Interleaved trinuclear MRS for single-session investigation of carbohydrate and lipid metabolism in human liver at 7T.

The liver plays a central role in metabolic homeostasis, as exemplified by a variety of clinical disorders with hepatic and systemic metabolic disarrays. Of particular interest are the complex interactions between lipid and carbohydrate metabolism in highly prevalent conditions such as obesity, diabetes, and fatty liver disease. Limited accessibility and the need for invasive procedures challenge direct investigations in humans. Hence, noninvasive dynamic evaluations of glycolytic flux and steady-state assessments of lipid levels and composition are crucial for basic understanding and may open new avenues toward novel therapeutic targets. Here, three different MR spectroscopy (MRS) techniques that have been combined in a single interleaved examination in a 7T MR scanner are evaluated. 1H-MRS and 13C-MRS probe endogenous metabolites, while deuterium metabolic imaging (DMI) relies on administration of deuterated tracers, currently 2H-labelled glucose, to map the spatial and temporal evolution of their metabolic fate. All three techniques have been optimized for a robust single-session clinical investigation and applied in a preliminary study of healthy subjects. The use of a triple-channel 1H/2H/13C RF coil enables interleaved examinations with no need for repositioning. Short-echo-time STEAM spectroscopy provides well resolved spectra to quantify lipid content and composition. The relative benefits of using water saturation versus metabolite cycling and types of respiratory synchronization were evaluated. 2H-MR spectroscopic imaging allowed for registration of time- and space-resolved glucose levels following oral ingestion of 2H-glucose, while natural abundance 13C-MRS of glycogen provides a dynamic measure of hepatic glucose storage. For DMI and 13C-MRS, the measurement precision of the method was estimated to be about 0.2 and about 16 mM, respectively, for 5 min scanning periods. Excellent results were shown for the determination of dynamic uptake of glucose with DMI and lipid profiles with 1H-MRS, while the determination of changes in glycogen levels by 13C-MRS is also feasible but somewhat more limited by signal-to-noise ratio.

Tailoring the Padova Type 2 Diabetes Simulator for Treatment Guidance in Target Populations.

OBJECTIVE: The Padova type 2 diabetes (T2D) simulator (T2DS) has been recently proposed to optimize T2D treatments including novel long-acting insulins. It consists of a physiological model and an in silico population describing glucose dynamics, derived from early-stage T2D subjects studied with sophisticated tracer-based experimental techniques. This limits T2DS domain of validity to this specific sub-population. Conversely, running simulations in insulin-naïve or advanced T2D subjects, would be more valuable. However, it is rarely possible or cost-effective to run complex experiments in such populations. Therefore, we propose a method for tuning the T2DS to any desired T2D sub-population using published clinical data. As case study, we extended the T2DS to insulin-naïve T2D subjects, who need to start insulin therapy to compensate the reduced insulin function. METHODS: T2DS model was identified based on literature data of the target population. The estimated parameters were used to generate a virtual cohort of insulin-naïve T2D subjects (inC1). A model of basal insulin degludec (IDeg) was also incorporated into the T2DS to enable basal insulin therapy. The resulting tailored T2DS was assessed by simulating IDeg therapy initiation and comparing simulated vs. clinical trial outcomes. For further validation, this procedure was reiterated to generate a new cohort of insulin-naïve T2D (inC2) assuming inC1 as target population. RESULTS: No statistically significant differences were found when comparing fasting plasma glucose and IDeg dose, neither in clinical data vs. inC1, nor inC1 vs. inC2. CONCLUSIONS: The tuned T2DS allowed reproducing the main findings of clinical studies in insulin-naïve T2D subjects. SIGNIFICANCE: The proposed methodology makes the Padova T2DS usable for supporting treatment guidance in target T2D populations.

The Minimally-Invasive Oral Glucose Minimal Model: Estimation of Gastric Retention, Glucose Rate of Appearance, and Insulin Sensitivity From Type 1 Diabetes Data Collected in Real-Life Conditions.

