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. 2023 May;17(3):751-756.
doi: 10.1177/19322968221076559. Epub 2022 Feb 10.

Intraperitoneal Insulin Delivery: Evidence of a Physiological Route for Artificial Pancreas From Compartmental Modeling

Jorge Lo Presti  1 , Alfonso Galderisi  1   2 , Francis J Doyle 3rd  3 , Howard C Zisser  4 , Eyal Dassau  3 , Eric Renard  5   6 , Chiara Toffanin  7 , Claudio Cobelli  1
Affiliations

Intraperitoneal Insulin Delivery: Evidence of a Physiological Route for Artificial Pancreas From Compartmental Modeling

Jorge Lo Presti et al. J Diabetes Sci Technol. 2023 May.

Abstract

Background: Intraperitoneal insulin delivery has proven to safely overcome a major limit of subcutaneous delivery-meal announcement-and has been able to optimize glycemic control in adults under controlled experimental conditions. In addition, intraperitoneal delivery avoids peripheral hyperinsulinemia resulting from the subcutaneous route and restores a physiological liver gradient.

Methods: Relying on a unique data set of intraperitoneal closed-loop insulin delivery obtained with a Model Predictive Controller (MPC), we develop a compartmental model of intraperitoneal insulin kinetics, which, once included in the UVa/Padova T1D simulator, will facilitate the investigation of various control strategies, for example, the simpler Proportional Integral Derivative controller versus MPC.

Results: Intraperitoneal insulin kinetics can be described with a 2-compartment model including liver and plasma.

Conclusion: Intraperitoneal insulin transit is fast enough to render irrelevant the addition of a peritoneal compartment, proving the peritoneum being a virtual-not actual-transit space for insulin delivery.

Keywords: closed-loop; insulin kinetics; intraperitoneal insulin delivery; type 1 diabetes.

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Conflict of interest statement

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: JL, AG, ER, CT, and CC have no conflict of interest to report related to this article; ED is currently an employee and shareholder of Eli Lilly and Company, the work presented in this article was performed as part of his academic appointment and is independent of his employment with Eli Lilly and Company; FJD reports equity, licensed IP, and is a member of the scientific advisory board of Mode AGC; HCZ is currently employed by Verily Diabetes. No other potential conflicts of interest relevant to this article were reported.

Figures

Figure 1.
Figure 1.
Four intraperitoneal insulin kinetics models. Abbreviations: RaIP, rate of intraperitoneal glucose appearance; IP, intraperitoneal; Il, liver insulin concentration; IP, plasma insulin concentration; IT, peripheral insulin concentration.
Figure 2.
Figure 2.
Model 4 fit (continuous line) against plasma insulin data (circles) for participant 9.
Figure 3.
Figure 3.
Weighted residual plot on all the nine subjects. Data are presented as median and interquartile range. Modeling methodology requires that most of the weighted residuals lay in the +1/−1 region.
See this image and copyright information in PMC

References

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