A previous semi‐mechanistic model described changes in fasting serum insulin (FSI), fasting plasma glucose (FPG), and glycated hemoglobin (HbA1c) in patients with type 2 diabetic mellitus (T2DM) by modeling insulin sensitivity and β‐cell function. It was later suggested that change in body weight could affect insulin sensitivity, which this study evaluated in a population model to describe the disease progression of T2DM. Nonlinear mixed effects modeling was performed on data from 181 obese patients with newly diagnosed T2DM managed with diet and exercise for 67 weeks. Baseline β‐cell function and insulin sensitivity were 61% and 25% of normal, respectively. Management with diet and exercise (mean change in body weight = −4.1 kg) was associated with an increase of insulin sensitivity (30.1%) at the end of the study. Changes in insulin sensitivity were associated with a decrease of FPG (range, 7.8–7.3 mmol/L) and HbA1c (6.7–6.4%). Weight change as an effector on insulin sensitivity was successfully evaluated in a semi‐mechanistic population model.

The raised lysophosphatidylcholine level in oxidatively modified LDL was related to the ability of the LDL to impair endothelium dependent relaxation. However, lipid peroxidation products assessed by TBARS did not relate to the phospholipid changes in LDL and therefore cannot be used to predict the vascular effects of LDL after oxidative modification.

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.

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 β-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.

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.