OBJECTIVE: Modeling the effect of meal composition on glucose excursion would help in designing decision support systems (DSS) for type 1 diabetes (T1D) management. In fact, macronutrients differently affect post-prandial gastric retention (GR), rate of appearance (R[Formula: see text]), and insulin sensitivity (S[Formula: see text]). Such variables can be estimated, in inpatient settings, from plasma glucose (G) and insulin (I) data using the Oral glucose Minimal Model (OMM) coupled with a physiological model of glucose transit through the gastrointestinal tract (reference OMM, R-OMM). Here, we present a model able to estimate those quantities in daily-life conditions, using minimally-invasive (MI) technologies, and validate it against the R-OMM. METHODS: Forty-seven individuals with T1D (weight =78±13 kg, age =42±10 yr) underwent three 23-hour visits, during which G and I were frequently sampled while wearing continuous glucose monitoring (CGM) and insulin pump (IP). Using a Bayesian Maximum A Posteriori estimator, R-OMM was identified from plasma G and I measurements, and MI-OMM was identified from CGM and IP data. RESULTS: The MI-OMM fitted the CGM data well and provided precise parameter estimates. GR and R[Formula: see text] model parameters were not significantly different using the MI-OMM and R-OMM (p 0.05) and the correlation between the two S[Formula: see text] was satisfactory ( ρ =0.77). CONCLUSION: The MI-OMM is usable to estimate GR, R[Formula: see text], and S[Formula: see text] from data collected in real-life conditions with minimally-invasive technologies. SIGNIFICANCE: Applying MI-OMM to datasets where meal compositions are available will allow modeling the effect of each macronutrient on GR, R[Formula: see text], and S[Formula: see text]. DSS could finally exploit this information to improve diabetes management.

A New Index of Insulin Sensitivity from Glucose Sensor and Insulin Pump Data: In Silico and In Vivo Validation in Youths with Type 1 Diabetes.

Background: Estimation of insulin sensitivity (SI) and its daily variation are key for optimizing insulin therapy in patients with type 1 diabetes (T1D). We recently developed a method for SI estimation from continuous glucose monitoring (CGM) and continuous subcutaneous insulin infusion (CSII) data in adults with T1D (SISP) and validated it under restrained experimental conditions. Herein, we validate in vivo a new version of SISP performing well in daily life unrestrained conditions. Methods: The new SISP was tested in both simulated and real data. The simulated dataset consists of 100 virtual adults of the UVa/Padova T1D Simulator monitored during an open-loop experiment, whereas the real dataset consists of 10 youths with T1D monitored during a hybrid closed-loop meal study. In both datasets, participants underwent two consecutive meals (breakfast and lunch, at 7 and 11 am) with the same carbohydrate content (70 g). Plasma glucose and insulin were measured during each meal to estimate the oral glucose minimal model SI (SIMM). CGM and CSII data were used for SISP calculation, which was then validated against the gold standard SIMM. Results: SISP was estimated with good precision (median coefficient of variation <20%) in 100% of the real and 91% of the simulated meals. SISP and SIMM were highly correlated, both in the simulated and real datasets (R = 0.82 and R = 0.83, P < 0.001), and exhibited a similar intraday pattern. Conclusions: SISP is suitable for estimating SI in both closed- and open-loop settings, provided that the subject wears a CGM sensor and a subcutaneous insulin pump.

Counter-regulatory responses to postprandial hypoglycaemia in patients with post-bariatric hypoglycaemia vs surgical and non-surgical control individuals.

AIMS/HYPOTHESIS: Post-bariatric hypoglycaemia is an increasingly recognised complication of bariatric surgery, manifesting particularly after Roux-en-Y gastric bypass. While hyperinsulinaemia is an established pathophysiological feature, the role of counter-regulation remains unclear. We aimed to assess counter-regulatory hormones and glucose fluxes during insulin-induced postprandial hypoglycaemia in patients with post-bariatric hypoglycaemia after Roux-en-Y gastric bypass vs surgical and non-surgical control individuals. METHODS: In this case-control study, 32 adults belonging to four groups with comparable age, sex and BMI (patients with post-bariatric hypoglycaemia, Roux-en-Y gastric bypass, sleeve gastrectomy and non-surgical control individuals) underwent a postprandial hypoglycaemic clamp in our clinical research unit to reach the glycaemic target of 2.5 mmol/l 150-170 min after ingesting 15 g of glucose. Glucose fluxes were assessed during the postprandial and hypoglycaemic period using a dual-tracer approach. The primary outcome was the incremental AUC of glucagon during hypoglycaemia. Catecholamines, cortisol, growth hormone, pancreatic polypeptide and endogenous glucose production were also analysed during hypoglycaemia. RESULTS: The rate of glucose appearance after oral administration, as well as the rates of total glucose appearance and glucose disappearance, were higher in both Roux-en-Y gastric bypass groups vs the non-surgical control group in the early postprandial period (all p<0.05). During hypoglycaemia, glucagon exposure was significantly lower in all surgical groups vs the non-surgical control group (all p<0.01). Pancreatic polypeptide levels were significantly lower in patients with post-bariatric hypoglycaemia vs the non-surgical control group (median [IQR]: 24.7 [10.9, 38.7] pmol/l vs 238.7 [186.3, 288.9] pmol/l) (p=0.005). Other hormonal responses to hypoglycaemia and endogenous glucose production did not significantly differ between the groups. CONCLUSIONS/INTERPRETATION: The glucagon response to insulin-induced postprandial hypoglycaemia is lower in post-bariatric surgery individuals compared with non-surgical control individuals, irrespective of the surgical modality. No significant differences were found between patients with post-bariatric hypoglycaemia and surgical control individuals, suggesting that impaired counter-regulation is not a root cause of post-bariatric hypoglycaemia. TRIAL REGISTRATION: ClinicalTrials.gov NCT04334161.

