subjects include AI-assisted disease diagnosis and early detection, AI-enhanced treatment and delivery, wearable and implantable biosensor applications for precision and personalized medicine, clinical decision support with AI techniques, improving patient care through AI applications, radionics and quantitative imaging, bioinformatics for more effective healthcare, and novel AI applications for patient safety. 96Future IoT devices and systems will use Green IoT, an environmentally friendly and energy-efficient technology, to limit their negative effects on the environment by maximizing energy efficiency, eliminating waste, and lowering carbon emissions. 100A brand-new kind of bio-analytical tool called the Internet of Medical Things (IoMT) combines software and network-connected biomedical equipment to enhance human health. 101The shift in healthcare management toward precision medicine and, consequently, the improvement of a patient's quality of life, may be facilitated by electrochemical biosensors.Little periods of analysis times, minimal prices, and a wide range of alterations and approaches are all made possible by technology.
Fortunately, the advancement of computational tools like cloudbased computing, graphic processing units (GPUs), and tensor processing units (TPUs) has allowed us to make use of the massive amounts of data generated by these technologies. 102Large and complicated QB data may be handled and analyzed effectively in the cloud by utilizing distributed computing infrastructure and highperformance computing (HPC) clusters.Complex data processing, feature extraction, and pattern recognition activities are common in QB data analysis, and GPU acceleration can help speed up computations and shorten analysis times.GPU clusters facilitate the speedy training and execution of DL models for image analysis, signal processing, and classification tasks.This allows for the prompt interpretation of QB data and the extraction of valuable insights for medical diagnostics and monitoring.Processing enormous volumes of QB data for medical applications requires quicker model training and inference at scale, which TPUs provide above conventional CPUs and GPUs in terms of computational speed and energy efficiency.This has thus prompted the creation of several AI-based techniques designed to conclude huge healthcare datasets. 103,104The aim of AI and ML algorithms in medical science is to develop strategies for early-stage disease diagnosis by analyzing clinical data using CNNs and DL deterministic modeling.ML algorithms are already being tested for predicting symptoms of brain tumors, brain ageing, and neural disorders. 105When it comes to biosensor applications, ML may be roughly defined as an algorithmic method for using statistical approaches to analyze sensor data and extract relevant information.Regression analysis and classification have historically been the two main applications of ML techniques.Thus, it should come as no surprise that these instruments are quite helpful in the field of chemometrics.ML algorithms can help nano-biosensors retrieve information from raw data that would not be visible otherwise because of their sophisticated pattern recognition capabilities.These algorithms, for instance, have been used to categorize unprocessed sensor data and lower the possibility of cross-sensitivity and false positives.Furthermore, background noise from the sensor output has been reduced using ML algorithms, enabling a lower detection limit. 106ML algorithms have been empowering functionalized fluorescent nanodiamonds (FNDs) for intracellular magnetic microscopy improved up to 20 times.DL algorithms enable the high-contrast reconstruction of magnetic images from optical images.FNDs are small, biocompatible diamond particles that can be functionalized with various molecules, such as antibodies or peptides which allows them to be targeted to specific cells or tissues in the body.DL algorithms are a type of ML algorithm that can learn to perform complex tasks by analyzing large amounts of data.Fluorescence-based biosensors can significantly benefit from the potential uses of ML algorithms, such as rapid on-chip data processing, noise suppression improving the clarity and contrast, image analysis, and segmentation to identify and quantify specific cells or tissues in the images. 107Integrating an AIbased processor with medical test strips can support data acquisition and real-time monitoring for any non-linearity in the biosensor response under inevitable conditions or contamination.
A staggering portion of the global gross domestic product (GDP), approximately 10% or 10 trillion USD, is allocated to medical expenditures yearly.Within this expansive healthcare landscape, a wealth of data emerges from diverse sources including medication databases, genetic profiles, medical imaging, electronic health records (EHRs), and chemical analysis.In this section, we aim to spotlight several studies that have introduced compelling applications of QB, demonstrating a remarkable potential for transformative clinical utilization.Advancements in biomedical engineering, ECS Sensors Plus, 2024 3 025001 microfabrication, neurobiology, and biosensor technology will speed up the development of a fully implanted, long-lasting working biosensor system.

