Early and accurate detection of disease markers is essential for timely diagnosis and the advancement of personalized healthcare. While blood and cerebrospinal fluid remain clinical gold standards, this review emphasizes non-invasive biofluids — urine, saliva, tears, and sweat — as accessible and patient-friendly alternatives. These fluids carry a range of biomolecular signatures, including nucleic acids, proteins, metabolites, and microbial components, which together offer potential for continuous and real-time health monitoring.
The review, published in Nanotechnology (2026) by authors from the University of Western Ontario, frames non-invasive biofluid analysis as a complementary diagnostic pathway that could reduce patient burden and enable longitudinal sampling outside clinical settings. Indexed MeSH terms include Biomarkers/analysis, Biosensing Techniques/methods, Body Fluids/chemistry, and Nanotechnology.
The article summarizes biomarkers associated with major diseases and their detectability in non-invasive biofluids. It highlights cancer, diabetes mellitus, and neurodegenerative disorders as focal conditions for which urine, saliva, tears, and sweat can carry informative molecular signatures. Types of measurable analytes in these biofluids include:
The review stresses that non-invasive biofluids vary in analyte concentration and matrix complexity compared with blood or cerebrospinal fluid, which affects assay design and required analytical sensitivity.
Recent advances in nanotechnology have transformed biomarker detection by enabling analytical platforms with high sensitivity, selectivity, and rapid response. The review describes how nanoscale materials and device architectures are applied to detect low-abundance targets in complex biofluid matrices. Key sensing modalities discussed include electrochemical, optical, and affinity-based approaches that leverage nanomaterials to amplify signals or improve target capture.
Nanomaterial-enabled strategies are presented as particularly relevant for non-invasive biofluids because these matrices often contain lower analyte concentrations and more potential interferents than blood. Enhancements provided by nanomaterials can include increased surface area for capture, plasmonic or fluorescent signal enhancement, and catalytic or electronic amplification mechanisms.
The review highlights the role of engineered nanostructures in improving detection performance. Advanced nanostructures—such as functionalized nanoparticles, nanostructured electrodes, and hybrid nanocomposites—can increase assay sensitivity and selectivity through optimized surface chemistries and tailored physical properties. These structures help overcome matrix effects from urine, saliva, tears, and sweat and can be integrated into compact sensing platforms suitable for point-of-care or wearable formats.
The authors note that choice of nanostructure and surface functionalization must consider stability, biocompatibility, and reproducibility when transitioning toward clinical use.
The convergence of wearable sensing technologies with artificial intelligence frameworks is examined as an emerging paradigm for continuous biomarker monitoring and intelligent disease management. Wearable devices that sample sweat, interstitial fluids, or tears can provide longitudinal data streams. Machine learning and AI can process these complex, high-frequency data to identify patterns, detect deviations from baseline, and support decision-making.
The review positions the integration of wearables and AI as a key step toward real-time, personalized healthcare, enabling proactive interventions and improved disease tracking outside traditional clinical settings.
The article outlines several challenges that must be addressed to realize clinical translation of non-invasive biofluid diagnostics. These include:
The authors emphasize that overcoming these hurdles will require interdisciplinary collaboration among engineers, clinicians, materials scientists, and data scientists.
The review concludes by outlining future directions to guide development of next-generation, non-invasive diagnostic platforms. Key priorities include advancing nanomaterial chemistry and device engineering to boost detection limits, integrating multimodal sensing for more comprehensive biomarker panels, and coupling wearables with robust AI to translate continuous measurements into clinically useful insights.
The authors advocate for further research into standardization, large-scale clinical validation, and user-centered device design to support adoption in real-world healthcare. They present non-invasive biofluid monitoring as a promising route toward more accessible, continuous, and personalized diagnostics.
This work is a review article published in Nanotechnology on 23 September 2026 (volume 37, issue 38), DOI 10.1088/1361-6528/ae9d2c, PMID 42633764. Authors are affiliated with the School of Biomedical Engineering and the Department of Chemical and Biochemical Engineering at the University of Western Ontario. The review is published under a Creative Commons Attribution license. Indexed MeSH terms include biomarkers, biosensing techniques, body fluids, diabetes mellitus diagnosis, neoplasms diagnosis, neurodegenerative diseases diagnosis, nanostructures, and nanotechnology.