Unraveling, contributing factors to the severity of postprandial hypoglycemia after gastric bypass surgery.

BACKGROUND: Despite the increasing prevalence of postbariatric hypoglycemia (PBH), a late metabolic complication of bariatric surgery, our understanding of its diverse manifestations remains incomplete. OBJECTIVES: To contrast parameters of glucose-insulin homeostasis in 2 distinct phenotypes of PBH (mild versus moderate hypoglycemia) based on nadir plasma glucose. SETTING: University Hospital (Bern, Switzerland). METHODS: Twenty-five subjects with PBH following gastric bypass surgery (age, 41 ± 12 years; body mass index, 28.1 ± 6.1kg/m2) received 75g of glucose with frequent blood sampling for glucose, insulin, C-peptide, and glucagon-like peptide 1 (GLP)-1. Based on nadir plasma glucose (

Effects of Roux-en-Y Gastric Bypass and Sleeve Gastrectomy on ß-Cell Function at 1 Year After Surgery: A Systematic Review.

Bariatric surgery is a highly effective obesity treatment resulting in substantial weight loss and improved glucose metabolism. We hereby aimed to summarize available evidence of the effect of the 2 most common bariatric surgery procedures, Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG), on dynamic measures of ß-cell function (BCF). A systematic search of the literature was conducted in 3 bibliographic databases for studies reporting effects of RYGB and/or SG on BCF assessed using dynamic metabolic perturbation (oral or intravenous bolus stimulation), performed before and 1 year (±3 months) after surgery. Twenty-seven unique studies (6 randomized controlled trials and 21 observational studies), involving a total of 1856 obese adults, were included for final analysis. Twenty-five and 9 studies report effects of RYGB and SG on BCF, respectively (7 studies compared the 2 procedures). Seven studies report results according to presurgical diabetes status. Owing to variable testing procedures and BCF indices reported, no meta-analysis was feasible, and data were summarized qualitatively. For both surgical procedures, most studies suggest an increase in BCF and disposition index, particularly when using oral stimulation, with a more pronounced increase in diabetic than nondiabetic individuals. Additionally, limited indications for greater effects after RYGB versus SG were found. The quality of the included studies was, in general, satisfactory. The considerable heterogeneity of test protocols and outcome measures underscore the need for a harmonization of BCF testing in future research.

Modeling Between-Subject Variability in Subcutaneous Absorption of a Long-Acting Insulin Glargine 100 U/mL by a Nonlinear Mixed Effects Approach.

Subcutaneous insulin absorption is well-known to vary significantly both between and within subjects (BSV and WSV, respectively). This variability considerably obstacles the establishing of a reproducible and effective insulin therapy. Some models exist to describe the subcutaneous kinetics of both fast and long-acting insulin analogues; however, none of them account for the BSV. The aim of this study is to develop a nonlinear mixed effects model able to describe the BSV observed in the subcutaneous absorption of a long-acting insulin glargine 100 U/mL. Four stochastic models of the BSV were added to a previously validated model of subcutaneous absorption of insulin glargine 100 U/mL. These were assessed on a database of 47 subjects with type 1 diabetes. The best model was selected based on residual analysis, precision of the estimates and parsimony criteria. The selected model provided good fit of individual data, precise population parameter estimates and allowed quantifying the BSV of the insulin glargine 100 U/mL pharmacokinetics. Future model development will include the description of the WSV of long- acting insulin absorption.

