Volume 3, Issue 2 pp. 130-140

REVIEW

Open Access

Recent Advancements in Microfluidic Biosensors for Clinical Applications

Haiyan Wang,

Haiyan Wang

orcid.org/0000-0003-4177-6633

Department of Laboratory Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China

Contribution: Conceptualization (equal), Formal analysis (equal), Investigation (equal)

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Wenjuan Wu,

Corresponding Author

Wenjuan Wu

[email protected]

Department of Laboratory Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China

Correspondence: Wenjuan Wu

([email protected])

Contribution: Conceptualization (equal), Formal analysis (equal), Project administration (equal)

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Haiyan Wang,

Haiyan Wang

orcid.org/0000-0003-4177-6633

Department of Laboratory Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China

Contribution: Conceptualization (equal), Formal analysis (equal), Investigation (equal)

Search for more papers by this author

Wenjuan Wu,

Corresponding Author

Wenjuan Wu

[email protected]

Department of Laboratory Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China

Correspondence: Wenjuan Wu

([email protected])

Contribution: Conceptualization (equal), Formal analysis (equal), Project administration (equal)

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First published: 10 March 2025

https://doi.org/10.1002/ila2.70002

Funding: This work was supported by National Natural Science Foundation of China (No. 82172326).

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ABSTRACT

The combination of low-consumption microfluidic chips and high-sensitivity biosensors enables rapid and accurate detection of complex target analytes. This integrated system holds significant potential for applications in disease diagnosis, health monitoring, and treatment management. Advances in novel biomaterials have led to device integration into wearable and implantable systems for point-of-care testing. Here, we review recent advances in microfluidic biosensors for clinical applications in detecting nucleic acids, proteins, metabolites, pathogens, and cellular components. We outline the prospects of integrated devices based on microfluidic biosensors for the analysis of biofluids such as sweat and discuss the remaining challenges facing the clinical application of microfluidic biosensors.

Abbreviations

AI: artificial intelligence
CK-MB: creatine kinase-myocardial band isoenzyme
CRISPR: clustered regularly interspaced short palindromic repeats
CRP: C-reactive protein
CTC: circulating tumor cell
cTnI: cardiac troponin I
ELISA: enzyme-linked immunosorbent assay
EV: extracellular vesicle
gRNA: guide RNA
LAMP: loop-mediated isothermal amplification
LOD: limit of detection
MIP: molecularly imprinted polymer
miRNA: microRNA
Myo: myoglobin
PCR: polymerase chain reaction
POCT: point-of-care testing
RF: radio frequency
SARS-CoV-2: severe acute respiratory syndrome coronavirus 2
S. aureus: Staphylococcus aureus
SERS: surface-enhanced Raman scattering

1 Introduction

Biosensors are analytical devices consisting of biological recognition and signal conversion elements: they represent an important development in point-of-care testing (POCT). The World Health Organization recommends that POCT devices should be affordable, sensitive, specific, user-friendly, rapid, robust, equipment-free, and deliverable to end users to allow on-site detection and diagnosis in the daily lives of patients and consumers [1]. With advancing technologies in energy drivers, detector materials, and digital connectivity, biosensors are expected to play a key role in revolutionizing the diagnosis and treatment of major diseases.

Electrochemical glucose meters are the most successful commercial POCT biosensors and have been used worldwide to help guide the treatment of diabetes. The detection principle of biosensors is based on a signal change triggered by the interaction between the biometric element and the target analyte, allowing specific detection. In clinical detection, target biosensor analytes mainly include nucleic acids, proteins, metabolites, cell components, and pathogens. Biometric elements can be bioactive substances such as antibodies, enzymes, nucleic acids, aptamers, peptides, and molecularly imprinted polymers (MIPs). The signal conversion element works physiochemically through electrochemical, electrochemiluminescent, optical, radio frequency (RF), or piezoelectric reactions, converting one signal into another to allow easy analyte measurement and quantification.

As POCT requirements become more diverse, miniaturized, integrated, and automated microfluidic devices have offered a new option for the development of portable detection devices that have attracted much attention. Given the inherent complexity of biological sample components and reaction systems, a series of sequential steps such as sample processing, signal amplification, and multiplex analysis are typically required [2]. Microfluidic technology enables a range of laboratory functions to be performed on a single micron-scale chip. By integrating a microfluidic channel with sensor electrodes and signal processing and transmission units, a low-consumption, high-speed, high-sensitivity chip analysis platform can be constructed, allowing personalized clinical diagnosis and treatment. The development of biomaterials and signal amplification strategies has facilitated the rapid development of microfluidic chip devices, enabling the extension of analyte detection from the laboratory to the home, community, and field.

In this review, we searched the literature from the Web of Science and PubMed archives for the topics “microfluidic” and “biosensor” between 2021 and 2024. Recent advances in microfluidic biosensors for target analytes including nucleic acids, proteins, metabolites, pathogens, and cellular components are detailed. Additionally, we highlight new developments in microfluidic biosensors, focusing on wearable devices, multiplex panels, implanted devices, and artificial intelligence, as well as the clinical challenges facing their application.

