Minimal modeling of insulin secretion in the perfused rat pancreas: a drug effect case study

GLP-1 Receptor Agonists Models for Type 1 Diabetes: A Narrative Review

BACKGROUND

Glucagon-like peptide 1 (GLP-1) is a hormone that promotes insulin secretion, delays gastric emptying, and inhibits glucagon secretion. The GLP-1 receptor agonists have been developed as adjunctive therapies for type 2 diabetes to improve glucose control. Recently, there has been an interest in introducing GLP-1 receptor agonists as adjunctive therapies in type 1 diabetes alongside automatic insulin delivery systems. The preclinical validation of these systems often relies on mathematical simulators that replicate the glucose dynamics of a person with diabetes. This review aims to explore mathematical models available in the literature to describe GLP-1 effects to be used in a type 1 diabetes simulator.

METHODS

Three databases were examined in the search for GLP-1 mathematical models. More than 1500 works were found after searching for specific keywords that were narrowed down to 39 works for full-text assessment.

RESULTS

A total of 23 works were selected describing GLP-1 pharmacokinetics and pharmacodynamics. However, none of the found models was designed for type 1 diabetes. An analysis is included of the available models' features that could be translated into a GLP-1 receptor agonist model for type 1 diabetes.

CONCLUSION

There is a gap in research in GLP-1 receptor agonists mathematical models for type 1 diabetes, which could be incorporated into type 1 diabetes simulators, providing a safe and inexpensive tool to carry out preclinical validations using these therapies.

Effects of Sustained Treatment With Lixisenatide on Gastric Emptying and Postprandial Glucose Metabolism in Type 2 Diabetes: A Randomized Controlled Trial

OBJECTIVE

Tachyphylaxis for slowing of gastric emptying is seen with continuous exposure to glucagon-like peptide 1 (GLP-1). We therefore aimed to establish whether prolonged use of a "short-acting" GLP-1 receptor agonist, lixisenatide, achieves sustained slowing of gastric emptying and reduction in postprandial glycemia.

RESEARCH DESIGN AND METHODS

A total of 30 patients with metformin-treated type 2 diabetes underwent assessment of gastric emptying (scintigraphy) and glucose metabolism (dual tracer technique) after a 75-g glucose drink, before and after 8 weeks' treatment with lixisenatide (20 μg subcutaneously daily) or placebo, in a double-blind randomized parallel design.

RESULTS

Gastric retention of the glucose drink was markedly increased after lixisenatide versus placebo (ratio of adjusted geometric means for area under the curve [AUC] over 240 min of 2.19 [95% CI 1.82, 2.64], P < 0.001), associated with substantial reductions in the rate of systemic appearance of oral glucose (P < 0.001) and incremental AUC for blood glucose (P < 0.001). Lixisenatide suppressed both glucagon (P = 0.003) and insulin (P = 0.032), but not endogenous glucose production, over 120 min after oral glucose intake. Postprandial glucose lowering over 240 min was strongly related to the magnitude of slowing of gastric emptying by lixisenatide (r = -0.74, P = 0.002) and to the baseline rate of emptying (r = 0.52, P = 0.048) but unrelated to β-cell function (assessed by β-cell glucose sensitivity).

CONCLUSIONS

Eight weeks' treatment with lixisenatide is associated with sustained slowing of gastric emptying and marked reductions in postprandial glycemia and appearance of ingested glucose. Short-acting GLP-1 receptor agonists therefore potentially represent an effective long-term therapy for specifically targeting postprandial glucose excursions.

The Bio-inspired Artificial Pancreas for Type 1 Diabetes Control in the Home: System Architecture and Preliminary Results

BACKGROUND

Artificial pancreas (AP) technology has been proven to improve glucose and patient-centered outcomes for people with type 1 diabetes (T1D). Several approaches to implement the AP have been described, clinically evaluated, and in one case, commercialized. However, none of these approaches has shown a clear superiority with respect to others. In addition, several challenges still need to be solved before achieving a fully automated AP that fulfills the users' expectations. We have introduced the Bio-inspired Artificial Pancreas (BiAP), a hybrid adaptive closed-loop control system based on beta-cell physiology and implemented directly in hardware to provide an embedded low-power solution in a dedicated handheld device. In coordination with the closed-loop controller, the BiAP system incorporates a novel adaptive bolus calculator which aims at improving postprandial glycemic control. This paper focuses on the latest developments of the BiAP system for its utilization in the home environment.

METHODS

The hardware and software architectures of the BiAP system designed to be used in the home environment are described. Then, the clinical trial design proposed to evaluate the BiAP system in an ambulatory setting is introduced. Finally, preliminary results corresponding to two participants enrolled in the trial are presented.

RESULTS

Apart from minor technical issues, mainly due to wireless communications between devices, the BiAP system performed well (~88% of the time in closed-loop) during the clinical trials conducted so far. Preliminary results show that the BiAP system might achieve comparable glycemic outcomes to the existing AP systems (~73% time in target range 70-180 mg/dL).

CONCLUSION

The BiAP system is a viable platform to conduct ambulatory clinical trials and a potential solution for people with T1D to control their glucose control in a home environment.