Modeling Intraperitoneal Insulin Absorption in Patients with Type 1 Diabetes.

Standard insulin therapy to treat type 1 diabetes (T1D) consists of exogenous insulin administration through the subcutaneous (SC) tissue. Despite recent advances in insulin formulations, the SC route still suffers from delays and large inter/intra-subject variability that limiting optimal glucose control. Intraperitoneal (IP) insulin administration, despite its higher invasiveness, was shown to represent a valid alternative to the SC one. To date, no mathematical model describing the absorption and distribution of insulin after IP administration is available. Here, we aim to fill this gap by using data from eight patients with T1D, treated by implanted IP pump, studied in a hospitalized setting, with frequent measurements of plasma insulin and glucose concentration. A battery of models describing insulin kinetics after IP administration were tested. Model comparison and selection were performed based on model ability to predict the data, precision of parameters and parsimony criteria. The selected model assumed that the insulin absorption from the IP space was described by a linear, two-compartment model, coupled with a two-compartment model of whole-body insulin kinetics with hepatic insulin extraction controlled by hepatic insulin. Future developments include model incorporation into the UVa/Padova T1D Simulator for testing open- and closed-loop therapies with IP insulin administration.

Exercise effect on insulin-dependent and insulin-independent glucose utilization in healthy individuals and individuals with type 1 diabetes: a modeling study.

Exercise effects (EE) on whole body glucose rate of disappearance (Rd) occur through insulin-independent (IIRd) and insulin-dependent (IDRd) mechanisms. Quantifying these processes in vivo would allow a better understanding of the physiology of glucose regulation. This is of particular importance in individuals with type 1 diabetes (T1D) since such a knowledge may help to improve glucose management. However, such a model is still lacking. Here, we analyzed data from six T1D and six nondiabetic (ND) subjects undergoing a labeled glucose clamp study during, before, and after a 60-min exercise session at 65% V̇o2max on three randomized visits: euglycemia-low insulin, euglycemia-high insulin, and hyperglycemia-low insulin. We tested a set of models, all sharing a single-compartment description of glucose kinetics, but differing in how exercise is assumed to modulate glucose disposal. Model selection was based on parsimony criteria. The best model assumed an exercise-induced immediate effect on IIRd and a delayed effect on IDRd. It predicted that exercise increases IIRd, compared with rest, by 66%-82% and 67%-97% in T1D and ND, respectively, not significantly different between the two groups. Conversely, the exercise effect on IDRd ranged between 81% and 155% in T1D and it was significantly higher than ND, which ranged between 10% and 40%. The exaggerated effect observed in IDRd can explain the higher hypoglycemia risk related to individuals with T1D. This novel exercise model could help in informing safe and effective glucose management during and after exercise in individuals with T1D.NEW & NOTEWORTHY Here, we present a new mathematical model describing the effect of moderate physical activity on insulin-mediated and noninsulin-mediated glucose disposal in subjects with and without diabetes. We believe that this represents a step-forward in the knowledge of type 1 diabetes pathophysiology, and an useful tool to design safe and effective insulin-therapies.

Improved postprandial glucose metabolism in type 2 diabetes by the dual glucagon-like peptide-1/glucagon receptor agonist SAR425899 in comparison with liraglutide.

AIM: To gain further insights into the efficacy of SAR425899, a dual glucagon-like peptide-1/glucagon receptor agonist, by providing direct comparison with the glucagon-like peptide-1 receptor agonist, liraglutide, in terms of key outcomes of glucose metabolism. RESEARCH DESIGN AND METHODS: Seventy overweight to obese subjects with type 2 diabetes (T2D) were randomized to receive once-daily subcutaneous administrations of SAR425899 (0.12, 0.16 or 0.20 mg), liraglutide (1.80 mg) or placebo for 26 weeks. Mixed meal tolerance tests were conducted at baseline (BSL) and at the end of treatment (EOT). Metabolic indices of insulin action and secretion were assessed via Homeostasis Model Assessment (HOMA2) and oral minimal model (OMM) methods. RESULTS: From BSL to EOT (median [25th, 75th] percentile), HOMA2 quantified a significant improvement in basal insulin action in liraglutide (35% [21%, 74%]), while secretion enhanced both in SAR425899 (125% [63%, 228%]) and liraglutide (73% [43%, 147%]). OMM quantified, both in SAR425899 and liraglutide, a significant improvement in insulin sensitivity (203% [58%, 440%] and 36% [21%, 197%]), basal beta-cell responsiveness (67% [34%, 112%] and 40% [16%, 59%]), and above-basal beta-cell responsiveness (139% [64%, 261%] and 69% [-15%, 120%]). A significant delay in glucose absorption was highlighted in SAR425899 (37% [52%,18%]). CONCLUSIONS: SAR425899 and liraglutide improved postprandial glucose control in overweight to obese subjects with T2D. A significantly higher enhancement in beta-cell function was shown by SAR425899 than liraglutide.

