Insulin in Type 1 and Type 2 Diabetes-Should the Dose of Insulin Before a Meal be Based on Glycemia or Meal Content?

A Glucose-Responsive Cannula for Automated and Electronics-Free Insulin Delivery

Automated delivery of insulin based on continuous glucose monitoring is revolutionizing the way insulin-dependent diabetes is treated. However, challenges remain for the widespread adoption of these systems, including the requirement of a separate glucose sensor, sophisticated electronics and algorithms, and the need for significant user input to operate these costly therapies. Herein, a user-centric glucose-responsive cannula is reported for electronics-free insulin delivery. The cannula-made from a tough, elastomer-hydrogel hybrid membrane formed through a one-pot solvent exchange method-changes permeability to release insulin rapidly upon physiologically relevant varying glucose levels, providing simple and automated insulin delivery with no additional hardware or software. Two prototypes of the cannula are evaluated in insulin-deficient diabetic mice. The first cannula-an ends-sealed, subcutaneously inserted prototype-normalizes blood glucose levels for 3 d and controls postprandial glucose levels. The second, more translational version-a cannula with the distal end sealed and the proximal end connected to a transcutaneous injection port-likewise demonstrates tight, 3-d regulation of blood glucose levels when refilled twice daily. This proof-of-concept study may aid in the development of "smart" cannulas and next-generation insulin therapies at a reduced burden-of-care toll and cost to end-users.

Impact of gut microbiota and associated mechanisms on postprandial glucose levels in patients with diabetes

Diabetes and its complications are serious medical and global burdens, often manifesting as postprandial hyperglycemia. In recent years, considerable research attention has focused on relationships between the gut microbiota and circulating postprandial glucose (PPG). Different population studies have suggested that PPG is closely related to the gut microbiota which may impact PPG via short-chain fatty acids (SCFAs), bile acids (BAs) and trimethylamine N-oxide (TMAO). Studies now show that gut microbiota models can predict PPG, with individualized nutrition intervention strategies used to regulate gut microbiota and improve glucose metabolism to facilitate the precision treatment of diabetes. However, few studies have been conducted in patients with diabetes. Therefore, little is known about the relationships between the gut microbiota and PPG in this cohort. Thus, more research is required to identify key gut microbiota and associated metabolites and pathways impacting PPG to provide potential therapeutic targets for PPG.

Associations Between Psychosocial Needs, Carbohydrate-Counting Behavior, and App Satisfaction: A Randomized Crossover App Trial on 92 Adults With Diabetes

To examine whether psychosocial needs in diabetes care are associated with carbohydrate counting and if carbohydrate counting is associated with satisfaction with diabetes applications' usability, a randomized crossover trial of 92 adults with type 1 or 2 diabetes requiring insulin therapy tested two top-rated diabetes applications, mySugr and OnTrack Diabetes. Survey responses on demographics, psychosocial needs (perceived competence, autonomy, and connectivity), carbohydrate-counting frequency, and application satisfaction were modeled using mixed-effect linear regressions to test associations. Participants ranged between 19 and 74 years old (mean, 54 years) and predominantly had type 2 diabetes (70%). Among the three tested domains of psychosocial needs, only competence-not autonomy or connectivity-was found to be associated with carbohydrate-counting frequency. No association between carbohydrate-counting behavior and application satisfaction was found. In conclusion, perceived competence in diabetes care is an important factor in carbohydrate counting; clinicians may improve adherence to carbohydrate counting with strategies designed to improve perceived competence. Carbohydrate-counting behavior is complex; its impact on patient satisfaction of diabetes application usability is multifactorial and warrants consideration of patient demographics such as sex as well as application features for automated carbohydrate counting.

