Scientific and Technological Advancements in Diabetes Management

Published by Biotech Connection Singapore on

By Low Su Jun Blaise and Lim Chang Siang

Diabetes mellitus is a disease caused by the body’s inability to regulate blood sugar (glucose) levels, resulting in persistently high glucose levels in the body. This condition occurs when the body is unable to produce sufficient insulin – a hormone secreted by the pancreas to promote uptake of glucose from the blood into various cells to generate energy for bodily functions – or respond appropriately to insulin. There are 4 types of diabetes: Type 1 diabetes, Type 2 diabetes, monogenic diabetes and gestational diabetes. Type 1 diabetes results from the destruction of insulin-producing cells in the pancreas, which causes a lack of insulin secretion. Type 1 diabetes patients require administration of insulin injections to manage the disease [1]. Type 2 diabetes results from the inability of various cells in the body to respond appropriately to insulin, which eventually impairs insulin secretion. Patients with Type 2 diabetes typically require drug treatments that improve insulin sensitivity or increase insulin secretion [1]. Monogenic diabetes is a genetic disease caused by mutations in a single gene. These genes, such as HNF1A, ABCC8, INS, and GCK, are typically involved in gene regulation, pancreatic beta cell function, insulin production and glucose sensitivity. Monogenic diabetes patients may require either drug treatment or insulin therapy depending on the severity of the condition [2]. Gestational diabetes occurs in pregnant mothers, typically in the 2nd or 3rd trimester of their pregnancy, and usually resolves after childbirth [3]. Mothers who suffer from gestational diabetes during their pregnancies also have a higher risk of developing type 2 diabetes [4]. When these diabetic conditions are poorly managed, the high glucose levels in the blood may damage other organs and cause serious complications such as cardiovascular disease, kidney disease, fatty liver disease and eye damage [5].

Currently, more than 422 million people worldwide suffer from diabetes [6]. More than 60% of diabetics in the world live in Asia [7]. In Singapore, diabetes accounts for 10% of the disease burden, afflicting more than 440,000 people, thereby posing a substantial financial burden for the country [8]. It is estimated that 1 million Singaporeans will suffer from diabetes by 2050 [9], with medical costs expected to rise to a whopping S$2.5 billion (Figure 1) [10].

Figure 1. Diabetes accounts for a significant proportion of the disease burden in Singapore and can also cause complications such as stroke, heart attack and kidney failure. Image adapted from: Health Promotion Board, Singapore: Diabetes in Singapore, 2019,, Copyright 2013 by Health Promotion Board, Singapore

As the number of diabetes patients continues to rise in Singapore and globally, it is important to develop solutions and technologies to help diabetes patients manage their conditions more effectively. Researchers and start-up companies have devised innovative solutions in cell therapy, material science, digital health technology and artificial intelligence to tackle this global health problem.

Cell Therapy

In 1978, the first synthetic insulin was created by genetic engineering, enabling the mass production of insulin to treat diabetes patients [12]. While synthetic insulin therapy has been effective in helping diabetes patients to better control their blood sugar levels, the multiple insulin injections and daily insulin dosage calculations remain a challenge for patients [13]. In order to relieve diabetes patients from daily insulin injections, scientists and surgeons from the University of Alberta developed a transplantation technique known as The Edmonton Protocol in 2000 [14]. This technique enabled the transplantation of pancreatic islets containing insulin-producing cells from human cadaveric donors into type 1 diabetes patients. However, less than 44% of the transplanted patients remained insulin-independent after the islet transplantations [15]. Moreover, access to suitable cadaveric donor islets is limited by their scarce availability [16].

To overcome the limitations of islet transplantations, scientists are now exploring the possibilities of stem cell-based therapies for diabetes patients. Pluripotent stem cells are a unique type of cells with the ability to develop into almost any cell type in the body. In 2006, scientists devised a protocol that created pluripotent stem cells from adult skin cells, known as induced-pluripotent stem cells (iPSCs) [17]. The breakthrough creation of iPSCs offers the potential to grow cells or even organs from a patient’s own cells, eliminating the need for immunosuppression and the complications of graft rejections. More recently, scientists reported the successful production of insulin-producing cells from human pluripotent stem cells and demonstrated their capability of reversing diabetes in mice [18, 19]. These discoveries offer a huge potential in treating diabetes using stem cell-based therapies.