The Current State of Quantum Biosensors in The Healthcare Industry
Despite the various scientific and technological advancements related to biosensors that have been documented, there is a noticeable disparity between these advancements and the number of commercially accessible QB-based products.High sensitivity and specificity in detecting target biomolecules in complex biological matrices are challenges faced by QBs.To overcome non-specific binding and background noise, research should focus on developing novel surface functionalization techniques, advanced signal processing algorithms, and ML techniques.QB commercialization requires compact, portable devices.Challenges include compromising performance.Future research should explore nanostructuring microfabrication, and microfluidics advancements for precise sample handling.High production costs and scalability issues hinder the widespread adoption of QBs.Research should focus on developing cost-effective synthesis and exploring new materials with improved performance and lower costs.QBs require excellent biocompatibility and stability for long-term operation in biological environments.Future research should focus on developing biocompatible coatings, surface modifications, and encapsulation strategies to mitigate degradation and fouling effects.Collaborative efforts between academia, industry, and regulatory agencies are crucial for commercializing QBs.Investing in validation studies and clinical trials can demonstrate safety, efficacy, and reliability.This gap can be attributed to the difficulties in mass manufacturing reliable and durable instruments with great specificity, sensitivity, and repeatability.Different technical Table I (such as sensor performance and ease of handling) and nontechnical (such as acceptability in clinical application) hurdles are the next problems in the field of customized medicine.Multianalyte techniques would also be extremely desired since they make it easy, quick, and affordable to quantify several analytes from a single human material (such as blood, saliva, urine, or even exhaled air condensate).In this context, there is a critical and immediate need for bioanalytical devices with excellent sensor performance (high sensitivity and selectivity), rapid turnaround times, multiplexing capabilities, and minimal system complexity (cheap manufacturing and straightforward user operation).
The University of Waterloo's Institute of Quantum Computing (IQC) unveiled a novel type of quantum sensor in March 2019 that can detect high-speed radiation at the single-photon level.This technology enables long-distance observations.It is composed of semiconductor nanowires made of indium phosphide (InP).From an analytical standpoint, the scope of singlet oxygen detection for cancer therapy dosage management is suggested in Ref. 120.

Future Direction, Challenges and Opportunities
This field of work will soon bear fruit and succeed.QBs have the potential to significantly enhance and innovate medical diagnostics in the future.The goal is to improve the sensitivity and accuracy of QBs so that biomolecules at extremely low concentrations may be detected even more precisely.The miniaturization of QB Table I.Presents a diverse range of companies and their innovative technologies used in the healthcare and medical sectors.These advancements include Quantum Technology for ultra-high-frequency X-ray Generators, Nanotechnology in a Point-of-care device (Doc-in-a-bagT M ) for early disease diagnosis, and the combination of Quantum physics and AI to achieve 10,000 times faster accuracy in drug discovery.technologies and the creation of portable, user-friendly point-of-care devices will be pursued.The application of AI and ML algorithms will enable more precise illness forecasting and data-driven decision-making in medical diagnostics.Realizing the full potential of QBs in medical diagnostics will need ongoing study, interdisciplinary cooperation, and careful consideration of ethical considerations.Every business in the world is primed for transformation thanks to quantum computing.With the development of quantum computing, previously theoretical computer operations are now practical, creating an infinite number of possibilities for building novel applications in fields ranging from aviation to medicine.Data security, physicianpatient dynamics, liability, and cost are all issues.Blockchain technology, which provides safe data transfer to the server and outperforms the safety level of the Diffie-Hellman and RSA algorithms now in use, is one answer to the issue of data security. 121here is an interesting article regarding applying quantum technology in spectroscopy using ML methods for advanced imaging applications.Lin et al. 122 designed an optical microscope using ML software for in situ identification of 2D nanostructures of MoS 2 and graphene.The database was created throughout the training phase and analyzed using the support vector machine (SVM) algorithm, and the computer learned the distinctive RGB information of optical pictures that were associated with the layers of graphene or MoS 2 (shown in Fig. 6a).Similarly, A strong ML-based read-out technique was created by Wiecha et al. 123 to enable the encoding of multiple-bit information.The optical data of silica nanostructures is either recorded as red-green-blue (RGB) values from dark-field imaging or as scattering spectra.Based on the input of both X-polarized and Y-polarized RGB datasets and the scattering intensities, a neural network was trained to produce 4-bit encoding values as the output (Fig. 6b).

Company name
QBs also face several challenges and obstacles that need to be addressed for their widespread adoption and practical use in healthcare settings.QBs often rely on advanced technologies, specialized equipment, and complex fabrication processes that lead to high development and production costs, making them less accessible for many medical applications.Incorporating QBs into existing medical diagnostic workflows and laboratory setups is challenging.While QBs are highly sensitive and specific, achieving optimal sensitivity and specificity in real-world clinical samples is challenging.Quantum systems are sensitive to their environment, and factors such as temperature fluctuations, electromagnetic interference, and even nearby materials can lead to quantum decoherence.Other challenges are privacy and data security, safety and biocompatibility, and clinical validation.
Techniques for brain imaging have benefited from the development of quantum sensor technology.Magnetoencephalography, which measures the magnetic fields produced by the electrical activity of neurons, is being improved using quantum sensors.QB has been used in studies that have demonstrated how they may be included in magnetoencephalography devices to allow the detection of activity in brain networks on a millisecond timescale while the person is moving.Even though these techniques are still in their infancy, we will undoubtedly learn more about neurological problems as they grow, which will make it easier to create apps for better disease detection and monitoring.

