Background and Aims

Insulin aspart and lispro are common analogs with a guide peak time of 1 to 3 hours. In practice, insulin action speed varies depending on formulation and patient metabolism.

In an artificial pancreas, the predicted glycaemia accuracy relies on the kinetic model of insulin subcutaneous diffusion. We aim to estimate the peak time for both analogs from insulinemia measurements I_m(t).

Methods

First, the Insulin On Board (IOB) is modelled with Hovorka’s set of two sub-compartments and output plasma insulin I(t). We estimate the model’s parameters t_max, V_i and k_e by minimising the quadratic error between I_m(t) and I(t). The reference IOB_ref is equal to the sum of sub-compartments.

Then, the IOB is modelled with an exponential function IOB_exp, decreasing with time and depending on τ. The optimal τ minimises the quadratic error between IOB_exp(t,τ) and IOB_ref for all patients at once.

Results

During 24h at hospital, 41 patients with type 1 diabetes, including 20 using aspart and 21 using lispro, were monitored during clinical trials Diabeloop-SP3 and SP6.1. Measurements include CGM, basal, bolus and insulinemia I_m(t).

The median individual t_max was estimated at 57 min [Q1: 49; Q3: 64] for aspart and 53 min [43; 57] for lispro. The population-optimal τ is 62 min for aspart, and 65 min for lispro.

Conclusions

In this study, insulin aspart and lispro peak times were estimated at both individual and population levels. Such values are essential to improve the glycaemia prediction accuracy by an artificial pancreas and to achieve a better diabetes management.