Clinical Evidence for Use of a Noninvasive Biosensor for Tear Glucose as an Alternative to Painful Finger-Prick for Diabetes Management Utilizing a Biopolymer Coating
Open accessAbstract
Diabetes is a metabolic condition that is exponentially increasing worldwide. Current monitoring methods for diabetes are invasive, painful, and expensive. Herein, we present the first multipatient clinical trial that demonstrates clearly that tear fluid may be a valuable marker for systemic glucose measurements. The NovioSense Glucose Sensor, worn under the lower eye lid (inferior conjunctival fornix), is reported to continuously measure glucose levels in the basal tear fluid with good correlation to blood glucose values, showing clear clinical feasibility in both animals and humans. Furthermore, the polysaccharide coated device previously reported by our laboratory when worn, does not induce pain or irritation. In a phase II clinical trial, six patients with type 1 Diabetes Mellitus were enrolled and the capability of the device to measure glucose in the tear fluid was evaluated. The NovioSense Glucose Sensor gives a stable signal and the results correlate well to blood glucose values obtained from finger-prick measurements determined by consensus error grid analysis.
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Scientific data evidenced how commercially available test strips exhibit the required performance to evaluate glucose concentration in low-volume tears.
“Scientific data evidenced how commercially available test strips exhibit the required performance to evaluate glucose concentration in low-volume tears 166-168.”
From Glucose biosensors in clinical practice: principles, limits and perspectives of currently used devices (2022) · cites this paper as [166]
The Results and Discussion describe glucose test strips used to analyze blood samples, while a separate NovioSense sensor measured tear glucose. The Introduction notes the tear film’s small volume, but our copy does not assess whether commercially available strips can measure glucose in low-volume tears (searched for test strips and tear volume). (LLM, conf=0.76)
Experimental — accuracy not yet measuredA recent clinical trial demonstrated great correlation between tear and blood glucose concentrations in animals and humans (including patients with type 1 diabetes).
“A recent clinical trial demonstrated great correlation between tear and blood glucose concentrations in animals and humans (including patients with type 1 diabetes)119.”
From Wearable biosensors for healthcare monitoring (2019) · cites this paper as [119]
Such sensor placement at the base of the eye provides continuously accessible tear glucose measurements when coupled with wireless data transmission, without causing discomfort.
“Such sensor placement at the base of the eye (behind the eyelid) provides continuously accessible tear glucose measurements when coupled with wireless data transmission, without causing discomfort.”
From Wearable biosensors for healthcare monitoring (2019) · cites this paper as [119]
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Cites
IDF Diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045
Cho, N. H., Shaw, J. E., Karuranga, S., Huang, Y., da Rocha Fernandes, J. D., Ohlrogge, A. W., & Malanda, B. (2018) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2018.02.023 · Cited by 7,283 · see citing works
IDF Diabetes Atlas: Global estimates for the prevalence of diabetes for 2015 and 2040
Ogurtsova, K., Fernandes, J. D. D. R., Huang, Y., Linnenkamp, U., Guariguata, L., Cho, N. H., Cavan, D. A., Shaw, J. E., & Makaroff, L. (2017) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2017.03.024 · Cited by 6,977 · see citing works
Diagnosis and classification of diabetes mellitus
American Diabetes Association (2009) · Diabetes Care · doi:10.2337/dc09-s062 · Cited by 1,817 · see citing works
Wearable smart sensor systems integrated on soft contact lenses for wireless ocular diagnostics
Kim, J., Kim, M., Lee, M.-S., Kim, K., Ji, S., Kim, Y.-T., Park, J., Na, K., Bae, K.-H., Kyun Kim, H., et al. (2017) · Nature Communications · doi:10.1038/ncomms14997 · Cited by 951 · see citing works
Glucose Sensing for Diabetes Monitoring: Recent Developments
Bruen, D., Delaney, C., Florea, L., & Diamond, D. (2017) · Sensors · doi:10.3390/s17081866 · Cited by 778 · see citing works
Self-Assembly of Janus Dendrimers into Uniform Dendrimersomes and Other Complex Architectures
Percec, V., Wilson, D. A., Leowanawat, P., Wilson, C. J., Hughes, A. D., Kaucher, M. S., Hammer, D. A., Levine, D. H., Kim, A. J., Bates, F. S., et al. (2010) · Science · doi:10.1126/science.1185547 · Cited by 734 · see citing works
Self-citationThe Global Epidemiology of Diabetes and Kidney Disease
Koye, D. N., Magliano, D. J., Nelson, R. G., & Pavkov, M. E. (2018) · Advances in Chronic Kidney Disease · doi:10.1053/j.ackd.2017.10.011 · Cited by 686 · see citing works