An automated all-in-one system for carbohydrate tracking, glucose monitoring, and insulin delivery

Glycemic control through titration of insulin dosing remains the mainstay of diabetes mellitus treatment. Insulin therapy is generally divided into dosing with long- and short-acting insulin, where long-acting insulin provides basal coverage and short-acting insulin supports glycemic excursions associated with eating. The dosing of short-acting insulin often involves several steps for the user including blood glucose measurement and integration of potential carbohydrate loads to inform safe and appropriate dosing. The significant burden placed on the user for blood glucose measurement and effective carbohydrate counting can manifest in substantial effects on adherence. Through the application of computer vision, we have developed a smartphone-based system that is able to detect the carbohydrate load of food by simply taking a single image of the food and converting that information into a required insulin dose by incorporating a blood glucose measurement. Moreover, we report the development of comprehensive all-in-one insulin delivery systems that streamline all operations that peripheral devices require for safe insulin administration, which in turn significantly reduces the complexity and time required for titration of insulin. The development of an autonomous system that supports maximum ease and accuracy of insulin dosing will transform our ability to more effectively support patients with diabetes.

Ultra Rapid Lispro (URLi) Accelerates Insulin Lispro Absorption and Insulin Action vs Humalog® Consistently Across Study Populations: A Pooled Analysis of Pharmacokinetic and Glucodynamic Data

BACKGROUND AND OBJECTIVE

Ultra rapid lispro (URLi) is a novel insulin lispro formulation developed to more closely match physiological insulin secretion and improve postprandial glucose control. This pooled analysis compared the pharmacokinetics and glucodynamics between URLi and Humalog® in healthy subjects and patients with type 1 or type 2 diabetes mellitus.

METHODS

The analysis included four randomized, double-blind, crossover, single-dose studies (healthy subjects [n = 74], patients with type 1 diabetes [n = 78], and type 2 diabetes [n = 38]) evaluating subcutaneous doses of 7, 15, or 30 U of URLi and Humalog during an 8- to 10-h euglycemic clamp procedure.

RESULTS

The pooled analysis showed an ~ 5-min faster onset of appearance, an ~8-fold greater exposure in the first 15 min, a 43% reduction in exposure beyond 3 h, and a 68-min shorter exposure duration with URLi vs Humalog across all study populations and dose range. Compared with Humalog, URLi had a 10-min faster onset of action, a 3-fold greater insulin action in the first 30 min, a 35% reduction in insulin action beyond 4 h, and a 44-min shorter duration of action across all populations and dose range. Overall exposure and insulin action were similar between URLi and Humalog for each dose level and study population.

CONCLUSIONS

Across the studied populations and dose range, URLi consistently demonstrated a faster absorption, reduced late exposure, and overall shorter exposure duration compared with Humalog. Similarly, URLi demonstrated earlier insulin action while reducing late insulin action and shorter insulin action compared with Humalog across the study populations and dose range.

CLINICAL TRIAL REGISTRATION

NCT02942654 (registered: 21 October, 2016), NCT03286751 (registered: 15 September, 2017), NCT03166124 (registered: 23 May, 2017), and NCT03305822 (registered: 5 October, 2017).

The Role of Protein and Fat Intake on Insulin Therapy in Glycaemic Control of Paediatric Type 1 Diabetes: A Systematic Review and Research Gaps

Carbohydrate counting (CHC) is the established form of calculating bolus insulin for meals in children with type 1 diabetes (T1DM). With the widespread use of continuous glucose monitoring (CGM) observation time has become gapless. Recently, the impact of fat, protein and not only carbohydrates on prolonged postprandial hyperglycaemia have become more evident to patients and health-care professionals alike. However, there is no unified recommendation on how to calculate and best administer additional bolus insulin for these two macronutrients. The aim of this review is to investigate: the scientific evidence of how dietary fat and protein influence postprandial glucose levels; current recommendations on the adjustment of bolus insulin; and algorithms for insulin application in children with T1DM. A PubMed search for all articles addressing the role of fat and protein in paediatric (sub-)populations (<18 years old) and a mixed age population (paediatric and adult) with T1DM published in the last 10 years was performed. Conclusion: Only a small number of studies with a very low number of participants and high degree of heterogeneity was identified. While all studies concluded that additional bolus insulin for (high) fat and (high) protein is necessary, no consensus on when dietary fat and/or protein should be taken into calculation and no unified algorithm for insulin therapy in this context exists. A prolonged postprandial observation time is necessary to improve individual metabolic control. Further studies focusing on a stratified paediatric population to create a safe and effective algorithm, taking fat and protein into account, are necessary.

