Modeling Pharmacokinetic Profiles of Insulin Regimens to Enhance Understanding of Subcutaneous Insulin Regimens

Abstract

Insulin pharmacokinetics following subcutaneous administration were modeled, simulated, and displayed through an interactive and user‐friendly interface to illustrate the time course of administered insulins frequently prescribed, providing a simple tool for clinicians through a straightforward visualization of insulin regimens. Pharmacokinetic data of insulin formulations with different onset and duration of action from several clinical studies, including insulin glargine, regular insulin, neutral protamine Hagedorn (NPH), insulin lispro, and premixed preparations of NPH with regular insulin (Mix 70/30), and insulin lispro protamine suspension with insulin lispro (Mix 50/50, Mix 75/25), were used to develop a predictive population pharmacokinetic model of insulins with consideration of factors such as insulin formulation, weight‐based dosing, body‐weight effect on volume of distribution, and administration time relative to meals, on the insulin time‐action profile. The model‐predicted insulin profile of each insulin was validated and confirmed to be comparable to observed data via an external validation method. Model‐based simulations of clinically relevant insulin‐dosing scenarios to cater to specific initial patient and prescribing conditions were then implemented with differential equations using the R statistical program (version 3.2.2). The R package Shiny was subsequently applied to build a web browser interface to execute and visualize the model simulation outputs. The application of insulin pharmacokinetic modeling enabled informative visualization of insulin time‐action profiles and provided an efficient and intuitive educational tool to quickly convey and interactively explore many insulin time‐action profiles to ease the understanding of insulin formulations in clinical practice.

Toward Better Understanding of Insulin Therapy by Translation of a PK‐PD Model to Visualize Insulin and Glucose Action Profiles

“…18 The discrimination between insulin derived from subcutaneous insulin administration and endogenously secreted insulin in healthy volunteers or patients with T2DM to determine subcutaneous insulin PK has been discussed previously. 10 Insulin PK Model Linked to IGI Model A PK model to describe insulin concentrations following subcutaneous administration of various insulin formulations was previously developed and validated. 10 The PK model structure ( Figure 1) was based on the assumption that absorption behavior differs between the different formulations of the same insulin type.…”

“…10 Insulin PK Model Linked to IGI Model A PK model to describe insulin concentrations following subcutaneous administration of various insulin formulations was previously developed and validated. 10 The PK model structure ( Figure 1) was based on the assumption that absorption behavior differs between the different formulations of the same insulin type. The insulin types were categorized as regular, lispro, or glargine insulin.…”

“…8,9 Because of the availability of a wide variety of insulin treatment options, a tool that enables the visualization of the time course of insulin concentrations and the associated glucose action profiles may be helpful to health care practitioners. Expanding on a previous analysis that established a pharmacokinetic (PK) model to describe typical profiles of insulin concentration over time following subcutaneous administration of various insulin formulations, 10 the goal of the current analysis was to link the PK model for subcutaneous insulins to an integrated glucose-insulin (IGI) systems pharmacology model. [11][12][13][14][15][16] Although several pharmacology models describing the feedback relationship between insulin and glucose have been developed over the years, 17 the selected glucose-insulin model for this work had a structure that was amenable to joining with the subcutaneous insulin PK model, enabled prospective simulations, and allowed for consideration of population variability.…”

Risk stratification according to insulin type

“…12 Prandial insulin has different pharmacokinetic properties compared to basal insulin. 13 The latter was designed with the aim to avoid a peak concentration, which could have less unfavourable influence on duration of QTc interval. In our opinion, considering all the aforementioned circumstances, it would be of great interest if subanalysis, regarding type of insulin used and cardiovascular outcomes, could be performed.…”

“…Prandial insulin has different pharmacokinetic properties compared to basal insulin . The latter was designed with the aim to avoid a peak concentration, which could have less unfavourable influence on duration of QTc interval.…”