The Performance and Usability of a Factory-Calibrated Flash Glucose Monitoring System
Bailey, T., Bode, B. W., Christiansen, M. P., Klaff, L. J., & Alva, S. (2015) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2014.0378 · Cited by 685 · see citing works
Soft, smart contact lenses with integrations of wireless circuits, glucose sensors, and displays
Park, J., Kim, J., Kim, S.-Y., Cheong, W. H., Jang, J., Park, Y.-G., Na, K., Kim, Y.-T., Heo, J. H., Lee, C. Y., et al. (2018) · Science Advances · doi:10.1126/sciadv.aap9841 · Cited by 671 · see citing works
Responsive biomimetic networks from polyisocyanopeptide hydrogels
Kouwer, P. H. J., Koepf, M., le Sage, V. A. A., Jaspers, M., van Buul, A. M., Eksteen-Akeroyd, Z. H., Woltinge, T., Schwartz, E., Kitto, H. J., Hoogenboom, R., et al. (2013) · Nature · doi:10.1038/nature11839 · Cited by 557 · see citing works
A contact lens with embedded sensor for monitoring tear glucose level
Yao, H., Shum, A. J., Cowan, M., Lähdesmäki, I., & Parviz, B. A. (2011) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2010.12.042 · Cited by 513 · see citing works
Xuan, X., Yoon, H. S., & Park, J. Y. (2018) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2018.02.054 · Cited by 413 · see citing works
IDF Diabetes Atlas estimates of 2014 global health expenditures on diabetes
Fernandes, J. D. R., Ogurtsova, K., Linnenkamp, U., Guariguata, L., Seuring, T., Zhang, P., Cavan, D. A., & Makaroff, L. (2016) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2016.04.016 · Cited by 377 · see citing works
Chu, M. X., Miyajima, K., Takahashi, D., Arakawa, T., Sano, K., Sawada, S.-I., Kudo, H., Iwasaki, Y., Akiyoshi, K., Mochizuki, M., et al. (2011) · Talanta · doi:10.1016/j.talanta.2010.10.055 · Cited by 279 · see citing works
A history of continuous glucose monitors (CGMs) in self-monitoring of diabetes mellitus
Olczuk, D., & Priefer, R. (2017) · Diabetes & Metabolic Syndrome Clinical Research & Reviews · doi:10.1016/j.dsx.2017.09.005 · Cited by 194 · see citing works
Tear glucose analysis for the noninvasive detection and monitoring of diabetes mellitus
Baca, J. T., Finegold, D. N., & Asher, S. A. (2007) · The Ocular Surface · doi:10.1016/s1542-0124(12)70094-0 · Cited by 187 · cited 1× · see citing works
“11,12 A number of proof-of concept enzymatic prototype devices have attempted to demonstrate the potential to be used as tear glucose sensors but with little success.”
Yao, H., Liao, Y., Lingley, A. R., Afanasiev, A., Lähdesmäki, I., Otis, B. P., & Parviz, B. A. (2012) · Journal of Micromechanics and Microengineering · doi:10.1088/0960-1317/22/7/075007 · Cited by 182 · see citing works
Tear Glucose Dynamics in Diabetes Mellitus
Lane, J., Krumholz, D. M., Sack, R. A., & Morris, C. (2006) · Current Eye Research · doi:10.1080/02713680600976552 · Cited by 160 · see citing works
初, 明. (2011) · Medical Entomology and Zoology · Cited by 157 · see citing works
The Chemistry of Commercial Continuous Glucose Monitors
McGarraugh, G. V. (2009) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2008.0133 · Cited by 144 · see citing works
Therapeutic nanoworms: towards novel synthetic dendritic cells for immunotherapy
Mandal, S., Eksteen-Akeroyd, Z. H., Jacobs, M. J., et al. (2013) · Chemical Science · doi:10.1039/c3sc51399h · Cited by 103 · see citing works
Polymer Brush-Functionalized Chitosan Hydrogels as Antifouling Implant Coatings
Buzzacchera, I., Vorobii, M., Kostina, N. Y., Pereira, A. D. L. S., Riedel, T., Brüns, M., Ogieglo, W., Möller, M., Wilson, C. J., & Rodriguez‐Emmenegger, C. (2017) · Biomacromolecules · doi:10.1021/acs.biomac.7b00516 · Cited by 85 · see citing works
Self-citationXiao, Q., Ludwig, A., Romanò, C., Buzzacchera, I., Sherman, S. E., Vetro, M., Vértesy, S., Kaltner, H., Reed, E. H., Möller, M., et al. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1720055115 · Cited by 84 · see citing works
Self-citationZimoch, J., Padial, J. S., Klar, A. S., Vallmajó-Martín, Q., Meuli, M., Biedermann, T., Wilson, C., Rowan, A. E., & Ernst Reichmann, A. (2018) · Acta Biomaterialia · doi:10.1016/j.actbio.2018.01.042 · Cited by 77 · see citing works
Self-citationCelikkin, N., Padial, J. S., Costantini, M., Hendrikse, H. C., Cohn, R., Wilson, C. J., Rowan, A. E., & Święszkowski, W. (2018) · Polymers · doi:10.3390/polym10050555 · Cited by 52 · see citing works
Self-citationSensor Devices Inspired by the Five Senses: A Review
Svechtarova, M. I., Buzzacchera, I., Toebes, B. J., Lauko, J., Anton, N., & Wilson, C. (2016) · Electroanalysis · doi:10.1002/elan.201600047 · Cited by 46 · see citing works
Self-citationTear production and evaporation in the normal eye
Tomlinson, A., Trees, G. R., & Occhipinti, J. R. (1991) · Ophthalmic and Physiological Optics · doi:10.1111/j.1475-1313.1991.tb00193.x · Cited by 35 · see citing works
Tear production and evaporation in the normal eye.
