A Subcutaneous Insulin Pharmacokinetic Model for Computer Simulation in a Diabetes Decision Support Role: Model Structure and Parameter Identification

Author:

Wong Jason1,Chase J. Geoffrey1,Hann Christopher E.1,Shaw Geoffrey M.2,Lotz Thomas F.1,Lin Jessica1,Le Compte Aaron J.1

Affiliation:

1. Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand

2. Department of Intensive Care, Christchurch Hospital, Christchurch School of Medicine and Health Science, University of Otago, Dunedin, New Zealand

Abstract

Objective: The goal of this study was to develop a unified physiological subcutaneous (SC) insulin absorption model for computer simulation in a clinical diabetes decision support role. The model must model the plasma insulin appearance of a wide range of current insulins, especially monomer insulin and insulin glargine, utilizing common chemical states and transport rates, where appropriate. Methods: A compartmental model was developed with 13 patient-specific model parameters covering six diverse insulin types [rapid-acting, regular, neutral protamine Hagedorn (NPH), lente, ultralente, and glargine insulin]. Model parameters were identified using 37 sets of mean plasma insulin time-course data from an extensive literature review via nonlinear optimization methods. Results: All fitted parameters have a coefficient of variation <100% (median 51.3%, 95th percentile 3.6–60.6%) and can be considered a posteriori identifiable. Conclusion: A model is presented to describe SC injected insulin appearance in plasma in a diabetes decision support role. Clinically current insulin types (monomeric insulin, regular insulin, NPH, insulin, and glargine) and older insulin types (lente and ultralente) are included in a unified framework that accounts for nonlinear concentration and dose dependency. Future work requires clinical validation using published pharmacokinetic studies.

Publisher

SAGE Publications

Subject

Biomedical Engineering,Bioengineering,Endocrinology, Diabetes and Metabolism,Internal Medicine

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