2 Microfluidic Biosensor Detection of Target Analytes

2.1 Nucleic Acid

Nucleic acid testing has grown significantly in the areas of genetic disease detection, liquid biopsy, and microbial identification. Various methods have been used, including polymerase chain reaction (PCR), next-generation sequencing, loop-mediated isothermal amplification (LAMP), and clustered regularly interspaced short palindromic repeats (CRISPR)/Cas systems. The sensitivity of the CRISPR/Cas system critically depends on the efficiency of nucleic acid amplification techniques, which determine the detection limit. CRISPR/Cas system uses guide RNA (gRNA) to direct the Cas protein to specific target sequences, the specificity of which is largely determined by the exact matching of the gRNA to the target sequence. By carefully designing the gRNA to match a unique region of the target sequence, the CRISPR/Cas system can reduce cross-reactivity and false positives. Additionally, CRISPR/Cas-based microfluidic biosensors avoid off-target effects through chemical modification and engineering approaches [3]. By using advanced bioinformatics tools to screen potential off-target sites, researchers can ensure that the gRNA is unique to the target sequence. Given the importance of simple and rapid diagnosis in the early stages of disease, the development of sensitive, miniaturized, and automated microfluidic devices for nucleic acid-based diagnosis is very promising. However, because of the low nucleic acid yield and quality of complex samples in clinical settings, microfluidic-based nucleic acid detection faces technical challenges in terms of signal amplification and interference [4].

2.1.1 DNA

Circulating DNA is a non-invasive alternative indicator of disease liquid biopsy. A microfluidic biosensor allowing the ultrasensitive and specific detection of nasopharyngeal carcinoma-associated Epstein-Barr virus DNA was constructed using bifunctional split-DNase and dendritic probe cascade signal amplification technology on a microbead array chip [5], achieving an excellent limit of detection (LOD) of 0.36 fM and a wide linear range of 1–10³ fM for simulated samples. Another disease, mastitis, can be diagnosed by testing for Staphylococcus aureus, which requires high sensitivity and selectivity. A microfluidic impedance factor sensor for the detection of S. aureus DNA consisting of a chitosan/sericin membrane layer functionalized with an S. aureus DNA capture probe, was developed and demonstrated to have an accuracy of 89% and an LOD of 5.90 × 10⁻¹⁹ mol/L [6]. A DNA detection platform combining microfluidic DNA extraction, ligase chain reaction, and acoustic measurement using a highly expandable liposome as a signal enhancer has also been constructed [7]; its LOD for the BRAF gene V600E, a common mutation in various malignancies such as thyroid papillary carcinoma, reached 220 aM for human plasma, offering the possibility of automated detection of single nucleotide variations in raw samples from tumor patients.

2.1.2 RNA

MicroRNAs (miRNAs) are involved in the pathogenesis of various diseases, and those circulating in body fluids such as plasma and serum are considered biomarkers for diagnosis, prognosis, and outcome evaluation. Most miRNA sensors use cross-hybridization of the target with the capture probe and are usually designed as sandwich or competition methods. Although the sandwich method has a narrow dynamic range, it can discriminate oligonucleotide sequences with a single base mismatch with good sensitivity and selectivity [8]. An electrochemical nucleic acid biosensor integrated into a microfluidic chip was fabricated, allowing rapid detection within 30 min, with an LOD down to 1 aM for synthetic miRNA-122 [9]. The problem of base mismatch was overcome by using a methylene blue solution, allowing partial hybridization to be distinguished from complete and complementary hybridization. A novel microfluidic biosensor combining multifunctional nanosurfaces, double-strand specific nuclease-assisted target cyclic amplification, and double-surface enhanced Raman scattering (SERS) detection was also developed for miRNA-21 measurement, achieving a wide linear range of 10 fM–10 nM for mouse serum [10].

2.2 Protein

2.2.1 Neurodegenerative Diseases

With the increasing number of people suffering from neurodegenerative diseases such as dementia, ultrasensitive biosensors for low-level biomarkers can enable early assisted diagnosis, helping patients to benefit from early intervention or personalized treatment. A double-microring resonant microfluidic chip with drop addition was developed to quantify the well-known Alzheimer's disease biomarker β-amyloid 1–42, demonstrating an LOD of 9.02 pg/mL for simulated serum [11]. Aminoacyl transfer RNA synthase complex-interacting multifunctional protein-2, a potential biomarker for Parkinson's disease, was detected by a capillary flow-driven microfluidic cartridge integrating a metal-enhanced fluorescence biosensor, which had a linear range of 10⁻²–10⁴ ng/mL and an LOD of 0.007 ng/mL for human serum [12]. A microfluidic-based magnetoimpedance biosensor platform was constructed using Dynabeads M-450 Epoxy (Invitrogen, Waltham, MA, USA) as the magnetic label for plasma glial fibrillary acidic protein, a useful biomarker for differentiating stroke subtypes, with an LOD of 1.0 ng/mL for plasma from acute stroke patients [13].