Modeling Between-Subject Variability in Subcutaneous Absorption of a Fast-Acting Insulin Analogue by a Nonlinear Mixed Effects Approach.

Despite the great progress made in insulin preparation and titration, many patients with diabetes are still experiencing dangerous fluctuations in their blood glucose levels. This is mainly due to the large between- and within-subject variability, which considerably hampers insulin therapy, leading to defective dosing and timing of the administration process. In this work, we present a nonlinear mixed effects model describing the between-subject variability observed in the subcutaneous absorption of fast-acting insulin. A set of 14 different models was identified on a large and frequently-sampled database of lispro pharmacokinetic data, collected from 116 subjects with type 1 diabetes. The tested models were compared, and the best one was selected on the basis of the ability to fit the data, the precision of the estimated parameters, and parsimony criteria. The selected model was able to accurately describe the typical trend of plasma insulin kinetics, as well as the between-subject variability present in the absorption process, which was found to be related to the subject's body mass index. The model provided a deeper understanding of the insulin absorption process and can be incorporated into simulation platforms to test and develop new open- and closed-loop treatment strategies, allowing a step forward toward personalized insulin therapy.

Model-Based Assessment of C-Peptide Secretion and Kinetics in Post Gastric Bypass Individuals Experiencing Postprandial Hyperinsulinemic Hypoglycemia.

Assessment of insulin secretion is key to diagnose postprandial hyperinsulinemic hypoglycemia (PHH), an increasingly recognized complication following bariatric surgery. To this end, the Oral C-peptide Minimal Model (OCMM) can be used. This usually requires fixing C-peptide (CP) kinetics to the ones derived from the Van Cauter population model (VCPM), which has never been validated in PHH individuals. The objective of this work was to test the validity of the OCMM coupled with the VCPM in PHH subjects and propose a method to overcome the observed limitations. Two cohorts of adults with PHH after gastric bypass (GB) underwent either a 75 g oral glucose (9F/3M; age=42±9 y; BMI=28.3±6.9 kg/m2) or a 60 g mixed-meal (7F/3M; age = 43 ± 11 y; BMI=27.5±4.2 kg/m2) tolerance test. The OCMM was identified on CP concentration data with CP kinetics fixed to VCPM (VC approach). In both groups, the VC approach underestimated CP-peak and overestimated CP-tail suggesting CP kinetics predicted by VCPM to be inaccurate in this population. Thus, the OCMM was identified using CP kinetics estimated from the data (DB approach) using a Bayesian Maximum a Posteriori estimator. CP data were well predicted in all the subjects using the DB approach, highlighting a significantly faster CP kinetics in patients with PHH compared to the one predicted by VCPM. Finally, a simulation study was used to validate the proposed approach. The present findings question the applicability of the VCPM in patients with PHH after GB and call for CP bolus experiments to develop a reliable CP kinetic model in this population.

In Silico Cloning of Target Type 2 Diabetes Population for Treatments Development and Decision Support.

Therapies for treatment of type 2 diabetes (T2D) involve a variety of medications, depending on the stage of T2D progression. It is now an accepted knowledge that in silico trials can help to accelerate drug development and support treatment optimization. A T2D simulator (T2DS), consisting of a model of the glucose-insulin system and an in silico population describing glucose-insulin dynamics in T2D subjects, has been recently developed based on early-stage T2D data, studied with sophisticated experimental techniques. This limits the domain of validity of the simulator to this specific sub-population of T2D. Here we proposed a method for tuning the T2DS to any desired T2D target population, e.g. insulin-naïve (i.e., not experienced with insulin) patients, without the need to resort to complex and expensive clinical studies. This will allow to use the T2DS for testing treatments in the target population. To illustrate the methodology, we used a case study: extending the T2DS to reproduce the behavior of insulin-naïve T2D subjects. The methodology described here can be extended to other stages of T2D, allowing an extensive in silico testing phase of different treatments before human trials.