Since then, several companies have invested efforts into developing more efficient methods to generate insulin-producing cells. Currently, there are at least 16 companies worldwide that are working on stem cell-based diabetes therapies [20]. ViaCyte, a biotechnology company based in California, is one of the first to generate insulin-producing cells from human pluripotent stem cells. The insulin-producing cells are placed in an encapsulation device, EncaptraTM, which is implanted under the patient’s skin to deliver insulin into the bloodstream appropriately. Currently, ViaCyte’s devices PEC-DirectTM and PEC-EncapTM are undergoing Phase I/II clinical trials to evaluate their efficacy and safety for diabetes treatments [21].

Material Science

With advancements in islet transplantations and stem cell-based therapies for diabetes treatment, there is an imperative need to develop improved modes of delivering the transplanted cells into patients. Currently, human cadaveric islet cells are transplanted via the portal vein of the liver. However, this approach is not ideal as it exposes the transplanted islets to the patients’ immune system which could destroy the transplanted cells. Hence, companies are now developing devices to protect the transplanted cells from immune attack and aid the engraftment of these cells.

Presently, Sernova Corporation has developed the Cell Pouch SystemTM, an implantable medical device that ensures the long-term survival and function of the transplanted islets. This is achieved by keeping the cells in a chamber made of polypropylene mesh. Using a specific mesh configuration, blood vessels can grow within the chamber and facilitate the exchange of hormones between the transplanted cells and the host’s circulation system, while isolating the islets from the immune system [22]. In response to elevated glucose levels, the transplanted islets within the Cell Pouch™ produce insulin which diffuses into the bloodstream. [22]. The Cell Pouch™ is currently in Phase I/II clinical trials to assess its safety and efficacy in diabetes treatment [23].

Digital Health

The widespread usage of smartphones today has inspired much interest in the development of mobile application tools to support the delivery of healthcare services to patients. Innovators can leverage on the broad functionalities of the smartphone – photo-taking capabilities, high-speed internet connection, vibrant display and fast processing speed – to assist patients in communicating their healthcare needs anytime and anywhere.

Glycoleap, developed by Holmusk – a Singapore-based digital health company that delivers personalized lifestyle and dietary advice for diabetes patients – is an application which employs the use of smartphones in diabetes care. Using Glycoleap, users can track their meals, weight changes, blood sugar levels and physical activity levels. The app is supported by a team of dietician coaches who will review user inputs and provide personalised recommendations so that each user can make better dietary choices to control their blood sugar levels.

Artificial Intelligence

The advancements made in artificial intelligence (AI) could offer new opportunities in delivering personalised healthcare to patients and supporting diabetes management. AI technology could potentially be used to improve diabetes care by predicting the blood sugar level changes in patients after each meal [24, 25]. As glycaemic responses to food intake vary from individual to individual [26], AI predictions based on machine learning algorithms, could allow each diabetes patient to better understand how every meal affects their blood sugar levels. A group of computer scientists at Weizmann Institute of Science collected post meal glucose response data from 800 individuals and profiled them based on their dietary habits, anthropometrics, physical activity, and gut microbiota. They then tagged the glucose response patterns to the individuals’ physical and biochemical profiles, to develop a machine-learning model that can be used to predict personalized glycaemic  responses in the population [25].

AI can also help diabetes patients accurately calculate the insulin dosage required. A challenge faced by diabetes patients who require insulin injections is the difficulty in calculating the insulin dosage needed based on their blood sugar levels [13]. Furthermore, diabetes patients are also unable to address changes in their blood sugar levels during sleep., Currently, measurement of blood sugar levels, calculation of appropriate insulin dosages and injections of insulin are performed on separate devices. As these devices are not connected in a single closed-loop system, it is inconvenient for patients to use them to manage their glucose levels.

The inconvenience and lack of suitable devices inspired Dana Lewis, a type 1 diabetes patient, to develop a single closed-loop “artificial pancreas” with her husband, to manage her diabetes. Using a Raspberry Pi single-board computer, they programmed the connection of a continuous glucose monitoring device and a hacked Medtronic insulin pump [27]. In 2015, they initiated the Open Artificial Pancreas System (#OpenAPS) project to share their knowledge and advance the development of creating an affordable artificial pancreas device.