2.2.2 Cardiac Diseases

Acute myocardial infarction is a fast-onset, high-mortality cardiovascular disease; the development of automated, rapid, sensitive, and portable POCT devices for biomarkers for detecting this condition is critical to facilitate timely clinical decision-making and improve patient outcomes. Based on a signal amplification strategy using a novel superoxide dismutase, a dual-channel microfluidic chip was integrated with a sandwich-type cathodic photoelectrochemical biosensor for the ultrasensitive and efficient detection of cardiac troponin I (cTnI) [14]; its linear range was 0.1 pg/mL–100 ng/mL, and the LOD was as low as 0.042 pg/mL for human serum. A microfluidic electrochemical biosensor for the detection of N-terminal hormone pronatriuretic peptide, a key indicator to assess the heart failure severity, was developed using silver nanoparticles in a trehalosaccharide matrix doped with Na₂SO₃ as an oxygen scavenger dried directly in a microfluidic channel, allowing dry and ready-to-use storage for at least 18 weeks [15]. Key features of the sensor included a low LOD (0.57 ng/mL for human serum), small sample size, simple detection strategy, and readily available dry long-term stable reagents, making it an ideal home test device with the potential to replace the commonly used lateral flow analysis. Compared with traditional detection methods, such as enzyme-linked immunosorbent assays (ELISAs), these microfluidic biosensors have the advantages of rapid detection, portability, and cost-effectiveness, with better limitations of sensitivity under certain conditions and sample handling requirements in clinical settings.

2.2.3 Cancer

Tumor biomarker detection is also an important research direction.

Applying a novel superoxide dismutase-loaded honeycomb manganese oxide nanostructure as a co-catalyst signal amplification label, a microfluidic chip integrated with a microelectrode and a cathodic photoelectrochemical biosensor was constructed for the detection of cytokeratin 21-1, a biomarker for non-small-cell lung cancer [16]. The chip had a good linear range of 0.1 pg/mL–100 ng/mL and an LOD of 0.026 pg/mL for human serum.

2.3 Metabolites

2.3.1 Glucose

Diabetes is a globally prevalent chronic disease that leads to serious complications. Continuous monitoring and control of blood glucose levels can delay and largely prevent these complications. Glucose biosensors are mainly based on the principle of measuring the change in current generated by the reaction of glucose oxidase or dehydrogenase with glucose in the blood. A vertically aligned array of carbon nanotube sensors, combined with a miniature potentiostat and infusion pump, was developed as a low-cost microfluidic chip for glucose monitoring [17]. Using microelectromechanical technology, a self-assembling and fully packaged microfluidic biosensor for glucose detection was also proposed, providing a simple construction strategy for the miniaturization of clinical medical devices [18]. A microfluidic resonator chip system providing a high-intensity surface electromagnetic field and a microfluidic cavity loaded with glucose reaction solution was also constructed to allow for non-contact, rapid, real-time glucose measurement [19]. Additionally, a selective in situ fixation method for microcontact printing mixed with a self-assembled monolayer on a working electrode was developed, achieving continuous and time-independent microfluidic electrochemical glucose detection [20]. Another study integrated a microwave biosensor based on a three-ring microstrip patch antenna into a bionic microfluidic device for glucose detection, achieving an LOD of 0.077 mg/mL for glucose solution in a rapid response time of only 150 ms [21]. A self-powered microfluidic glucose biosensor based on biofuel cells and wireless electronics has also been constructed, showing a linear interval of 0–10 mM and an LOD of 0.48 mM for human blood, allowing direct detection and signal processing without the use of a potentiostat or galvanostat [22]. Additionally, a 3D origami design of a paper-based sensor was constructed to achieve ultrasensitive detection of glucose, with a linear range of 1 × 10⁻⁹–1 × 10⁻⁴ mol/L and an LOD of 4.6 × 10⁻¹⁰ mol/L for human blood [23]. An economical and environmentally friendly biosensor for glucose detection was also developed by utilizing a renewable material, biochar, as a platform for anchoring redox mediators and bioreceptors, with a wide linear dynamic range of 0.05–5.0 mM and an LOD of 0.94 μM for human serum [24]. Additionally, microfluidic paper-based analytical devices combined with a smartphone provide an ideal platform to take advantage of online result processing, aiming to improve quantification capability and data communication. A user-friendly and low-cost cellulose device of this nature was constructed for glucose detection, providing an LOD of 0.1 mM for human tears and results in 5 min by visual observation of color intensity without the need for additional equipment or trained personnel [25].

2.3.2 Lipids

Hyperlipidemia is a major predisposing factor for cardiovascular disease and other conditions. A low-cost enzymatic optical biosensor for triglyceride detection was developed using an Arduino-based microfluidic platform, achieving a detection range of 7.6741–58.835 mg/dL for triglyceride solution [26]. A different microfluidic biosensor integrating a magnetically retained enzyme microreactor coupled to a remote fluorometer was constructed for total cholesterol detection, in which two enzymes (cholesterol esterase and cholesterol oxidase) were immobilized on magnetic nanoparticles, with a dynamic range of 0.005–10 mM and an LOD of 1.1 μM for human serum [27].