Dietary Aspects to Incorporate in the Creation of a Mobile Image-Based Dietary Assessment Tool to Manage and Improve Diabetes

Diabetes is the seventh leading cause of death in United States. Dietary intake and behaviors are essential components of diabetes management. Growing evidence suggests dietary components beyond carbohydrates may critically impact glycemic control. Assessment tools on mobile platforms have the ability to capture multiple aspects of dietary behavior in real-time throughout the day to inform and improve diabetes management and insulin dosing. The objective of this narrative review was to summarize evidence related to dietary behaviors and composition to inform a mobile image-based dietary assessment tool for managing glycemic control of both diabetes types (type 1 and type 2 diabetes). This review investigated the following topics amongst those with diabetes: (1) the role of time of eating occasion on indicators of glycemic control; and (2) the role of macronutrient composition of meals on indicators of glycemic control. A search for articles published after 2000 was completed in PubMed with the following sets of keywords “diabetes/diabetes management/diabetes prevention/diabetes risk”, “dietary behavior/eating patterns/temporal/meal timing/meal frequency”, and “macronutrient composition/glycemic index”. Results showed eating behaviors and meal macronutrient composition may affect glycemic control. Specifically, breakfast skipping, late eating and frequent meal consumption might be associated with poor glycemic control while macronutrient composition and order of the meal could also affect glycemic control. These factors should be considered in designing a dietary assessment tool, which may optimize diabetes management to reduce the burden of this disease.

The comparison of two mealtime insulin dosing algorithms for high and low glycaemic index meals in adolescents with type 1 diabetes

AIMS

Postprandial glycaemic variability carries on being a clinical challenge in optimizing glucose control in type 1 diabetes. The aim of this study was to compare the postprandial glycaemic effects of carbohydrate counting and food insulin index algorithms following the consumption of protein-rich, high-fat meals with different glycaemic index (GI) in adolescents with type 1 diabetes.

METHODS

A randomized, single-blind and crossover trial included 15 adolescents aged 14-18 years with type 1 diabetes. Participants consumed two different test meals with similar energy, macronutrients and food insulin index but the approximately twofold difference in GI, in random order on four consecutive mornings at their home. Insulin dose for high- and low-GI test meals was determined by using the carbohydrate counting and food insulin index algorithms. Four-hour postprandial glycaemia was assessed by the continuous glucose monitoring system.

RESULTS

Compared with carbohydrate counting, the food insulin index algorithm significantly decreased peak glucose excursion (-57%, p = 0.02), incremental area under the curve (-65%, p = 0.02) and coefficient variation of blood glucose (-37%, p = 0.03) in the high-GI meal, though there was no difference between the two algorithms in the low-GI meal. The occurrence of hypoglycaemia did not significantly differ between insulin dosing algorithms for the high-GI (p = 0.58) and low-GI (p = 0.20) meals.

CONCLUSIONS

The food insulin index algorithm may be beneficial for postprandial glycaemic control after the consumption of high-GI meals in adolescents with type 1 diabetes.

Pharmacokinetic and Glucodynamic Responses of Ultra Rapid Lispro vs Lispro Across a Clinically Relevant Range of Subcutaneous Doses in Healthy Subjects

PURPOSE

Ultra rapid lispro (URLi) is a novel insulin lispro formulation developed to more closely match physiological insulin secretion and improve postprandial glucose control. This study compared the pharmacokinetic and glucodynamic parameters of URLi and Lispro (Humalog®) at 3 dose levels in healthy subjects.