In Silico Head-to-Head Comparison of Insulin Glargine 300 U/mL and Insulin Degludec 100 U/mL in Type 1 Diabetes.

Background: Second-generation long-acting insulin glargine 300 U/mL (Gla-300) and degludec 100 U/mL (Deg-100) provide novel basal insulin therapies for the treatment of type 1 diabetes (T1D). Both offer a flatter pharmacokinetic (PK) profile than the previous generation of long-acting insulins, thus improving glycemic control while reducing hypoglycemic events. This work describes an in silico head-to-head comparison of the two basal insulins on 24-h glucose profiles and was used to guide the design of a clinical trial. Materials and Methods: The Universities of Virginia (UVA)/Padova T1D simulator describes the intra-/interday variability of glucose-insulin dynamics and thus provides a robust bench-test for assessing glucose control for basal insulin therapies. A PK model describing subcutaneous absorption of Deg-100, in addition to the one already available for Gla-300, has been developed based on T1D clinical data and incorporated into the simulator. One hundred in silico T1D subjects received a basal insulin dose (Gla-300 or Deg-100) for 12 weeks (8 weeks uptitration, 4 weeks stable dosing) by morning or evening administration in a basal/bolus regimen. The virtual patients were uptitrated to their individual doses with two different titration rules. Results: The last 2-week simulated continuous glucose monitoring data were used to calculate various outcome metrics for both basal insulin treatments, with primary outcome being the percent time in glucose target (70-140 mg/dL). The simulations show no statistically significant difference for Gla-300 versus Deg-100 in the main endpoints. Conclusions: This work suggests comparable glucose control using either Gla-300 or Deg-100 and was used to guide the design of a clinical trial intended to compare second-generation long-acting insulin analogues.

Dual glucagon-like peptide-1 receptor/glucagon receptor agonist SAR425899 improves beta-cell function in type 2 diabetes.

AIM: To evaluate the change in insulin sensitivity, ß-cell function and glucose absorption after 28 days of treatment with high and low doses of SAR425899, a novel dual glucagon-like peptide-1 receptor/glucagon receptor agonist, versus placebo. MATERIALS AND METHODS: Thirty-six overweight to obese subjects with type 2 diabetes were randomized to receive daily subcutaneous administrations of low-dose SAR425899 (0.03, 0.06 and 0.09 mg) and high-dose SAR425899 (0.06, 0.12 and 0.18 mg) or placebo for 28 days; dose escalation occurred after days 7 and 14. Mixed meal tolerance tests were conducted before treatment (day -1) and on days 1 and 28. Oral glucose and C-peptide minimal models were used to quantify metabolic indices of insulin sensitivity, ß-cell responsiveness and glucose absorption. RESULTS: With low-dose SAR425899, high-dose SAR425899 and placebo, ß-cell function from day -1 to day 28 increased by 163%, 95% and 23%, respectively. The change in area under the curve for the rate of meal glucose appearance between 0 and 120 minutes was -32%, -20% and 8%, respectively. CONCLUSIONS: After 28 days of treatment, SAR425899 improved postprandial glucose control by significantly enhancing ß-cell function and slowing glucose absorption rate.

Modeling Subcutaneous Absorption of Long-Acting Insulin Glargine in Type 1 Diabetes.

OBJECTIVE: Subcutaneous (sc) administration of long-acting insulin analogs is often employed in multiple daily injection (MDI) therapy of type 1 diabetes (T1D) to cover patient's basal insulin needs. Among these, insulin glargine 100 U/mL (Gla-100) and 300 U/mL (Gla-300) are formulations indicated for once daily sc administration in MDI therapy of T1D. A few semi-mechanistic models of sc absorption of insulin glargine have been proposed in the literature, but were not quantitatively assessed on a large dataset. The aim of this paper is to propose a model of sc absorption of insulin glargine able to describe the data and provide precise model parameters estimates with a clear physiological interpretation. METHODS: Three candidate models were identified on a total of 47 and 77 insulin profiles of T1D subjects receiving a single or repeated sc administration of Gla-100 or Gla-300, respectively. Model comparison and selection were performed on the basis of their ability to describe the data and numerical identifiability. RESULTS: The most parsimonious model is linear two-compartment and accounts for the insulin distribution between the two compartments after sc administration through parameter k. Between the two formulations, we report a lower fraction of insulin in the first versus second compartment (k = 86% versus 94% in Gla-100 versus Gla-300, p < 0.05), a lower dissolution rate from the first to the second compartment ([Formula: see text] versus 0.0008 min-1 in Gla-100 versus Gla-300, p << 0.001), and a similar rate of insulin absorption from the second compartment to plasma ([Formula: see text] versus 0.0016 min-1 in Gla-100 versus Gla-300, p = NS), in accordance with the mechanisms of insulin glargine protraction. CONCLUSIONS: The proposed model is able to both accurately describe plasma insulin data after sc administration and precisely estimate physiologically plausible parameters. SIGNIFICANCE: The model can be incorporated in simulation platforms potentially usable for optimizing basal insulin treatment strategies.