2.3.3 Renal Function Markers

Creatinine and urea are considered primary biomarkers for assessing the progression of kidney disease. A photonic nanostructure-based biosensor with three different label-free sensing layers was proposed to measure creatinine concentration, with a detection range from 80.9 to 85.28 μmol/L for creatinine solution [28]. Additionally, an efficient, convenient, and low-cost polydimethylsiloxane microfluidic device was fabricated using 3D printing and transfer techniques, providing a linear range of 10–50 mg/dL and a sensitivity of 3.02 mV(mg/dL) for urea solution [29].

2.3.4 Neurotransmitters

Dopamine is the main neurotransmitter released by dopaminergic neurons and plays an important role in neurodegenerative diseases. A microfluidic biosensor functionalized with the hybrid material consisting of indium phosphate and polyaniline nanointerfaces was developed for dopamine measurement, with a linear range of 10⁻¹⁸–10⁻¹¹ M and an LOD of 1.83 × 10⁻¹⁹ M for human serum [30]. A different microfluidic MIP biosensor utilizing the MXene/nitrogen-doped electrochemically exfoliated graphene nanocomposite was introduced to achieve highly sensitive, specific, and reliable detection of agmatine, with a wide linear range of 1 nM–100 μM and an LOD of 0.1 nM for human plasma [31].

3 Microfluidic Biosensor Detection of Clinical Conditions

3.1 Pathogens

The global health system is currently facing increasing challenges because of the dynamic evolution of pathogens. In recent decades, a rise in outbreaks of human infectious disease has caused substantial morbidity and mortality, as demonstrated by the COVID-19 pandemic [32]. Rapid and effective identification of pathogens is critical for the prevention and control of infectious diseases. Ideally, very low levels of pathogens should be detected before symptoms develop.

The most commonly used methods for clinical pathogen detection include culture, ELISA, high-performance liquid chromatography-mass spectrometry, and PCR. These traditional methods perform well in terms of sensitivity and specificity, but are time-consuming, require laboratory facilities, and carry a risk of environmental contamination [33]. The advantage of microfluidic devices over traditional methods is that they integrate the antigen-antibody or PCR reaction on a closed chip and provide a miniaturized portable controlled detection environment, reducing environmental contamination and requiring less infrastructure to run.

3.1.1 Viruses

The ability to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a major challenge in controlling the COVID-19 pandemic. A powerful microelectromechanical system-based impedance biosensor was developed that enabled SARS-COV-2 detection in clinical swab specimens within 40 min with a sensitivity of 26 tissue culture infectious dose 50/mL for clinical swabs [34]. Additionally, an electrochemical capillary-driven ELISA device was developed for the detection of SARS-CoV-2 nucleocapsid protein, with an LOD of 627 PFU/mL for clinical nasal swabs [35]. The device was considered as an alternative to traditional ELISA because of its low cost, low sample and reagent consumption, low waste generation, and short analysis time. A different label-free integrated microfluidic plasmonic biosensor was designed for the detection of COVID-19 receptor binding domain protein, with a wide detection range of 0.5 ng/mL–50 μg/mL for receptor binding domain protein solution [36]. Additionally, a self-powered microfluidic chip for the detection of SARS-CoV-2 nucleocapsid protein was developed to automatically perform the entire analysis of electrochemical immunobiosensing analysis without active fluid handling, with a linear detection range of 10–1000 pg/mL and an LOD of 3.1 pg/mL for the nucleocapsid protein solution [37]. A microfluidic electrochemical impedance biosensor for the detection of SARS-CoV-2 antigen was also constructed, coupled with a smartphone-based readout, having a linear range of 16 fM–160 nM and an LOD of 19.09 fM for human nasopharyngeal swabs [38]. However, inter-smartphone or inter-circumstance result variations limit the analytical potential of smartphone-based microfluidic biosensors, especially in the case of optical sensing. By combining an all-fiber optical system and a multimode fiber bioprobe, a novel all-fiber Fresnel reflection microfluidic biosensor was constructed to quantify SARS-CoV-2 IgM and IgG antibodies within 7 min, with LODs for human serum of 0.82 and 0.45 ng/mL, respectively [39]. An indium gallium zinc oxide-based biosensor field-effect transistor was also developed to simultaneously detect SARS-CoV-2 spike proteins and antibodies in less than 20 min, with LODs of 1 pg/mL and 200 ng/mL, respectively [40]. These studies suggest that the development of rapid and accurate simultaneous detection systems for pathogen antigens and antibodies will play a critical role in controlling global epidemic outbreaks.

