In Switzerland, the first rapid-acting and long-acting insulin analogues came onto the market about twenty years ago. These have been successively developed further, so that today a wide range of preparations is available for personalized diabetes treatment. Diabetes technology innovations have also significantly improved insulin therapy and the quality of life of those affected. These include continuous glucose monitoring and the “Hybrid”/”closed-loop” systems with adaptive insulin delivery.
For people with diabetes, these achievements lead to greater autonomy and empowerment at all stages of life [1]. Despite all these developments, however, lifestyle measures such as regular exercise sessions and dietary changes remain a central component of diabetes therapy.
Ultrafast and ultra-long acting insulin analogues
Recent developments include ultrafast analogs that further reduce postprandial glucose spikes and accumulation-induced hypoglycemia by providing an even faster onset and offset of insulin action [1]. The latest ultra-long-acting basal insulins minimize hypoglycemia through longer duration of action and more stable action profiles. Nevertheless, to date it is not possible to fully simulate the physiological 3:1 ratio of insulin exposure of liver and peripheral tissues with subcutaneous insulin therapy. Alternatives such as oral or liver-specific insulins are currently being researched. Inhaled insulin is not approved in Switzerland.
Continuous glucose monitoring
In addition to conventional continuous glucose monitoring (CGM) systems that continuously send readings to a receiver device, there are also so-called “flash glucose monitoring” systems that require glucose values to be actively retrieved using a reader [1]. Glucose is measured in the subcutaneous adipose tissue using an enzyme-coated sensor. CGM/”Flash Glucose Monitoring” systems provide a dynamic glucose curve compared to conventional capillary blood glucose measurements. Studies have shown an improvement in glycemic control with a reduction in hypoglycemia, and clinical practice has shown that these systems have a positive impact on user motivation and self-management. Affected individuals can anticipate glucose deviations and take appropriate action. It is not only the diabetics themselves who benefit from the fact that therapy can be adjusted more precisely and situationally, but the entire treatment team.
“Closed-loop” systems and AI-assisted “decision support”.
The coupling of insulin pumps with CGM systems led to the development of so-called “closed-loop” systems [1]. These closed-loop systems enable automated and on-demand insulin delivery with the goal of improving glucose control. This reduces the amount of therapy required for those affected and thus leads to relief. While “Fully Closed-Loop” systems operate autonomously, “Hybrid Closed-Loop” systems require input from the user such as meal announcements. For some years now, various “hybrid closed-loop” systems have been commercially available in Switzerland and have been used with great success primarily in type 1 diabetes. In contrast, no fully closed-loop system is currently approved in Germany. However, the fact that these systems significantly improve glucose control in the inpatient setting, in (par)enteral nutrition, or in dialysis patients is considered empirically confirmed [2–4].
What future developments are emerging?
Regarding non-insulin antidiabetic agents, the combination of the gut hormones GLP-1 and GIP is being studied with potent effects on glucose control and weight loss [5]. In the field of insulin therapy, research is being conducted, among other things, on the development of even longer-acting insulin analogues, for example in the form of basic insulin applied once a week [6]. Closed-loop” systems are constantly being improved by equipping them with more precise CGM sensors, even faster-acting insulin analogues, the addition of hormones such as glucagon or amylin analogues (“multiple-hormone artificial pancreas”) or the integration of movement and nutrition data. In addition, they are trying to make the systems more and more user-friendly. Integrative data analysis can already benefit from artificial intelligence (AI) methods. The application of new technologies leads to the generation of increasingly large amounts of data. Complex patterns can be identified through the use of AI-powered methods. This is a basis for so-called “decision support” systems to support affected individuals and their treatment teams. Increasing digitization enables the development of telemedical applications that provide therapy recommendations to patients based on the collected data. Even if there are still certain regulatory and data protection hurdles with regard to AI and digitization, the future potential of these innovative technologies is enormous. Not only are further efforts underway in the field of diabetes technology and pharmacotherapy, but also research in islet cell transplantation continues, for example with encapsulated islet cells [1].
Literature:
- Lehmann V, et al.: Diabetes therapy in transition – evolution and revolution with focus on the affected. Swiss Med Forum 2022; 22(0506): 85-87.
- Bally L, et al: Closed-loop insulin delivery for glycemic control in noncritical care. N Engl J Med 2018; 379(6): 547-56.
- Boughton CK, et al: Fully closed-loop insulin delivery in inpatients receiving nutritional support: a two-centre, open-label, randomised controlled trial. Lancet Diabetes Endocrinol 2019;7(5): 368-377.
- Boughton CK, et al: Fully automated closed-loop glucose control compared with standard insulin therapy in adults with type 2 diabetes requiring dialysis: an open-label, randomized crossover trial. Nat Med 2021; 27(8): 1471-1476.
- Frías JP, et al: Tirzepatide versus semaglutide once weekly in patients with type 2 diabetes. N Engl J Med 2021; 385(6): 503-515.
- Rosenstock J, et al: Once-weekly insulin for type 2 diabetes without previous insulin treatment. N Engl J Med 2020; 383(22): 2107-2116.
HAUSARZT PRAXIS 2022; 17(8): 34
CARDIOVASC 2022; 21(3): 32
