The variability in beta-cell function in placebo-treated subjects with type 2 diabetes: application of the weight-HbA1c-insulin-glucose (WHIG) model.

AIM: The weight-glycosylated haemoglobin (HbA1C)-insulin-glucose (WHIG) model describes the effects of changes in weight on insulin sensitivity (IS) in newly diagnosed, obese subjects receiving placebo treatment. This model was applied to a wider population of placebo-treated subjects, to investigate factors influencing the variability in IS and ß-cell function. METHODS: The WHIG model was applied to the WHIG dataset (Study 1) and two other placebo datasets (Studies 2 and 3). Studies 2 and 3 consisted of nonobese subjects and subjects with advanced type 2 diabetes mellitus (T2DM). Body weight, fasting serum insulin (FSI), fasting plasma glucose (FPG) and HbA1c were used for nonlinear mixed-effects modelling (using NONMEM v7.2 software). Sources of interstudy variability (ISV) and potential covariates (age, gender, diabetes duration, ethnicity, compliance) were investigated. RESULTS: An ISV for baseline parameters (body weight and ß-cell function) was required. The baseline ß-cell function was significantly lower in subjects with advanced T2DM (median difference: Study 2: 15.6%, P < 0.001; Study 3: 22.7%, P < 0.001) than in subjects with newly diagnosed T2DM (Study 1). A reduction in the estimated insulin secretory response in subjects with advanced T2DM was observed but diabetes duration was not a significant covariate. CONCLUSION: The WHIG model can be used to describe the changes in weight, IS and ß-cell function in the diabetic population. IS remained relatively stable between subjects but a large ISV in ß-cell function was observed. There was a trend towards decreasing ß-cell responsiveness with diabetes duration, and further studies, incorporating subjects with a longer history of diabetes, are required.

Modeling the Disease Progression from Healthy to Overt Diabetes in ZDSD Rats.

Studying the critical transitional phase between healthy to overtly diabetic in type 2 diabetes mellitus (T2DM) is of interest, but acquiring such clinical data is impractical due to ethical concerns and would require a long study duration. A population model using Zucker diabetic Sprague-Dawley (ZDSD) rats was developed to describe this transition through altering insulin sensitivity (IS, %) as a result of accumulating excess body weight and ß-cell function (BCF, %) to affect glucose-insulin homeostasis. Body weight, fasting plasma glucose (FPG), and fasting serum insulin (FSI) were collected biweekly over 24 weeks from ZDSD rats (n = 23) starting at age 7 weeks. A semi-mechanistic model previously developed with clinical data was adapted to rat data with BCF and IS estimated relative to humans. Non-linear mixed-effect model estimation was performed using NONMEM. Baseline IS and BCF were 41% compared to healthy humans. BCF was described with a non-linear rise which peaked at 14 weeks before gradually declining to a negligible level. A component for excess growth reflecting obesity was used to affect IS, and a glucose-dependent renal effect exerted a two- to sixfold increase on the elimination of glucose. A glucose-dependent weight loss effect towards the end of experiment was implemented. A semi-mechanistic model to describe the dynamics of glucose and insulin was successfully developed for a rat population, transitioning from healthy to advanced diabetes. It is also shown that weight loss can be modeled to mimic the glucotoxicity phenomenon seen in advanced hyperglycemia.

Identification of the primary mechanism of action of an insulin secretagogue from meal test data in healthy volunteers based on an integrated glucose-insulin model.

The integrated glucose-insulin (IGI) model is a previously developed semi-mechanistic model that incorporates control mechanisms for the regulation of glucose production, insulin secretion, and glucose uptake. It has been shown to adequately describe insulin and glucose profiles in both type 2 diabetics and healthy volunteers following various glucose tolerance tests. The aim of this study was to investigate the ability of the IGI model to correctly identify the primary mechanism of action of glibenclamide (Gb), based on meal tolerance test (MTT) data in healthy volunteers. IGI models with different mechanism of drug action were applied to data from eight healthy volunteers participating in a randomized crossover study with five single-dose tests (placebo and four drug arms). The study participants were given 3.5 mg of Gb, intravenously or orally, or 3.5 mg of the two main metabolites M1 and M2 intravenously, 0.5 h prior to a standardized breakfast with energy content of 1800 kJ. Simultaneous analysis of all data by nonlinear mixed effect modeling was performed using NONMEM(®). Drug effects that increased insulin secretion resulted in the best model fit, thus identifying the primary mechanism of action of Gb and metabolites as insulin secretagogues. The model also quantified the combined effect of Gb, M1 and M2 to have a fourfold maximal increase on endogenous insulin secretion, with an EC(50) of 169.1 ng mL(-1) for Gb, 151.4 ng mL(-1) for M1 and 267.1 ng mL(-1) for M2. The semi-mechanistic IGI model was successfully applied to MTT data and identified the primary mechanism of action for Gb, quantifying its effects on glucose and insulin time profiles.

A combined pharmacokinetic model for the hypoxia-targeted prodrug PR-104A in humans, dogs, rats and mice predicts species differences in clearance and toxicity.

BACKGROUND: PR-104 is a phosphate ester that is systemically converted to the corresponding alcohol PR-104A. The latter is activated by nitroreduction in tumours to cytotoxic DNA cross-linking metabolites. Here, we report a population pharmacokinetic (PK) model for PR-104 and PR-104A in non-human species and in humans. METHODS: A compartmental model was used to fit plasma PR-104 and PR-104A concentration-time data after intravenous (i.v.) dosing of humans, Beagle dogs, Sprague-Dawley rats and CD-1 nude mice. Intraperitoneal (i.p.) PR-104 and i.v. PR-104A dosing of mice was also investigated. Protein binding was measured in plasma from each species. Unbound drug clearances and volumes were scaled allometrically. RESULTS: A two-compartment model described the disposition of PR-104 and PR-104A in all four species. PR-104 was cleared rapidly by first-order (mice, rats, dogs) or mixed-order (humans) metabolism to PR-104A in the central compartment. The estimated unbound human clearance of PR104A was 211 L/h/70 kg, with a steady state unbound volume of 105 L/70 kg. The size equivalent unbound PR-104A clearance was 2.5 times faster in dogs, 0.78 times slower in rats and 0.63 times slower in mice, which may reflect reported species differences in PR-104A O-glucuronidation. CONCLUSIONS: The PK model demonstrates faster size equivalent clearance of PR-104A in dogs and humans than rodents. Dose-limiting myelotoxicity restricts the exposure of PR-104A in humans to approximately 25% of that achievable in mice.