In-silico Assessment of Using Faster Insulin Analogs in Automated Insulin Delivery (AID) Systems Without Meal Announcement

Automated Insulin delivery has become standard of care for managing glycemic control in Type 1 Diabetes (T1D), and has been shown to dramatically improve overall glycemic control. However, postprandial hyperglycemia remains a challenge, even with AID systems that require meal announcements. Rapid- and Ultra-rapid-acting insulin analogs that could improve or even prevent postprandial hyperglycemia are now available for both research and clinical care. However, it has been shown that adjusting AID system’s parameters is necessary for maximizing benefits when using accelerated insulins within these systems. In this work, the safety and performance effect of accelerating insulin within AIDANET, a state-of-the-art AID system is evaluated in-silico to address postprandial hyperglycemia generated by unannounced meals. Pharmacokinetic parameters are leveraged to include the use of a novel ultra-rapid insulin formulation within the UVA/Padova Type 1 Diabetes simulator. Additionally, two in-silico scenarios are used to assess the performance of Automated Insulin Delivery as Adaptive NETwork (AIDANET) with (i) faster insulin analogs and (ii) more concentrated formulations. Results show that AIDANET’s built-in adaptive capabilities allow it to adjust its aggressiveness to accommodate faster PK and more concentrated formulations, achieving clinically significant improvements in glycemic control outcomes and maximizing the benefits of alternative formulations.