Conclusions
In conclusion, the development of QB is an innovative and revolutionary step in the field of medical diagnosis.These biosensors provide unmatched sensitivity, accuracy, and real-time monitoring capabilities for detecting biomolecules and disease-related indicators by utilizing the laws of quantum mechanics.QBs have a wide range of uses in the diagnostic field of medicine.QBs may also improve cancer biomarker detection, infectious disease diagnostics, and therapeutic development.There are still issues that need to be resolved despite the great promise.One of the crucial difficulties that calls for continual study and innovation is scalability.Other essential issues include coherence maintenance, specificity, and cost-effectiveness.In the future, it will be crucial for scientists, engineers, and medical specialists to work together to overcome these obstacles and turn QB technology into useful medical applications (Fig. 7).QBs have the potential to change medical diagnostics as the area develops, resulting in earlier illness identification, more individualized therapies, and eventually better patient outcomes across the world.QBs are poised to influence the future of medical diagnostics and open the door to precision medicine through continual improvements and incorporation into clinical settings.High sensitivity for multiplexed analysis, real-time monitoring, and disease biomarker detection are exhibited by QBs.Rapid on-site diagnosis and nonintrusive testing are promised.Key applications include quantumenhanced medical imaging, infectious agent identification, and cancer-specific biomarker detection.Accuracy is improved by integrating AI and data analytics.Point-of-care biosensors help personalized treatment by optimizing medication administration and avoiding resistance.Privacy, discrimination, and healthcare inequities are just a few of the ethical, legal, and societal ramifications.Diverse, fair access, patient empowerment through technology, and reducing input-output discrepancies in research are key to the future.A revolutionary route toward accurate, patient-centered healthcare is provided by QBs.

Figure 2 .
Figure 2. Schematic of Diamond NV quantum biosensor technologies.
described a virtual sensor array (VSA) based on QSM for identifying indicators of volatile organic compounds (VOC) present in human breath to aid in the diagnosis of diseases.To create the VSA, a thin layer of Ti 3 C 2 Tx MXene was used on the outer layer of a QCM.The VSA was then subjected to several VOC biomarkers.They kept track of changes in the MXene's mechanical and electrical characteristics, which were used to identify the VOCs biomarker.To detect VOC biomarkers, Fig. 4 shows a schematic example of VSA based on the Butterworth-Van Dyke Equivalent Model of QCM.

Figure 3 .
Figure 3. Illustrating the configuration and operational principle of a diamond magnetic microscope for tissue magnetic imaging.(A) The microscope enables integrated optical and magnetic images of tumor tissues by integrating a widefield ODMR device with a standard optical microscope.(B) The NV center's energy-level diagram is shown.(C) Tissue sections, marked with magnetic nanoparticles (MNPs), are detected by a dense NV center layer, just 100 nm thick.The blue structures are cell nuclei, while the brown lines are MNP-labeled membrane proteins.(D) The tissue's protein distribution may be seen in the generated magnetic picture, where the red and blue lines represent the magnetic signal poles.50 m is the scale bar.Adapted from Ref. 65.

Figure 4 .
Figure 4. Virtual Sensor Array Based on Butterworth Adapted from Ref. 81.

Figure 5 .
Figure 5. Detection of RNA of COVID-19 virus directly from a patient in a microfluidic channel using the NV diamond center.(a) sample collection (b) viral RNA detection in nanodiamond NV center.(c) Mechanism of magnetic noise quenching.(d) Energy level diagram of an NV center showing the optical transitions.Adapted from Ref. 33.

Figure 6 .
Figure 6.(a) Optical identification of 2D nanostructures in graphene and MoS 2 using a support vector machine (SVM) algorithm.The training set contains optical microscope photographs of graphene or MoS 2 samples at different light intensities.Following the judgment based on atomic force microscopy (AFM) and Raman spectroscopy, the red-green-blue (RGB) database and SVM model of graphene or MoS 2 samples (denoted as "training results") are established after SVM analyses of the RGB data collected from the training set.Referring to the "training results," graphene, MoS 2 , or heterostructures of these two materials can then be identified according to their optical microscope photographs (denoted as "testing results").(b) Optical information read-out via the RGB values of microscopy images based on an artificial neural network (ANN).Within a "4-bit" nanostructure geometry, the digital information is encoded in the four silicon blocks (block: "1", no block: "0").The structure corresponds to the 4-bit digit "1001" (decimal "9").The L-shaped sidewall is necessary to distinguish symmetric arrangements via polarized optical spectroscopy.Representative polarized (X-polarizations and Y-polarizations) filtered dark-field color images of representative 3 × 3 arrays of the "4-bit" digit structures are collected to extract the input feature, including R, G, and B values in both polarizations and the intensity value.A scheme of the fully connected ANN is used for the RGB classification task and generates the "4-bit" digit output.Adapted from Refs.122, 123.