Soon after, Medtronic announced their first FDA-approved MiniMed 670G System in 2016. MiniMed 670G is the first FDA-approved hybrid closed-loop insulin pump system that can automatically monitor blood sugar levels and release insulin doses accordingly in diabetes patients [28]. This device has also recently demonstrated its cost-effectiveness amongst patients with poorly controlled type 1 diabetes [29].


Diabetes is a debilitating disease that compromises the quality of life of patients. It is of utmost importance to develop improved treatments and healthcare solutions for the millions of people living with diabetes worldwide. Today, the progress made in scientific innovations and technological inventions has offered potentially promising diabetes treatments and improved healthcare options. These range from stem cell-based therapies that help to restore insulin-producing capacity in patients, devices that protect transplanted cells from immune attack, mobile apps that provide personalised healthcare services as well as  AI-driven devices that function as an artificial pancreas system. These promising innovations provide much hope in improving diabetes management in the near future.


  1. Zaccardi, F., Webb, D. R., Yates, T., and Davies, M. J. (2015). Pathophysiology of type 1 and type 2 diabetes mellitus: a 90-year perspective. Postgraduate Medical Journal 92, 63–69.
  2. Stoffel, M. (2016). Maturity-Onset Diabetes of the Young: Molecular Genetics, Clinical Manifestations, and Therapy. Principles of Diabetes Mellitus, 1–14.
  3. Mcintyre, H. D. Gestational diabetes mellitus, obesity, and pregnancy outcomes. Textbook of Diabetes and Pregnancy, 246–252.
  4. Cai, S., Tan, S., Gluckman, P. D., Godfrey, K. M., Saw, S.-M., Teoh, O. H., Chong, Y.-S., Meaney, M. J., Kramer, M. S., Gooley, J. J., et al. (2016). Sleep Quality and Nocturnal Sleep Duration in Pregnancy and Risk of Gestational Diabetes Mellitus. Sleep 40.
  5. Diabetes Mellitus HealthHub. Available at: [Accessed October 12, 2019].
  6. Roglic, G. (2016). Global report on diabetes (Geneva, Switzerland: World Health Organization).
  7. Guariguata, L., Whiting, D., Hambleton, I., Beagley, J., Linnenkamp, U., and Shaw, J. (2014). Global estimates of diabetes prevalence for 2013 and projections for 2035. Diabetes Research and Clinical Practice 103, 137–149.
  8. IDF Diabetes Atlas, 7th Edition, 2015, International Diabetes Federation
  9. Phan, T. P., Alkema, L., Tai, E. S., Tan, K. H. X., Yang, Q., Lim, W.-Y., Teo, Y. Y., Cheng, C.-Y., Wang, X., Wong, T. Y., et al. (2014). Forecasting the burden of type 2 diabetes in Singapore using a demographic epidemiological model of Singapore. BMJ Open Diabetes Research & Care 2.
  10. Khalik, S. (2016). Study: Cost of diabetes to Singapore to soar beyond $2.5b. The Straits Times. Available at: [Accessed August 25, 2019].
  11. Khalik, S. (2016). Parliament: Health Minister Gan Kim Yong declares ‘war on diabetes’; new task force set up. The Straits Times. Available at: [Accessed August 25, 2019].
  12. History of Insulin. History of Insulin – Discovery to Modern Day Timeline. Available at: [Accessed August 25, 2019].
  13. Parikh, R., and Padmanabhan, K. (2014). Insulin Therapy in Type 2 Diabetes Mellitus. Diabetology: Type 2 Diabetes Mellitus, 105–105.
  14. Shapiro, A. J., Lakey, J. R., Ryan, E. A., Korbutt, G. S., Toth, E., Warnock, G. L., Kneteman, N. M., and Rajotte, R. V. (2000). Islet Transplantation in Seven Patients with Type 1 Diabetes Mellitus Using a Glucocorticoid-Free Immunosuppressive Regimen. New England Journal of Medicine 343, 230–238.
  15. Shapiro, A. M. James; Ricordi, Camillo; Hering, Bernhard J.; Auchincloss, Hugh; Lindblad, Robert; Robertson, R. Paul; Secchi, Antonio; Brendel, Mathias D.; Berney, Thierry (2006). International trial of the Edmonton protocol for islet transplantation. The New England Journal of Medicine.
