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MedTech Outlook | Wednesday, April 26, 2023
Integrating insulin delivery systems with automation shows improvements in HbA1c levels, while devices face shortcomings with the location of glucose sensing and insulin delivery.
The prospect of a biological cure for type 1 diabetes is unlikely shortly, but automated insulin delivery (AID) systems have evolved as a technological solution for diabetes management. AID systems combine continuous glucose monitoring systems (CGM) data, a control algorithm, and an insulin pump to automate subcutaneous insulin delivery. Although many different names refer to AID systems, all describe the same basic concept.
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Commercial AID systems require user input to determine optimal prandial insulin dosing and to correct insulin dosing automatically and manually. They are, however, a significant step toward optimizing diabetic glucose management. It is important to note that AID systems do not cure diabetes. Rather, they provide automatic dose correction and adjust basal insulin delivery as part of diabetes care, which can ease some of the daily burdens of diabetes care.
People with diabetes and providers need to be aware of the limitations and benefits of such systems.
Integrating artificial intelligence: There has been exponential growth in AID systems over the past decade due to many advances. As evidenced by improvements in HbA1c, both in adults and children, AID technology demonstrates an improvement in glycaemic control. AID systems have been shown to improve quality of life by improving sleep, reducing anxiety, and reducing some of the burdens of diabetes management, according to early studies. Nevertheless, future research is necessary to determine if such improvements occur in the general population rather than only in selected study populations. Diabetes patients may be able to adjust the response of AID systems using artificial intelligence in the future. It is also possible to improve the performance of such procedures by adding hormones and medications like glucagon, glucagon-like peptide receptor agonists, amylin analogs, and sodium-glucose cotransporter two inhibitors; however, it is essential to carefully consider the benefits of using noninsulin adjuncts.
Challenges with AID adoption: Despite its apparent benefits, AID has limitations. The most critical physiological limitation is the location of glucose sensing and insulin delivery. CGM sensors are placed in the interstitial fluid (ISF), so the sensor glucose value is a lag time compared to blood glucose measurements. As glucose levels fluctuate rapidly, this issue is exacerbated. Even with the current rapid-acting insulin analogs, delivery via insulin pumps into the subcutaneous space can impede the pharmacodynamic response. As a result of these limitations, AID systems adopted a hybrid approach that requires users to manually bolus for carbohydrate intake. The eventual creation of a full AID system might be possible with the development of better insulin products and algorithms that include meal detection and glucose monitoring every minute. The level of physical activity a patient measures with wearables or smartphones can be used to adjust insulin dosage based on their current needs; it is still being determined how well AID systems manage insulin requirements during physical activity. A smartphone application that determines carbohydrate content based on pictures of a meal is an example of how artificial intelligence could eventually assist with such individualization and customization.
This type of advanced diabetes therapy should not only be understood by individuals with diabetes but also be able to revert to standard diabetes therapy, that is, non-automated subcutaneous insulin delivery by pump or injection if the AID system fails. In addition to troubleshooting independently, they should also have access to their healthcare provider (HCP) for assistance. It is also important that their HCP has easy access to their AID system data remotely. Giving a person with diabetes an AID system without adequate training presents safety risks without improving outcomes. AID systems are not currently available to all people with diabetes due to their high cost. Future AID systems will be more affordable, including insulin and digital access to data.
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