3.1.2 Bacteria

A fully integrated microfluidic biosensor consisting of three functional parts (immunomagnetic separation, nucleic acid extraction and purification, and CRISPR/Cas12a signal detection) was developed for finger-operated gastrointestinal pathogen nucleic acid detection, with a detection range of 10²–10⁸ colony-forming units (CFU)/mL and an LOD of 10 CFU/mL for Escherichia coli O157:H7 [41], and an LOD of 1.93 × 10² CFU/mL for Salmonella typhimurium [42]. A fully paper-based microfluidic device integrated with LAMP and ssDNA functionalized graphene oxide nanobiosensors was also developed, with an LOD of 6 DNA copies for Neisseria meningitidis [43].

3.1.3 Parasites

An electrochemical microfluidic aptasensor based on 3D gold nano/microislands was proposed for Cryptosporidium parvum antigen, with a linear range of 10–100,000 oocysts/mL and an LOD of 10 oocysts/mL for stool and tap water [44]. A microfluidic biosensor using molybdenum disulphide modified thin-core microfibres was also developed for the detection of Toxoplasma gondii antibody, with a detection range of 1 pg/mL–10 ng/mL and an LOD of 87 fg/mL for the antibody solution [45]. Additionally, a microfluidic biosensor based on hyperspectral interference amplification complex analysis combined with an asymmetric dipole complex strategy was designed for the detection of the Plasmodium falciparum dhfr gene; it largely avoided false positives caused by primer dimers and non-specific products, with an LOD of 3.17 ng/μL for the synthetic plasmid [46].

3.2 Cellular Components

3.2.1 Cells

Detecting circulating tumor cells (CTCs) is a novel, non-invasive liquid biopsy technique that can be used for precision medicine, treatment management, and efficacy assessment, facilitating a better understanding of the process of tumor metastasis. CTCs can be as low as 1 cell/mL blood, so extremely high detection sensitivity and specificity are required [47]. Electrical impedance biosensors combined with a microfluidic device can analyze fundamental biological processes at the single-cell level [48]. A microfluidic device integrated with an electrochemical impedance spectroscopy biosensor was designed to capture and quantify EpCAM-positive and CD36-positive breast cancer cells with an LOD of 3 CTCs [47]. A lectin-based microfluidic biosensor based on the specific recognition of cell surface glycans and fluorescence-labeled lectins was also developed to distinguish melanoma cells from normal skin cells [49].

3.2.2 Extracellular Vesicles

Extracellular vesicles (EVs) carrying disease-related molecular profiles have shown great potential for reproducible and non-invasive disease diagnosis. The unique advantages of the microfluidic platform make it ideal for the separation and detection of EVs, including its low sample volume, faster processing speed, and higher recovery rate [50]. A silicon wafer microchip using a membrane-sensing peptide probe as the signal recognition element was fabricated for EV detection, achieving an LOD of 10⁴ EVs/mL for the cell culture media of H1975 cells [51]. An integrated biochip platform integrated with CD81 antibody-modified immunomagnetic beads was also developed for the detection of L1CAM-positive neuronal EVs associated with Parkinson's disease, with a sensitivity of 1 pg/mL for human serum [52].

The sugar patterns of EVs released by cancer cells are promising candidates for cancer monitoring, as they have similar patterns to the cells of their origin. EV glycan phenotype detection was performed based on the combination of a microfluidic platform, SERS, and lectin-glycan affinity recognition for multiple analysis of EVs, successfully discriminating patients with early-stage non-small-cell lung cancer from those with benign lung disease [53].

3.2.3 Exosomes

Exosomes, a class of EVs with a diameter of 30–150 nm, are emerging targets for tumor liquid biopsy. It remains particularly challenging to isolate and detect tumor-derived exosomes, which vary in size compared with free tumor cells or DNA. Improving capture efficiency and maintaining exosome integrity are important to promote exosome biomarker conversion [54]. A surface-functionalized terahertz metamaterial biosensor modified with PIK3CA antibody was proposed for exosome detection, which effectively discriminated breast cancer patients from healthy controls [55].

4 Perspective of Microfluidic Biosensors

4.1 Wearable Devices

Wearable biosensors have attracted considerable interest because of their potential for biomarker monitoring, toxicity assessment, and treatment tracking. Several wearable biosensors are already on the market, such as the well-known Abbott FreeStyle Libre sensor. Electrochemical and optical biosensing strategies have been combined with novel biocompatible flexible materials as devices for bio-specific recognition. However, difficulty in scaling, signal drift, short lifetimes, poor repeatability, and other persistent defects severely limit the field application of wearable devices.

Thanks to the applications offered by wearable biosensors, sweat—a biological fluid—is beginning to attract attention [56, 57]. Sweat has been shown to contain physiologically relevant biomarkers and is easy to collect, providing medical information at the molecular level in a completely non-invasive manner and allowing continuous monitoring of certain parameters. As sweat flows from the skin surface, a sampling system and microfluidic fluid transport system are required to properly deliver it to the molecular biosensors on a wearable devices [58]. This automated microfluidic module can eliminate the influence of the wearer's sweat rate on the biosensor response, ensuring the reliability of the detection results and the comparability between different wearers and detection times.

