Background and Aims

Clinical trials in free-living conditions is key in the development of an Artificial Pancreas (AP) for T1D subjects. Since the scenario plays a key role in the synthesis and validation of AP control algorithms, a probabilistic approach is proposed to automatically design meal scenarios. In particular, we exploit our real-life data to design realistic in silico scenarios.

Methods

The amount and time-of-day of ingested carbohydrates in a 1-month in 13 patients for a total of 1500 meals. have been considered. The joint distribution of these variables has been estimated via a copula function, in order to model their dependence. The use of a copula allows to generate Monte Carlo scenarios by drawing random samples, which represent a pair of amount and time-of-day.

Results

A Gaussian copula resulted suitable for the description of the dependence in the meal dataset with a p-value of 0.005 according to the χ² test based on Rosenblatt’s transformation. A bootstrap version of the test shows that the estimate of the Spearman correlation coefficient (ρ) is sufficiently accurate with respect to the correlation (ρ) directly computed from the data (ρ=0.13, ρ=0.12).

Conclusions

The availability of a copula statistical model able to represent the food habits of a T1D population allows to design realistic eating patterns to run in silico simulations under free-living conditions.

Background and Aims

An Artificial Pancreas usually involves subcutaneous (sc) devices to measure glucose and to infuse insulin with important delays. The intraperitoneal (ip) route is more physiological and would avoid the sc delays, improving glucose control[A]. In these last years, new ip devices have been designed[B] and new modalities of ip insulin delivery, e.g pulsatile, have been tested. The aim here is to present the new simulator and its first use in in silico trial comparing the ip vs. sc insulin delivery route.

[A]Dassau, E. et al. Diabetes,Obesity and Metabolism,19.12(2017):1698-1705.

[B]Iacovacci V. et al. Journal of Medical Devices,13.1(2019):011008.

Methods

The model of the UVA/Padova simulator has been modified to describe ip insulin administration. A Run-to-Run approach is used to adapt the Basal-Bolus Therapy (BBT) of the 100 in silico patients to the new ip site. A new version of the MPC controller [C] is synthesised using the new simulator and the optimized BBT.

[C] Soru P. et al. Annual Reviews in Control,36.1(2012):118-128.

Results

The intraperitoneal controller tested on a 2 days scenario maintains the glucose inside the target range for 93.5% of the time with no time spent below 70 mg/dl and 6.5% above 180 mg/dl. The MPC is able to keep the glycaemia inside the target range during all night.

Conclusions

The ip MPC results are much better than those obtained with the sc MPC. Future development of MPC involves the design of ad hoc constraints and safety. This new MPC in conjunctions with a new ip insulin pump will be tested in animals.