A Review on Hybrid Closed Loop Insulin Delivery System
DOI:
https://doi.org/10.48165/aabr.2025.2.2.04Keywords:
Type 1 diabetes mellitus, Automated insulin delivery, Hybrid Closed-Loop System, Continuous Glucose Monitoring, Artificial pancreasAbstract
Type 1 diabetes mellitus (T1DM) is a habitual autoimmune condition taking lifelong insulin remedy. Conventional approaches like multiple quotidian injections or continuous subcutaneous insulin infusion are limited by hypoglycaemia trouble, glycaemic variability, and patientburden. Automated insulin delivery (AID) systems, particularly crossbred unrestricted- circle (HCL) systems, integrate continuous glucose monitoring, insulin pumps, and control algorithms to optimize insulin delivery. HCL systems automate rudimentary insulin and correction boluses, taking manual mess boluses, and haves hown significant benefits, including increased time- in- range (TIR), lower HbA1c, reduced hypoglycaemia, and enhanced quality of life. These benefits are seen across different populations, including children, grown- ups, and pregnant women. Despite these advancements, limitations remain, analogous as mess gelcap dependence, delayed post- mess glucose control, sensor delicacy issues, cost, and specialized malfunctions. fully unrestricted- circle systems are being developed to count manual input and further mimic physiological insulin regulation. With ongoing advances,HCL systems represent a significant step toward a fully independent artificial pancreas, offering bettered glycaemic control, safety, and quality of life for individualities with T1DM. These systems have the eventuality to revise diabetes operation and meliorate patientissues.
References
Pilsniak, A., Otto-Buczkowska, E., et al. (2023). Type 1 diabetes — What’s new in prevention and therapeutic strategies? Pediatric Endocrinology, Diabetes and Metabolism, 29(3), 196–201. DOI: https://doi.org/10.5114/pedm.2023.132028
Lie, B. A., Todd, J. A., Pociot, F., et al. (1999). The predisposition to type 1 diabetes linked to the human leukocyte antigen complex includes a novel class II gene. American Journal of Human Genetics, 64, 793–800. DOI: https://doi.org/10.1086/302283
Klak, M., Gomolka, M., Kowalska, P., et al. (2020). Type 1 diabetes: Genes associated with disease development. Central European Journal of Immunology, 45, 439–453. DOI: https://doi.org/10.5114/ceji.2020.103386
Blanter, M., Sonk, H., Tuomilehto, S., & Flodström-Tullberg, M. (2019). Genetic and environmental interaction in type 1 diabetes: A relationship between genetic risk alleles and molecular traits of enterovirus infection. Current Diabetes Reports, 19, 82. DOI: https://doi.org/10.1007/s11892-019-1192-8
Dedrick, S., Sundaresh, B., Huang, Q., et al. (2020). The role of gut microbiota and environmental factors in type 1 diabetes pathogenesis. Frontiers in Endocrinology (Lausanne), 11, 78. DOI: https://doi.org/10.3389/fendo.2020.00078
TRIGR Study Group & Akerblom, H. K., Krischer, J., Virtanen, S. M., et al. (2011). The trial to reduce IDDM in the genetically at risk (TRIGR) study: Recruitment, intervention and follow-up. Diabetologia, 54, 627–633. DOI: https://doi.org/10.1007/s00125-010-1964-9
Witso, E., Cinek, O., Tapia, G., et al. (2015). Genetic determinants of enterovirus infections: Polymorphisms in type 1 diabetes and innate immune genes in the MIDIA study. Viral Immunology, 28, 556–563. DOI: https://doi.org/10.1089/vim.2015.0067
Wong, F. S., & Tree, T. I. (2019). Historical and new insights into pathogenesis of type 1 diabetes. Clinical and Experimental Immunology, 198, 292–293. DOI: https://doi.org/10.1111/cei.13396
Quinn, L. M., Wong, F. S., & Narendran, P. (2021). Environmental determinants of type 1 diabetes: From association to proving causality. Frontiers in Immunology, 12, 737964. DOI: https://doi.org/10.3389/fimmu.2021.737964