The most promising application for wearable devices is the continuous monitoring of blood glucose levels in diabetic patients. An innovative wearable microfluidic biosensor for the precise analysis of glucose in sweat was constructed using a Pt single-atom catalyst dispersed on tricobalt tetroxide nanorods and reduced graphene oxide, with a detection range of 1–800 μM for glucose solution [59]. A flexible, wearable, biocompatible, and biodegradable sweat sensor was also developed by embedding a new fluorescent nanosensor probe of borate-functionalized heteroatom-doped carbon quantum dots in a paper-based analytical device and integrating it with a microfluidic channel based on hydrophilic cotton threads to measure sweat glucose concentration in real time with smartphone readings [60]. Using fluorescence and colorimetric changes, the LODs for glucose concentration were 1.4–2.0 μM in the pH range of 4.5–7.5 for human sweat.

A fusion version of laser-induced graphene sensors with soft-band polymer microfluidics was also developed to quantify sweat metabolites (glucose and lactic acid) and electrolytes (sodium) for potential hydration and fatigue monitoring. The LODs for glucose and lactic acid in sweat were 8 and 220 μM, respectively. The linear ranges of glucose, lactic acid, and sodium for human sweat were 0–1, 0–32, and 10–100 mM, respectively [61]. A wearable electrochemical biosensor system integrated into a smartwatch with an e-paper display with a wireless communication module was also developed that continuously detects nine essential amino acids as well as common vitamins, metabolites, and lipids (vitamins B6, C, D3 and E, glucose, uric acid, creatine, creatinine, and cholesterol), hormones (cortisol), and drugs (mycophenolic acid), providing an ultra-wide range of selective biomarker detection with implications for personalized nutrition and precision therapy [62]. A 3D-printed flexible wearable health monitor was also built to provide reliable and quantitative in situ measurements of sweat rate along with glucose, lactic acid, and uric acid concentrations during physical activity [63].

Cortisol, a major stress hormone, provides real-time information about human stress states. An MIP-RF wearable sensor system was designed for the real-time, non-invasive assessment of sweat cortisol [64]. The sensor detected cortisol over a physiological range of 0.025–1 μM for human sweat and was stable for up to 28 days. An integrated analytical tool for portable sweat cortisol detection based on paper microfluidics, including paper for flow management and reagent loading, and a competitive magnetic bead immune sensor was also developed, with a linear range of 10–140 ng/mL for cortisol solution [65]. Additionally, a 3D origami microfluidic biosensor for the detection of cortisol levels in human sweat was developed based on fluorescence-labeled aptamers and fluorescence resonance energy transfer, with an LOD of 6.76 ng/mL for artificial sweat [66].

Continuous monitoring of sweat lactic acid and assessment of changes from aerobic to anaerobic metabolism are important for optimizing athletic training and physical exercise in rehabilitation patients and older adults. A microchannel lactate sensor was developed to overcome bubble interference with sweat, with a linear range of 1–50 mM for lactate solution [67]. A flexible wearable electrochemical sensor for the detection of levodopa and uric acid in sweat was also fabricated for pharmacokinetic monitoring of levodopa and gout management [68]. Additionally, a wearable microfluidic plasma microneedle sensor was developed for interstitial fluid sampling and minimally invasive uric acid monitoring, with an LOD of 0.51 μM for uric acid solution [69]. Real-time detection of the inflammatory biomarker C-reactive protein (CRP) in sweat may also aid in chronic disease management. A wearable electrochemical patch based on a graphene sensor array was reported with an LOD of 8 pM for CRP solution [70].

4.2 Multiplex Panels

In certain cases, clinical assessments based on a single biomarker are not sufficient to adequately diagnose or monitor treatment. A key requirement in the development of diagnostics is to assess the concentration of the target analytes under a given set of circumstances. This inevitably implies the need for multiplex panels, the simultaneous measurement of multiple analytes from a single sample, to improve accuracy.

There is an urgent need for multichannel biosensors that enable low-cost, easy-to-use and rapid field testing. A simple, flexible, and highly scalable strategy for implementing microfluidic multichannel electrochemical biosensors has been proposed [71]. The technique could be used to detect multiple drugs and/or biomarkers simultaneously, which would be an important step in chronic disease management. A microfluidic electrochemical device for the plasma detection of cTnI and myoglobin (Myo) was reported with an LOD as low as pg/mL, enabling rapid dual-electrode detection [72]. Dual-mode sensors can dynamically track antigen-antibody interactions during sensing, self-validate by providing signals in both modes and reduce false readings. A parallel optofluidic microfluidic chip biosensor for the simultaneous detection of three cardiac biomarkers (cTnI, Myo, and creatine kinase-myocardial band isoenzyme [CK-MB]) was constructed, with LODs of 3.7 pg/mL for CK-MB, 0.5 ng/mL for Myo, and 2.6 pg/mL for cTnI in a standard buffer sample, all of which covered the diagnostic limit of AMI [73]. The combination of β-isomeric C-terminal peptide of type I collagen and intact N-terminal peptide of type I procollagen provides an accurate overview of bone turnover markers; a multiplex, label-free microfluidic immunosensor was described with LODs of 15 ng/L and 0.66 μg/L, respectively, for clinical plasma [74]. The sensor could be stored at room temperature for > 6 months, making it suitable for use near patients and outside central laboratories.