Logical design of oral glucose ingestion pattern minimizing blood glucose in humans

Excessive increase in blood glucose level after eating increases the risk of macroangiopathy, and a method for not increasing the postprandial blood glucose level is desired. However, a logical design method of the dietary ingestion pattern controlling the postprandial blood glucose level has not yet been established. We constructed a mathematical model of blood glucose control by oral glucose ingestion in three healthy human subjects, and predicted that intermittent ingestion 30 min apart was the optimal glucose ingestion patterns that minimized the peak value of blood glucose level. We confirmed with subjects that this intermittent pattern consistently decreased the peak value of blood glucose level. We also predicted insulin minimization pattern, and found that the intermittent ingestion 30 min apart was optimal, which is similar to that of glucose minimization pattern. Taken together, these results suggest that the glucose minimization is achieved by suppressing the peak value of insulin concentration, rather than by enhancing insulin concentration. This approach could be applied to design optimal dietary ingestion patterns.

A coordinated control strategy for insulin and glucagon delivery in type 1 diabetes

Type 1 diabetes is an autoimmune condition characterised by a pancreatic insulin secretion deficit, resulting in high blood glucose concentrations, which can lead to micro- and macrovascular complications. Type 1 diabetes also leads to impaired glucagon production by the pancreatic α-cells, which acts as a counter-regulatory hormone to insulin. A closed-loop system for automatic insulin and glucagon delivery, also referred to as an artificial pancreas, has the potential to reduce the self-management burden of type 1 diabetes and reduce the risk of hypo- and hyperglycemia. To date, bihormonal closed-loop systems for glucagon and insulin delivery have been based on two independent controllers. However, in physiology, the secretion of insulin and glucagon in the body is closely interconnected by paracrine and endocrine associations. In this work, we present a novel biologically-inspired glucose control strategy that accounts for such coordination. An in silico study using an FDA-accepted type 1 simulator was performed to evaluate the proposed coordinated control strategy compared to its non-coordinated counterpart, as well as an insulin-only version of the controller. The proposed coordinated strategy achieves a reduction of hyperglycemia without increasing hypoglycemia, when compared to its non-coordinated counterpart.

Enhancing automatic closed-loop glucose control in type 1 diabetes with an adaptive meal bolus calculator - in silico evaluation under intra-day variability

BACKGROUND AND OBJECTIVE

Current prototypes of closed-loop systems for glucose control in type 1 diabetes mellitus, also referred to as artificial pancreas systems, require a pre-meal insulin bolus to compensate for delays in subcutaneous insulin absorption in order to avoid initial post-prandial hyperglycemia. Computing such a meal bolus is a challenging task due to the high intra-subject variability of insulin requirements. Most closed-loop systems compute this pre-meal insulin dose by a standard bolus calculation, as is commonly found in insulin pumps. However, the performance of these calculators is limited due to a lack of adaptiveness in front of dynamic changes in insulin requirements. Despite some initial attempts to include adaptation within these calculators, challenges remain.

METHODS

In this paper we present a new technique to automatically adapt the meal-priming bolus within an artificial pancreas. The technique consists of using a novel adaptive bolus calculator based on Case-Based Reasoning and Run-To-Run control, within a closed-loop controller. Coordination between the adaptive bolus calculator and the controller was required to achieve the desired performance. For testing purposes, the clinically validated Imperial College Artificial Pancreas controller was employed. The proposed system was evaluated against itself but without bolus adaptation. The UVa-Padova T1DM v3.2 system was used to carry out a three-month in silico study on 11 adult and 11 adolescent virtual subjects taking into account inter-and intra-subject variability of insulin requirements and uncertainty on carbohydrate intake.

RESULTS

Overall, the closed-loop controller enhanced by an adaptive bolus calculator improves glycemic control when compared to its non-adaptive counterpart. In particular, the following statistically significant improvements were found (non-adaptive vs. adaptive). Adults: mean glucose 142.2 ± 9.4vs. 131.8 ± 4.2mg/dl; percentage time in target [70, 180]mg/dl, 82.0 ± 7.0vs. 89.5 ± 4.2; percentage time above target 17.7 ± 7.0vs. 10.2 ± 4.1. Adolescents: mean glucose 158.2 ± 21.4vs. 140.5 ± 13.0mg/dl; percentage time in target, 65.9 ± 12.9vs. 77.5 ± 12.2; percentage time above target, 31.7 ± 13.1vs. 19.8 ± 10.2. Note that no increase in percentage time in hypoglycemia was observed.

CONCLUSION

Using an adaptive meal bolus calculator within a closed-loop control system has the potential to improve glycemic control in type 1 diabetes when compared to its non-adaptive counterpart.

Recent developments in the discovery of FFA1 receptor agonists as novel oral treatment for type 2 diabetes mellitus

Despite the availability of established medication for treatment of type 2 diabetes mellitus (T2DM) there still remains a significant unmet need for new effective, oral antidiabetic agents that improve glycemic control while maintaining an excellent safety profile. In this regard the FFA1 receptor has emerged as an attractive target in recent years. Activation of the FFA1 receptor has been shown to not only amplify glucose induced insulin secretion from pancreatic beta cells but also to stimulate incretin secretion from intestinal endocrine cells. The current review highlights on the latest developments and clinical data from evolving research on the potential of FFA1 agonists as effective treatment for T2DM.