Tomlinson, A., Trees, G. R., & Occhipinti, J. R. (1991) · PubMed · Cited by 34 · see citing works
Hennig, A., Lauko, J., Grabmaier, A., & Wilson, C. (2014) · Procedia Engineering · doi:10.1016/j.proeng.2014.11.267 · Cited by 23 · see citing works
Self-citationLee, W. C., Smith, E., Chubb, B., & Wolden, M. L. (2013) · Journal of Medical Economics · doi:10.3111/13696998.2013.873722 · Cited by 21 · see citing works
Imaging findings of diabetes on post-mortem CT
Ruder, T. D., Schweitzer, W., Ampanozi, G., et al. (2018) · Journal of Forensic Radiology and Imaging · doi:10.1016/j.jofri.2018.05.002 · Cited by 5 · see citing works
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Kim, J., Campbell, A. S., de Ávila, B. E.-F., & Wang, J. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0045-y · Cited by 3,373 · see citing works
Non-Invasive Blood Glucose Monitoring Technology: A Review
Tang, L., Chang, S. J., Chen, C.-J., & Liu, J.-T. (2020) · Sensors · doi:10.3390/s20236925 · Cited by 481 · see citing works
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Saha, T., Del Caño, R., Mahato, K., De la Paz, E., Chen, C., Ding, S., Yin, L., & Wang, J. (2023) · Chemical Reviews · doi:10.1021/acs.chemrev.3c00078 · Cited by 442 · see citing works
Eyeglasses-based tear biosensing system: Non-invasive detection of alcohol, vitamins and glucose
Sempionatto, J. R., Brazaca, L. C., García-Carmona, L., Bolat, G., Campbell, A. S., Martin, A., Tang, G., Shah, R., Mishra, R. K., Kim, J., et al. (2019) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2019.04.058 · Cited by 315 · see citing works
Pullano, S. A., Greco, M., Bianco, M. G., Foti, D., Brunetti, A., & Fiorillo, A. S. (2022) · Theranostics · doi:10.7150/thno.64035 · Cited by 210 · see citing works
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- Authors
- Kownacka, A. E., Vegelyte, D., Joosse, M., Anton, N., Toebes, B. J., Lauko, J., Buzzacchera, I., Lipinska, K., Wilson, D. A., Geelhoed-Duijvestijn, N., & Wilson, C. J.
- Affiliations
- NovioSense B.V. , NovioTech Campus, Transistorweg 5 , ,
- Medisch Centrum Haaglanden (NL)
- Grigore T. Popa University of Medicine and Pharmacy (RO)
- Radboud University Nijmegen (NL)
- Corresponding author
- Geelhoed-Duijvestijn, Nel
- Wilson, Christopher J.
- Venue
- Biomacromolecules
- Publisher
- American Chemical Society (ACS)
- Published
- 2018-10-12
- Volume
- 19
- Issue
- 11
- Pages
- 4504-4511
- ISSN
- 1525-7797 (ISSN-L)
- 1526-4602
- PMC
- PMC6234487
- OpenAlex
- W2898045499
- Cited by
- 164
- References
- 31
- Citations by year
- 2026: 9 · 2025: 27 · 2024: 22 · 2023: 29 · 2022: 27 · 2021: 24 · 2020: 14 · 2019: 12
- FWCI
- 9.94
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Biomacromolecules (publishedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Radboud Repository (Radboud University) (submittedVersion)
- Radboud Repository (Radboud University) (submittedVersion, other-oa)
- Funders
- European Commission (HORIZON2020, 642687)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electrochemical sensors and biosensors
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ocular Surface and Contact Lens
- Keywords
- tear glucose, non-invasive glucose monitoring, type 1 diabetes, biosensors, conjunctival fornix, polysaccharide coatings, clinical trials
- MeSH terms
- Animals, Biopolymers, Diabetes Mellitus, Glucose, Humans, Monitoring, Physiologic, Rabbits, Sheep, Tears, Biosensing Techniques, Disease Management
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