Minimally invasive screening methods based on EV-encapsulated miRNA biomarker assessment can achieve an early diagnosis of breast cancer and improve survival. A microfluidic system integrating EV capture and field-effect transistor sensors was constructed for the quantification of EV-encapsulated miRNA-195 and miRNA-126 in breast cancer [75]. The system automated the entire biomarker quantification process within 5 h, with detection limits for miRNA-195 and miRNA-126 purified standards of 84 and 75 aM, respectively, highlighting its potential as a sensitive platform for early breast cancer diagnosis. Different multiplexed versions of electrochemical microfluidic biosensors have also been developed for the amplification-free simultaneous quantification of up to eight miRNAs on a CRISPR biosensor [76]. Measurements of two miRNAs (miRNA-19b and miRNA-20a) from the miRNA-17-92 cluster, which are dysregulated in the blood of patients with pediatric medulloblastoma, confirmed the suitability of the platform for unamplified parallel detection of multiple nucleic acids.

Influenza A, influenza B, and SARS-CoV-2 circulate during the flu season and have very similar symptoms. To improve symptomatic and accurate treatment, there is an urgent need for simultaneous multi-pathogen detection technology for these viruses. A homogeneous nucleic acid detection system based on DNA-RNA hybridization was developed that can be used in combination with microfluidic chips and portable electrochemical instruments for rapid, sensitive, and simultaneous detection of influenza A, influenza B, and SARS-CoV-2 in clinical samples [77]. The LOD of synthetic DNA was 0.3 aM and the LOD of engineered bacteria was 100 CFU/mL. An ultrasensitive fluorescent biosensor based on a signal amplification strategy and a microfluidic fluidized bed was also developed that can simultaneously detect E. coli O157:H7, Salmonella paratyphi A, and Salmonella paratyphi B at 101 CFU/mL within 1.5 h [78].

Multiplex panels can be achieved by two strategies: one based on multiple recognition elements attached to a single electrode, and the other based on multiple recognition elements attached to multiple electrodes, with each electrode corresponding to one analyte [79]. However, technological issues such as potential cross-reaction between signal recognition ligands and their targets limit their clinical application. The issue of cross-reactions in multiplexed detection panels arises from the complex interplay of multiple components within the system. The mechanisms behind cross-reactions include non-specific binding of recognition elements, overlapping signal pathways, inadequate surface functionalization, competition for similar antigens, and matrix effects, all of which can lead to false signals. To address these challenges, high-affinity and -specificity antibodies, aptamers, or probes can be designed to minimize non-specific interactions. Physical separation of detection zones within microfluidic chips can prevent diffusion of reagents or signals. Additionally, computational tools consisting of data processing and algorithmic corrections can help predict and reduce cross-reactivity.

4.3 Implanted Devices

Real-time and continuous monitoring by implanted devices can accurately determine analyte fluctuations and provide abundant clinical information, which is beneficial for precise disease management. These implanted devices can provide an alternative solution for chronic disease management and are in high demand for home healthcare [69]. To date, the Food and Drug Administration has approved some commercial implanted devices based on microneedle-based biosensors, such as Abbott FreeStyle Libre, a patch that continuously monitors glucose in interstitial fluid [80]. Considering that they must maintain detection in the body for several days, implanted biosensors face key challenges, including analytical performance in terms of sensitivity, specificity, and dynamic range, and the need for durable mediators with favorable biocompatibility and biosafety.

5 Challenges Facing Microfluidic Biosensors

5.1 Stability

Although the integration of microfluidic chips and biosensors has many advantages for clinical diagnostics, there are still several important issues that need to be addressed. Device stability is the most important and yet overlooked factor in ensuring high-quality results. Reagents in microfluidic biosensors, such as enzymes and antibodies, may face evaporation or spillage during improper transport and storage [1]. Unpackaged reagents are also susceptible to failure if stored in an unfavorable environment. Lyophilization, a technique often used in the reagent process of microfluidic biosensor devices, imposes relatively strict storage temperatures and short lifetimes [81].

5.2 Standardization

Microfluidic biosensors have been developed for a variety of targets, but few have been commercialized. Initial laboratory evaluation may be convenient but may not reflect the true sensor characteristics when employed in real patient samples. A future direction for the clinical translation of microfluidic biosensor devices must aim to establish diagnostic standardization to objectively evaluate test results. For example, compared with blood, other bodily fluids such as sweat, saliva, and tears are more susceptible to sampling location, environment, and technique, emphasizing the need for standardization of bodily fluid sampling [1]. Consolidation efforts of key stakeholders consisting of quality control managers, primary care physicians, device technologists, patients, and consumers will provide an opportunity for coordination and standardization of the clinical translation of microfluidic biosensors.