A novel natural tracer method to measure complex carbohydrate metabolism.

While the triple tracer isotope dilution method has enabled accurate estimation of carbohydrate turnover after a mixed meal, use of the simple carbohydrate glucose as the carbohydrate source limits its translational applicability to everyday meals that typically contain complex carbohydrates. Hence, utilizing the natural enrichment of [13C]polysaccharide in commercially available grains, we devised a novel tracer method to measure postprandial complex carbohydrate turnover and indices of insulin action and ß-cell function and compared the parameters to those obtained after a simple carbohydrate containing mixed meal. We studied healthy volunteers after either rice (n = 8) or sorghum (n = 8) and glucose (n = 16) containing mixed meals and modified the triple tracer technique to calculate carbohydrate turnover. All meals were matched for calories and macronutrient composition. Rates of meal glucose appearance (2,658 ± 736 vs. 4,487 ± 909 µM·kg-1·2 h-1), endogenous glucose production (-835 ± 283 vs. -1,123 ± 323 µM·kg-1·2 h-1) and glucose disappearance (1,829 ± 807 vs. 3,606 ± 839 µM·kg-1·2 h-1) differed (P < 0.01) between complex and simple carbohydrate containing meals, respectively. Interestingly, there were significant increase in indices of insulin sensitivity (32.5 ± 3.5 vs. 25.6 ± 3.2 10-5 (dl·kg-1·min-2)/pM, P = 0.006) and ß-cell responsivity (disposition index: 1,817 ± 234 vs. 1,236 ± 159 10-14 (dl·kg-1·min-2)/pM, P < 0.005) with complex than simple carbohydrate meals. We present a novel triple tracer approach to estimate postprandial turnover of complex carbohydrate containing mixed meals. We also report higher insulin sensitivity and ß-cell responsivity with complex than with simple carbohydrates in mixed meals of identical calorie and macronutrient compositions in healthy adults.

Incorporating Long-Acting Insulin Glargine Into the UVA/Padova Type 1 Diabetes Simulator for In Silico Testing of MDI Therapies.

OBJECTIVE: Glargine 100 U/mL (Gla-100) and 300 U/mL (Gla-300) are long-acting insulin analogs providing basal insulin supply in multiple daily injection (MDI) therapy of type 1 diabetes (T1D). Both insulins require extensive testing to arrive at the optimal dosing regimen, e.g., timing and amount. Here we aim at a simulation tool for evaluating benefits/risks of different dosing schemes and up-titration rules for both Gla-100 and Gla-300 before clinical testing. METHODS: A new pharmacokinetic (PK) model of both Gla-100 and Gla-300 was incorporated into the FDA-accepted University of Virginia/Padova T1D simulator: Specifically, a joint parameter distribution, built from PK parameter estimates, was used to generate individual PK parametrizations for each in silico subject. A virtual trial comparing Gla-100 vs. Gla-300 was performed and assessed against a clinical study to validate the glargine simulator. RESULTS: Like in vivo, in silico both insulins performed similarly with respect to glucose control: percent time of glucose between [80-140] mg/dL with Gla-100 vs. Gla-300 (primary endpoint) were 41.5 ± 1.1% vs. 39.0 ± 1.2% (P = 0.11) in silico, 31.0 ± 1.6% vs. 31.8 ± 1.5% (P = 0.73) in vivo. CONCLUSIONS: The glargine simulator reproduced the main findings of the clinical trial, proving its validity for testing MDI therapies. SIGNIFICANCE: In silico testing of MDI therapies can help designing clinical trials. Due to the more standardized settings in silico (e.g., standardized meals and strict adherence to titration rule), any potential treatment effect is reaching statistical significance in simulation vs. clinical trial.