Diabetes Canada. (2018). 2018 clinical practice guidelines for the prevention and management of diabetes in Canada. Canadian Journal of Diabetes, 42(Suppl 1), S1–S325. DOI: https://doi.org/10.1016/S1499-2671(17)31026-2
Thomas, N. J., Jones, S. E., Weedon, M. N., Shields, B. M., Oram, R. A., & Hattersley, A. T. (2018). Frequency and phenotype of type 1 diabetes in the first six decades of life: A cross-sectional, genetically stratified analysis from UK Biobank. The Lancet Diabetes & Endocrinology, 6, 122–129. DOI: https://doi.org/10.1016/S2213-8587(17)30362-5
American Diabetes Association. (2019). Standards of medical care in diabetes—2019. Diabetes Care, 42, S1–S193. DOI: https://doi.org/10.2337/dc19-Sint01
Thunander, M., Petersson, C., Jonzon, K., et al. (2008). Incidence of type 1 and type 2 diabetes in adults and children in Kronoberg, Sweden. Diabetes Research and Clinical Practice, 82, 247–255. DOI: https://doi.org/10.1016/j.diabres.2008.07.022
Home, P. D., Bergenstal, R. M., Bolli, G. B., et al. (2015). New insulin glargine 300 units/mL versus glargine 100 units/mL in people with type 1 diabetes: A randomized, phase 3a open-label clinical trial (EDITION 4). Diabetes Care, 38, 2217–2225. DOI: https://doi.org/10.2337/dc15-0249
Bally, L., Thabit, H., Kojzar, H., et al. (2017). Day-and-night glycemic control with closed-loop insulin delivery versus conventional insulin pump therapy in free-living adults with well-controlled type 1 diabetes. The Lancet Diabetes & Endocrinology, 5, 261–270. DOI: https://doi.org/10.1016/S2213-8587(17)30001-3
Sharifi, A., De Bock, M. I., Jayawardena, D., et al. (2016). Glycemia, treatment satisfaction, cognition, and sleep quality using closed-loop system overnight versus sensor-augmented pump. Diabetes Technology & Therapeutics, 18, 772–783. DOI: https://doi.org/10.1089/dia.2016.0288
Tauschmann, M., Thabit, H., Bally, L., et al. (2018). Closed-loop insulin delivery in suboptimally controlled type 1 diabetes: A multicentre randomized trial. The Lancet, 392, 1321–1329. DOI: https://doi.org/10.1016/S0140-6736(18)31947-0
Renard, E. (2008). Insulin delivery route for the artificial pancreas. Journal of Diabetes Science and Technology, 2(4), 735–738. DOI: https://doi.org/10.1177/193229680800200429
Lal, R. A., Ekhlaspour, L., Hood, K., et al. (2019). Realizing a closed-loop (artificial pancreas) system for treatment of type 1 diabetes. Endocrine Reviews, 40(6), 1521–1546. DOI: https://doi.org/10.1210/er.2018-00174
Rodríguez-Sanmiéanto, D. L., León-Vargas, F., & García-Jaramillo, M. (2022). Artificial pancreas systems: Experience from concept to commercialization. Expert Review of Medical Devices, 19(11), 877–894. DOI: https://doi.org/10.1080/17434440.2022.2150546
Boughton, C. K., & Hovorka, R. (2019). Is an artificial pancreas for type 1 diabetes effective? Diabetic Medicine, 36(3), 279–286. DOI: https://doi.org/10.1111/dme.13816
Tauschmann, M., & Hovorka, R. (2018). Technology in the management of type 1 diabetes mellitus: Current status and future prospects. Nature Reviews Endocrinology, 14(8), 464–475. DOI: https://doi.org/10.1038/s41574-018-0044-y
Forlenza, G. P., Li, Z., Buckingham, B. A., et al. (2018). Predictive low-glucose suspend reduces hypoglycemia: PROLOG trial. Diabetes Care, 41(10), 2155–2161. DOI: https://doi.org/10.2337/dc18-0771
Bergenstal, R. M., Klonoff, D. C., Garg, S. K., et al. (2013). Threshold-based insulin-pump interruption for reduction of hypoglycemia. New England Journal of Medicine, 369(3), 224–232. DOI: https://doi.org/10.1056/NEJMoa1303576
Spaic, T., Driscoll, M., Raghinaru, D., et al. (2017). Predictive hyperglycemia and hypoglycemia minimization. Diabetes Care, 40(3), 359–366. DOI: https://doi.org/10.2337/dc16-1794