5.3 Wireless Transmission

Most reported microfluidic biosensors cannot perform real-time monitoring because they are designed to be disposable and lack an independent operating system. A bulky external device such as a handheld reader is needed for reading and transmitting measured data, which reduces device accessibility, flexibility, and portability. For microfluidic biosensors to make a real impact on clinical diagnostics and POCT, the technical challenges of wireless transmission must be addressed.

A common solution is to integrate ubiquitous devices such as smartphones. There are typically two strategies to achieve wireless transmission in microfluidic biosensors. The first is to use the built-in camera of a smartphone as an optical signal processing system to achieve quantitative analysis by analyzing the optical signal. For example, fluorescence and colorimetric signal changes for surface plasmon resonance can be captured by a common mobile phone camera [82]. The other is to use wireless modules such as near-field communication, radio frequency identification devices, WiFi, and Bluetooth to send measurement data to a smartphone, which then analyzes the target, as in an electrochemical sensor system used to monitor blood CRP [83] or sweat cortisol [64]. These innovative approaches improve the usability and accessibility of microfluidic biosensors, enabling the monitoring of critical disease-related biomarkers outside the laboratory.

5.4 Artificial Intelligence

The integration of artificial intelligence (AI) and microfluidic biosensors makes it possible to achieve precision diagnosis and personalized medicine. Recently, the emergence of the Internet of Things and cloud computing has brought new opportunities for microfluidic biosensors. Intelligent decision modules based on machine learning algorithms have been incorporated into microfluidic biosensors, enabling disease diagnosis and risk prediction, large-scale medical data mining, and public health tracking [79]; an example is a deep learning neural network-based cloud server data analysis system embedded in a smartphone, which enables color data acquisition, interpretation, auto-correction, and display [84]. A 3D-printed microfluidic biosensor coupled with fluorescence microscopy and machine learning-enabled AI methodology was proposed to count leukocyte particles, achieving a good correlation (R² = 0.99) when compared with the ground truth [85].

As microfluidic biosensors generate increasing volumes of data, effective data management and utilization are crucial for leveraging AI in diagnostics. Data collected from biosensors often comes in various formats, including raw signals, processed data, and metadata. Standardized data formats and frameworks are carried out to manage and interpret large datasets, ensuring consistent data representation and compatibility between different biosensor systems. Researchers can continuously implement machine learning algorithms with new data and immediate feedback loops, improving device robustness and diagnostic performance.

6 Summary

We have summarized several advances in the field of microfluidic biosensors between 2021 and 2024. To provide accurate diagnosis without laboratory assistance, the next generation of microfluidic biosensors should be rapid, affordable, user-friendly, highly integrated, and intelligent to end users, enabling on-site testing and diagnosis for individual patients. However, the stability of the integrated components, the complexity of the biological matrix, and the analytical properties of the materials used hinder and limit their clinical translation and application. The microfluidic biosensor systems reported so far are still in the early stages of development, and we expect that the continuous improvement of these sensors will make them widely available in the near future.

Author Contributions

Haiyan Wang: conceptualization (equal), formal analysis (equal), investigation (equal). Wenjuan Wu: conceptualization (equal), formal analysis (equal), project administration (equal).

Acknowledgments

The authors have nothing to report.

Ethics Statement

The authors have nothing to report.

Consent

The authors have nothing to report.

Conflicts of Interest

This article belongs to a special issue (SI)-Recent Advances of Point-of-Care Testing. As the journal's Editorial Board Member and SI's Guest Editor, Professor Wenjuan Wu was excluded from all editorial decision-making related to the acceptance of this article for publication. The remaining author declares no conflicts of interest.

Open Research

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this article.

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Volume3, Issue2

June 2025

Pages 130-140

Recent Advancements in Microfluidic Biosensors for Clinical Applications

ABSTRACT

Abbreviations

1 Introduction

2 Microfluidic Biosensor Detection of Target Analytes

2.1 Nucleic Acid

2.1.1 DNA

2.1.2 RNA

2.2 Protein

2.2.1 Neurodegenerative Diseases

2.2.2 Cardiac Diseases

2.2.3 Cancer

2.3 Metabolites

2.3.1 Glucose

2.3.2 Lipids

2.3.3 Renal Function Markers

2.3.4 Neurotransmitters

3 Microfluidic Biosensor Detection of Clinical Conditions

3.1 Pathogens

3.1.1 Viruses

3.1.2 Bacteria

3.1.3 Parasites

3.2 Cellular Components

3.2.1 Cells

3.2.2 Extracellular Vesicles

3.2.3 Exosomes

4 Perspective of Microfluidic Biosensors

4.1 Wearable Devices

4.2 Multiplex Panels

4.3 Implanted Devices

5 Challenges Facing Microfluidic Biosensors

5.1 Stability

5.2 Standardization

5.3 Wireless Transmission

5.4 Artificial Intelligence

6 Summary

Author Contributions

Acknowledgments

Ethics Statement

Consent

Conflicts of Interest

Open Research

Data Availability Statement

References

References

Related

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