In SilicoHead-to-Head Comparison of Insulin Glargine 300 U/mL and Insulin Degludec 100 U/mL in Type 1 Diabetes

Abstract

Background: Second-generation long-acting insulin glargine 300 U/mL (Gla-300) and degludec 100 U/mL (Deg-100) provide novel basal insulin therapies for the treatment of type 1 diabetes (T1D). Both offer a flatter pharmacokinetic (PK) profile than the previous generation of long-acting insulins, thus improving glycemic control while reducing hypoglycemic events. This work describes an in silico head-to-head comparison of the two basal insulins on 24-h glucose profiles and was used to guide the design of a clinical trial. Materials and Methods: The Universities of Virginia (UVA)/Padova T1D simulator describes the intra-/ interday variability of glucose-insulin dynamics and thus provides a robust bench-test for assessing glucose control for basal insulin therapies. A PK model describing subcutaneous absorption of Deg-100, in addition to the one already available for Gla-300, has been developed based on T1D clinical data and incorporated into the simulator. One hundred in silico T1D subjects received a basal insulin dose (Gla-300 or Deg-100) for 12 weeks (8 weeks uptitration, 4 weeks stable dosing) by morning or evening administration in a basal/bolus regimen. The virtual patients were uptitrated to their individual doses with two different titration rules. Results: The last 2-week simulated continuous glucose monitoring data were used to calculate various outcome metrics for both basal insulin treatments, with primary outcome being the percent time in glucose target (70-140 mg/dL). The simulations show no statistically significant difference for Gla-300 versus Deg-100 in the main endpoints. Conclusions: This work suggests comparable glucose control using either Gla-300 or Deg-100 and was used to guide the design of a clinical trial intended to compare second-generation long-acting insulin analogues.

Mathematical Models of Meal Amount and Timing Variability With Implementation in the Type-1 Diabetes Patient Decision Simulator

“…In the past 15 years of type 1 diabetes (T1D) research, in-silico clinical trials (ISCTs), performed using simulators relying on mathematical models of glucose-insulin system dynamics, have accelerated the development of new treatments 1 - 4 and drugs, 5 - 7 and have facilitated the design of clinical studies. 8 - 11 ISCTs allow investigators to carry out a vast number of experiments quickly, in order to evaluate, for example, new algorithms in high-risk scenarios, and so offer considerable economic and human resource savings.…”

Modeling Between-Subject Variability in Subcutaneous Absorption of a Fast-Acting Insulin Analogue by a Nonlinear Mixed Effects Approach

“…Actually, being able to account for subject variability and to detect useful covariates will pave the way for precision medicine in the field of diabetes, providing a customized approach to the disease for each patient. Furthermore, this model will be useful in the development of algorithms for subcutaneous insulin delivery implemented in insulin pump devices [ 20 , 21 ] and will be an important component of in silico platforms, like the UVa/Padova T1D Simulator [ 14 , 15 , 16 , 17 , 18 , 19 ]. The incorporation into the simulator of models that account for subject variability would allow for more realistic simulations, providing great benefits on the way to the development and approval of new insulin compounds.…”

“…In doing so, we tried also to personalize the model by the use of subject covariates. Such a model will become an important component of the University of Virginia (UVa)/Padova T1D Simulator [ 14 ], an in silico platform accepted by the Food and Drug Administration (FDA) as a substitute for preclinical trials for certain insulin treatments, including closed-loop algorithms for artificial pancreas [ 15 ], recently used as an ideal test bench for the development and evaluation of glucose sensors [ 16 ] and novel insulin analogues [ 17 , 18 ]. Furthermore, the presented model could be incorporated also in the recently proposed Padova T2D simulator [ 19 ], allowing optimizing insulin therapy in this population.…”

Modeling Intraperitoneal Insulin Absorption in Patients with Type 1 Diabetes

“…Another possible limitation is that, in this work, the whole-body insulin kinetics were described by a two-compartment model, even if a more physiological but complicated three-compartment model has also been proposed [ 20 ]. The choice was driven by the necessity to keep such a model as simple as possible, to favor both the a priori and the a posteriori identifiability, but also to make the model easy to incorporate in the UVa/Padova T1D Simulator, as done in [ 26 , 27 ]. This is particularly important to enable the in silico testing of a future closed-loop control algorithm for next generation SC-IP artificial pancreas.…”