  16. Wang, Y., Danielson, K. K., Ropski, A., Harvat, T., Barbaro, B., Paushter, D., Qi, M., and Oberholzer, J. (2013). Systematic Analysis of Donor and Isolation Factors Impact on Human Islet Yield and Size Distribution. Cell Transplantation 22, 2323–2333.
  17. Takahashi, K., and Yamanaka, S. (2006). Induction of Pluripotent Stem Cells from Mouse Embryonic and Adult Fibroblast Cultures by Defined Factors. Cell 126, 663–676.
  18. Rezania, A., Bruin, J. E., Arora, P., Rubin, A., Batushansky, I., Asadi, A., Odwyer, S., Quiskamp, N., Mojibian, M., Albrecht, T., et al. (2014). Reversal of diabetes with insulin-producing cells derived in vitro from human pluripotent stem cells. Nature Biotechnology 32, 1121–1133.
  19. Pagliuca, F. W., Millman, J. R., Gürtler, M., Segel, M., Van Dervort, A., Ryu, J. H., Peterson, Q. P., Greiner, D., and Melton, D. A. (2014). Generation of Functional Human Pancreatic β Cells In Vitro. Cell 159, 428–439.
  20. BioInformant (2019). Top Companies Developing Cell Therapy Treatments For Diabetes. BioInformant. Available at: [Accessed August 25, 2019].
  21. Center for Beta Cell Therapy in Diabetes and ViaCyte Announce Start of
    European Clinical Trial of Human Stem Cell-derived Implants in Type 1
    Diabetes Patients (2019). Viacyte, Inc. Available at:
    stem-cell-derived-implants-in-type-1-diabetes-patients [Accessed October 12, 2019].
  22. Hasilo, C., Leushner, J., Haworth, N. D., Shohet, S., Toleikis, M. P., Siroen,
    M. M. D. (2015) United States Patent No. US9011899. Retrieved from:
  23. BioSpace (2019). Sernova's Phase I/II US Clinical Trial for Type-1 Diabetes Advances Following Positive Preliminary Safety and Efficacy Data. BioSpace. Available at: [Accessed October 12, 2019].
  24. Albers, D. J., Levine, M., Gluckman, B., Ginsberg, H., Hripcsak, G., and
    Mamykina, L. (2017). Personalized glucose forecasting for type 2 diabetes
    using data assimilation. PLOS Computational Biology 13.
  25. Zeevi, D., Korem, T., Zmora, N., Israeli, D., Rothschild, D., Weinberger, A.,
    Ben-Yacov, O., Lador, D., Avnit-Sagi, T., Lotan-Pompan, M., et al. (2015).
    Personalized Nutrition by Prediction of Glycemic Responses. Cell 163,
  26. Vrolix, R., and Mensink, R. P. (2010). Variability of the glycemic response to
    single food products in healthy subjects. Contemporary Clinical Trials 31,
  27. Ragan, S. M. (2019). Medicine Ignored This Insulin Problem. Hackers Solved It. Medium. Available at: hack-artificial-pancreas-af6ef23a997f [Accessed August 25, 2019].
  28. Center for Devices and Radiological Health The Artificial Pancreas Device
    System. U.S. Food and Drug Administration. Available at:
  29. Jendle, J., Pöhlmann, J., Portu, S. D., Smith-Palmer, J., and Roze, S. (2019).
    Cost-Effectiveness Analysis of the MiniMed 670G Hybrid Closed-Loop
    System Versus Continuous Subcutaneous Insulin Infusion for Treatment of
    Type 1 Diabetes. Diabetes Technology & Therapeutics 21, 110–118.


Blaise Low Su Jun is a 4th year PhD student at Yong Loo Lin School of Medicine (NUS) and Institute of Molecular and Cell Biology (A*STAR).  Her project focuses on using pluripotent stem cell-derived pancreatic cells to study the genetic and molecular mechanisms that underlie monogenic diabetes. She is passionate about effective scientific communication and writes in science blogs in her free time. Follow her on Instagram @scientist.blaise where she muses on her life in the lab.



Lim Chang Siang is a research software engineer at Saw Swee Hock School of Public Health (NUS). His project focuses on using software technology to improve the delivery of healthcare services. His research interests include remote care delivery, disease prevention and health informatics.




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