Dataset Information

Cross-Validation of a Glucose-Insulin-Glucagon Pharmacodynamics Model for Simulation Using Data From Patients With Type 1 Diabetes.

ABSTRACT:

Background

Currently, no consensus exists on a model describing endogenous glucose production (EGP) as a function of glucagon concentrations. Reliable simulations to determine the glucagon dose preventing or treating hypoglycemia or to tune a dual-hormone artificial pancreas control algorithm need a validated glucoregulatory model including the effect of glucagon.

Methods

Eight type 1 diabetes (T1D) patients each received a subcutaneous (SC) bolus of insulin on four study days to induce mild hypoglycemia followed by a SC bolus of saline or 100, 200, or 300 µg of glucagon. Blood samples were analyzed for concentrations of glucagon, insulin, and glucose. We fitted pharmacokinetic (PK) models to insulin and glucagon data using maximum likelihood and maximum a posteriori estimation methods. Similarly, we fitted a pharmacodynamic (PD) model to glucose data. The PD model included multiplicative effects of insulin and glucagon on EGP. Bias and precision of PD model test fits were assessed by mean predictive error (MPE) and mean absolute predictive error (MAPE).

Results

Assuming constant variables in a subject across nonoutlier visits and using thresholds of ±15% MPE and 20% MAPE, we accepted at least one and at most three PD model test fits in each of the seven subjects. Thus, we successfully validated the PD model by leave-one-out cross-validation in seven out of eight T1D patients.

Conclusions

The PD model accurately simulates glucose excursions based on plasma insulin and glucagon concentrations. The reported PK/PD model including equations and fitted parameters allows for in silico experiments that may help improve diabetes treatment involving glucagon for prevention of hypoglycemia.

SUBMITTER: Wendt SL

PROVIDER: S-EPMC5951032 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Publications

Cross-Validation of a Glucose-Insulin-Glucagon Pharmacodynamics Model for Simulation Using Data From Patients With Type 1 Diabetes.

Wendt Sabrina Lyngbye SL Ranjan Ajenthen A Møller Jan Kloppenborg JK Schmidt Signe S Knudsen Carsten Boye CB Holst Jens Juul JJ Madsbad Sten S Madsen Henrik H Nørgaard Kirsten K Jørgensen John Bagterp JB

Journal of diabetes science and technology 20170201 6

<h4>Background</h4>Currently, no consensus exists on a model describing endogenous glucose production (EGP) as a function of glucagon concentrations. Reliable simulations to determine the glucagon dose preventing or treating hypoglycemia or to tune a dual-hormone artificial pancreas control algorithm need a validated glucoregulatory model including the effect of glucagon.<h4>Methods</h4>Eight type 1 diabetes (T1D) patients each received a subcutaneous (SC) bolus of insulin on four study days to ...[more]

PMID: 28654314

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Project description:BackgroundMost patients with type 1 diabetes do not achieve their glycemic targets. We aimed to assess the efficacy of glucose-responsive insulin and glucagon closed-loop delivery for controlling glucose levels in adults with type 1 diabetes.MethodsWe conducted a randomized crossover trial involving 15 adults with type 1 diabetes, comparing standard insulin-pump therapy with dual-hormone, closed-loop delivery. Patients were admitted twice to a clinical research facility and received, in random order, both treatments. Each 15-hour visit (from 1600 to 0700) included an evening exercise session, followed by a medium-sized meal, a bedtime snack and an overnight stay. During visits that involved closed-loop delivery, basal insulin and glucagon miniboluses were delivered according to recommendations based on glucose sensor readings and a predictive dosing algorithm at 10-minute intervals. During visits involving standard insulin-pump therapy (control visits), patients used conventional treatment.ResultsDual-hormone closed-loop delivery increased the percentage of time for which patients' plasma glucose levels were in the target range (median 70.7% [interquartile range (IQR) 46.1%-88.4%] for closed-loop delivery v. 57.3% [IQR 25.2%-71.8%] for control, p = 0.003) and decreased the percentage of time for which plasma glucose levels were in the low range (bottom of target range [< 4.0 mmol/L], 0.0% [IQR 0.0%-3.0%] for closed-loop delivery v. 10.2% [IQR 0.0%-13.0%] for control, p = 0.01; hypoglycemia threshold [< 3.3 mmol/L], 0.0% [IQR 0.0%-0.0%] for closed-loop delivery v. 2.8% [IQR 0.0%-5.9%] for control, p = 0.006). Eight participants (53%) had at least 1 hypoglycemic event (plasma glucose < 3.0 mmol/L) during standard treatment, compared with just 1 participant (7%) during closed-loop treatment (p = 0.02).InterpretationDual-hormone, closed-loop delivery guided by advanced algorithms improved short-term glucose control and reduced the risk of hypoglycemia in a group of 15 adults with type 1 diabetes.Trial registrationClinicalTrials.gov, no. NCT01297946.

Project description:Type 2 diabetes (T2D) is a pathophysiology that is characterized by insulin resistance, beta- and alpha-cell dysfunction. Mathematical models of various glucose challenge experiments have been developed to quantify the contribution of insulin and beta-cell dysfunction to the pathophysiology of T2D. There is a need for effective extended models that also capture the impact of alpha-cell dysregulation on T2D. In this paper a delay differential equation-based model is developed to describe the coupled glucose-insulin-glucagon dynamics in the isoglycemic intravenous glucose infusion (IIGI) experiment. As the glucose profile in IIGI is tailored to match that of a corresponding oral glucose tolerance test (OGTT), it provides a perfect method for studying hormone responses that are in the normal physiological domain and without the confounding effect of incretins and other gut mediated factors. The model was fit to IIGI data from individuals with and without T2D. Parameters related to glucagon action, suppression, and secretion as well as measures of insulin sensitivity, and glucose stimulated response were determined simultaneously. Significant impairment in glucose dependent glucagon suppression was observed in patients with T2D (duration of T2D: 8 (6-36) months) relative to weight matched control subjects (CS) without diabetes (k1 (mM)-1: 0.16 ± 0.015 (T2D, n = 7); 0.26 ± 0.047 (CS, n = 7)). Insulin action was significantly lower in patients with T2D (a1 (10 pM min)-1: 0.000084 ± 0.0000075 (T2D); 0.00052 ± 0.00015 (CS)) and the Hill coefficient in the equation for glucose dependent insulin response was found to be significantly different in T2D patients relative to CS (h: 1.4 ± 0.15; 1.9 ± 0.14). Trends in parameters with respect to fasting plasma glucose, HbA1c and 2-h glucose values are also presented. Significantly, a negative linear relationship is observed between the glucagon suppression parameter, k1, and the three markers for diabetes and is thus indicative of the role of glucagon in exacerbating the pathophysiology of diabetes (Spearman Rank Correlation: (n = 12; (-0.79, 0.002), (-0.73,.007), (-0.86,.0003)) respectively).

Dataset Information

Cross-Validation of a Glucose-Insulin-Glucagon Pharmacodynamics Model for Simulation Using Data From Patients With Type 1 Diabetes.

Background

Methods

Results

Conclusions

Publications

Cross-Validation of a Glucose-Insulin-Glucagon Pharmacodynamics Model for Simulation Using Data From Patients With Type 1 Diabetes.

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