A model-based approach to analyze the influence of UGT2B15 polymorphism driven pharmacokinetic differences on the pharmacodynamic response of the PPAR agonist sipoglitazar

The structural basis of conserved residue variant effect on enzyme activity of UGT2B15

UDP-glucuronosyltransferase 2B15 (UGT2B15) is a crucial phase II drug-metabolizing enzyme, which glucuronidates various compounds, including clinical drugs and hormones. Mutants might affect glucuronidation, leading to a disruption of drug metabolism in vivo and decrease of therapeutic effect. Here, we mainly analyzed two representative mutants, H401P and L446S, on UGT2B15 activity using glucuronidation assays, molecular dynamic (MD) simulation and X-ray diffraction methods. The enzyme activity of L446S obviously increased six-fold than the wild type, although the enzyme activities of P191L, T374A, and H401P were lost apparently. Furthermore, we used MD simulations to calculate the energy change in the catalytic process of H401P and L446S, and the results indicated the free binding energies of H401P mutant to oxazepam and UDPGA were -30.98 ± 1.00 kcal/mol and -36.42 ± 1.04 kcal/mol, respectively, increased obviously compared to wild type, suggesting the mutation on position 401 had a crucial effect on the catalysis. Moreover, the three-dimensional structure of UGT2B15 C-terminal domain L446S was determined through protein crystallography and X-ray diffraction technology and the results suggested that one more hydrogen bonding between S446 and K410 was formed in the S446 crystal structure, compared to the wild type. Isothermal titration calorimetry assay further revealed the K_d values of C-terminal domain of UGT2B15 harbored L446S towards the cofactor UDPGA was similar to the value of wild type. Above all, our results pointed out that H401P and L446S affected the enzyme activity by different mechanism. Our work provided a helpful mechanism for variance explained in the UGTs catalyzation process.

Efficacy of DPP-4 inhibitors, GLP-1 analogues, and SGLT2 inhibitors as add-ons to metformin monotherapy in T2DM patients: a model-based meta-analysis

AIMS

The aim of the present study was to quantitate the hypoglycaemic effects of dipeptidyl peptidase-4 inhibitors (DPP-4i), glucagon-like peptide-1 receptor agonists (GLP-1r) and sodium glucose cotransporter 2 inhibitors (SGLT2i) as add-on treatments to metformin monotherapy in patients with type 2 diabetes mellitus (T2DM) using a model-based meta-analysis (MBMA).

METHODS

A systematic literature search of public databases was conducted to develop models that describe the time courses of the fasting plasma glucose (FPG)- and haemoglobin A1c (HbA1c)-lowering effects of three antidiabetic classes using NONMEM 7.3.0.

RESULTS

Seventy-six publications were eligible for this study, and 873 FPG and 1086 HbA1c values were collected. We developed a physiological indirect response model that described the time courses of FPG and HbA1c and simulated reductions in these values 90 days after the initiation of add-on treatments. FPG and HbA1c reductions with once weekly exenatide, liraglutide and dulaglutide were greater than those with other drugs. Mean changes from baseline FPG and HbA1c with these drugs were as follows: exenatide (-22.5 and -16.6%), liraglutide (-22.1 and -16.3%), and dulaglutide (-19.3 and -14.3%). The hypoglycaemic effects of DPP-4i and SGLT2i were similar.

CONCLUSIONS

Once weekly exenatide, liraglutide and dulaglutide provided better hypoglycaemic effects among the antidiabetic drugs analysed. Long-acting GLP-1r appears to be more useful for T2DM patients inadequately controlled with metformin monotherapy.

Comparison of Power, Prognosis, and Extrapolation Properties of Four Population Pharmacodynamic Models of HbA1c for Type 2 Diabetes

Reusing published models saves time; time to be used for informing decisions in drug development. In antihyperglycemic drug development, several published HbA1c models are available but selecting the appropriate model for a particular purpose is challenging. This study aims at helping selection by investigating four HbA1c models, specifically the ability to identify drug effects (shape, site of action, and power) and simulation properties. All models could identify glucose effect nonlinearities, although for detecting the site of action, a mechanistic glucose model was needed. Power was highest for models using mean plasma glucose to drive HbA1c formation. Insulin contribution to power varied greatly depending on the drug target; it was beneficial only if the drug target was insulin secretion. All investigated models showed good simulation properties. However, extrapolation with the mechanistic model beyond 12 weeks resulted in drug effect overprediction. This investigation aids drug development in decisions regarding model choice if reusing published HbA1c models.

Genetics, genomics and personalized medicine in Type 2 diabetes: a perspective on the Arab region

Type 2 diabetes (T2D) is a wide-spread, chronic metabolic disorder, affecting millions of people worldwide. The epidemic of diabetes has placed a huge strain on public health, longevity and economy. T2D occurs as a result of both genetic and environmental factors and is heterogeneous in its presentation across individuals. This review gives an overview of the genetic variations identified by genome-wide association studies which predispose individuals to T2D and those which are responsible for variable drug response across patients, and the necessity to adopt a personalized approach to diabetes management. We also include a perspective on diabetes in Arabs, given the high incidence of T2D and consanguineous marriages, and the need to understand associated genetic components in this vulnerable population.

Evaluation of the long-term durability and glycemic control of fasting plasma glucose and glycosylated hemoglobin for pioglitazone in Japanese patients with type 2 diabetes

BACKGROUND

This study applied a pharmacodynamic model-based approach to evaluate the long-term durability and glycemic control of pioglitazone in comparison with other oral glucose-lowering drugs in Japanese type 2 diabetes mellitus (T2DM) patients.

SUBJECTS AND METHODS

Japanese T2DM patients were enrolled in a prospective, randomized, open-label, blinded-end point study and received pioglitazone with or without other oral glucose-lowering drugs (excluding another thiazolidinedione [TZD]) (n=293) or oral glucose-lowering drugs excluding TZD (n=294). Treatment was adjusted to achieve glycosylated hemoglobin (HbA1c) <6.9%, and samples for fasting plasma glucose (FPG) and HbA1c were collected over 2.5-4 years. A simultaneous cascading indirect response model structure was applied to describe the time course of FPG and HbA1c. HbA1c levels were described using both an FPG-dependent and an FPG-independent function. To account for titration, drug effects for both treatment groups were implemented using a time-dependent Emax model.

RESULTS

Pioglitazone was superior in both time to maximum effect and the magnitude of reduction achieved in FPG and HbA1c. A greater reduction in median FPG (-21 mg/dL vs. -9 mg/dL) was observed with pioglitazone (P<0.05). Maximum drug effect for FPG was predicted to occur earlier (11 months) for pioglitazone than for the control group (14 months). The simulated additional reduction in FPG and HbA1c achieved with pioglitazone was predicted to be maintained beyond the currently observed study duration.

CONCLUSIONS

Pioglitazone was found to result in improved glycemic control and durability compared with control treatment. This model-based approach enabled the quantification of differences in FPG and HbA1c for both treatment groups and simulation to evaluate longer-term durability on FPG and HbA1c.