Nimri, R., Müller, I., Atlas, E., et al. (2014). MD-Logic overnight control for home use in patients with type 1 diabetes. Diabetes Care, 37(11), 3025–3032. DOI: https://doi.org/10.2337/dc14-0835
Phillip, M., Battelino, T., Atlas, E., et al. (2013). Nocturnal glucose control with an artificial pancreas at a diabetes camp. New England Journal of Medicine, 368(9),824–833. DOI: https://doi.org/10.1056/NEJMoa1206881
Ekhlaspour, L., Nally, L. M., El-Khatib, F. H., et al. (2019). Feasibility studies of an insulin-only bionic pancreas. Journal of Diabetes Science and Technology, 13(6), 1001–1007. DOI: https://doi.org/10.1177/1932296819872225
Breton, M. D., Chernavvsky, D. R., Forlenza, G. P., et al. (2017). Closed-loop control during intense prolonged outdoor exercise in adolescents with type 1 diabetes. Diabetes Care, 40(12), 1644–1650. DOI: https://doi.org/10.2337/dc17-0883
Newman, C., Hartnell, S., Wilinska, M., Alwan, H., & Hovorka, R. (2025). Real-world evidence of the Cambridge hybrid closed-loop app. Journal of Diabetes Science and Technology, 19(1), 165–168. DOI: https://doi.org/10.1177/19322968231187915
Ware, J., Allen, J. M., Boughton, C. K., Wilinska, M. E., et al. (2024). Eighteen-month hybrid closed-loop use in very young children with type 1 diabetes. Diabetes Care, 47(12), 2189–2195. DOI: https://doi.org/10.2337/dc24-1313
Giannoulaki, P., Kotzakioulafi, E., Nakas, A., et al. (2024). Advanced hybrid closed-loop system during pregnancy. Journal of Clinical Medicine, 13, 1441. DOI: https://doi.org/10.3390/jcm13051441
Fogh-Andersen, N., Altura, B. M., Altura, B. T., & Siggaard-Andersen, O. (1995). Composition of interstitial fluid. Clinical Chemistry, 41, 1522–1525. DOI: https://doi.org/10.1093/clinchem/41.10.1522
Schrangl, P., Reiterer, F., Heinemann, L., Freckmann, G., & Del Re, L. (2018). Limits to the evaluation of CGM accuracy. Biosensors, 8, 50. DOI: https://doi.org/10.3390/bios8020050
Coyle, S., Curto, V. F., Benito-Lopez, F., Florea, L., & Diamond, D. (2014). Wearable bio and chemical sensors. In Wearable Sensors (pp. 65–83). Academic Press. DOI: https://doi.org/10.1016/B978-0-12-418662-0.00002-7
Richter, E. A., & Hargreaves, M. (2013). Exercise, GLUT4, and skeletal muscle glucose uptake. Physiological Reviews, 93, 993–1017. DOI: https://doi.org/10.1152/physrev.00038.2012
Staal, O. M., Hansen, H. M. U., Christiansen, S. C., et al. (2018). Differences between flash glucose monitor and finger-prick measurements. Biosensors, 8, 93. DOI: https://doi.org/10.3390/bios8040093
Schmelzeisen-Redeker, G., Schoemaker, M., Kirchsteiger, H., Freckmann, G., Heinemann, L., & Del Re, L. (2015). Time delay of CGM sensors. Journal of Diabetes Science and Technology, 9, 1006–1015. DOI: https://doi.org/10.1177/1932296815590154
Davey, R. J., Low, C., Jones, T. W., & Fournier, P. A. (2010). Intrinsic lag of CGM systems. Journal of Diabetes Science and Technology, 4, 1393–1399. DOI: https://doi.org/10.1177/193229681000400614
Joseph, J. I. (2021). Review of implantable Senseonics CGM system. Journal of Diabetes Science and Technology, 15, 167–173. DOI: https://doi.org/10.1177/1932296820911919
Ekhlaspour, L., Forlenza, G. P., Chernavvsky, D., et al. (2019). Closed-loop control in adolescents and children during winter sports. Pediatric Diabetes, 20(6), 759–768. DOI: https://doi.org/10.1111/pedi.12867
Bekiari, E., Kitsios, K., Thabit, H., et al. (2018). Artificial pancreas: Systematic review and meta-analysis. BMJ, 361, k1310. DOI: https://doi.org/10.1136/bmj.k1310
Weisman, A., Bai, J.-W., Cardinez, M., Kramer, C. K., & Perkins, B. A. (2017). Effect of artificial pancreas systems on glycaemic control. The Lancet Diabetes & Endocrinology, 5(7), 501–512. DOI: https://doi.org/10.1016/S2213-8587(17)30167-5