METHODS

This randomized, 6-period, subject- and investigator-blind, crossover study included 42 healthy subjects. At each period, subjects received a single subcutaneous dose of 7, 15, or 30 U of URLi or Lispro followed by a 10-h automated euglycemic clamp. Insulin lispro and blood glucose concentrations were measured.

FINDINGS

Across all 3 doses, insulin lispro appeared in the serum 2-5 min faster, and exposure was 6- to 8-fold greater in the first 15 min, with URLi versus Lispro. Exposure beyond 3 h postdose was 45%-52% lower, and duration of exposure was 67-86 min shorter with URLi versus Lispro for all dose levels. Onset of insulin action was 7-9 min faster and insulin action was ~3-fold greater in the first 30 min with URLi versus Lispro across the dose levels. Insulin action beyond 4 h was reduced by 32%-45%, and duration of action was reduced by 47-67 min, with URLi versus Lispro for all 3 dose levels. Overall exposure and total glucose infused were similar between URLi and Lispro at each dose level. Dose proportionality was observed for maximum and overall exposure after URLi. Less than dose-proportional increases in maximum and total glucose infused were observed and were similar for both URLi and Lispro.

IMPLICATIONS

URLi exhibited ultra-rapid pharmacokinetic and glucodynamic parameters across all 3 dose levels studied and exhibited dose-proportional increases in exposure in healthy subjects. ClinicalTrials.gov identifier: NCT03286751.

Therapeutic Advancements in the Management of Diabetes Mellitus with Special Reference to Nanotechnology

For improvisation of diabetic's quality of life, nanotechnology is facilitating the development of advanced glucose sensors as well as efficient insulin delivery systems. Our prime focus of the review is to highlight the advancement in diabetic research with special reference to nanotechnology at its interface. Recent studies are more focused on enhancing sensitivity, accuracy, and response by employing metal as well as nanoparticles based glucose sensors. Moreover, the review focuses on nanoscale based approaches i.e. closed-loop insulin delivery systems, which detect any fluctuation in blood glucose levels and allow controlled release of a drug, thus are also called self-regulating insulin release system. Additionally, this review summarizes the role of nanotechnology in the diagnosis and treatment of diabetic complications through little advancement in the existing techniques. To improve health, as well as the quality of life in diabetic's new sensing systems for blood glucose level evaluation and controlled administration of drugs through efficient drug delivery systems should be explored.

Dietary Intake and Type 2 Diabetes

This editorial aims to examine the risk factors associated with type 2 diabetes and to discuss the evidence relating to dietary strategies for managing people with this condition. It is clear from the evidence presented that a range of dietary interventions can provide useful approaches for managing people with type 2 diabetes, including the regulation of blood glucose and lipid parameters, and for reducing the risks of acute and chronic diabetic complications.

Postprandial Glucose Control in Type 1 Diabetes: Importance of the Gastric Emptying Rate

The achievement of optimal post-prandial (PP) glucose control in patients with type 1 diabetes (T1DM) remains a great challenge. This review summarizes the main factors contributing to PP glucose response and discusses the likely reasons why PP glucose control is rarely achieved in T1DM patients. The macronutrient composition of the meal, the rate of gastric emptying and premeal insulin administration are key factors affecting the PP glucose response in T1DM. Although the use of continuous insulin infusion systems has improved PP glucose control compared to conventional insulin therapy, there is still need for further ameliorations. T1DM patients frequently present a delayed gastric emptying (GE) that produces a lower but more prolonged PP hyperglycemia. In addition, delayed GE is associated with a longer time to reach the glycemic peak, with a consequent mismatch between PP glucose elevation and the timing of premeal insulin action. On this basis, including GE time and meal composition in the algorithms for insulin bolus calculation of the insulin delivery systems could be an important step forward for optimization of PP glucose control in T1DM.