Pharmacokinetic and pharmacodynamic modelling for renal function dependent urinary glucose excretion effect of ipragliflozin, a selective sodium-glucose cotransporter 2 inhibitor, both in healthy subjects and patients with type 2 diabetes mellitus

Effects of an SGLT Inhibitor on the Production, Toxicity, and Elimination of Gut-Derived Uremic Toxins: A Call for Additional Evidence

Sodium–glucose cotransporter (SGLT) inhibitors are a class of oral hypoglycemic agents, which, in recent years, have been shown to improve renal and cardiovascular outcomes in patients with diabetic and non-diabetic chronic kidney disease. There remains considerable debate regarding the potential glucose-independent mechanisms by which these benefits are conferred. SGLT inhibitors, to a variable extent, impair small intestinal glucose absorption, facilitating the delivery of glucose into the colon. This suppresses protein fermentation, and thus the generation of uremic toxins such as phenols and indoles. It is acknowledged that such a shift in gut microbial metabolism yields health benefits for the host. SGLT inhibition, in addition, may be hypothesized to foster the renal clearance of protein-bound uremic toxins. Altered generation and elimination of uremic toxins may be in the causal pathway between SGLT inhibition and improved cardiometabolic health. Present review calls for additional research.

Pharmacokinetic/Pharmacodynamic Properties and Clinical Use of SGLT2 Inhibitors in Non-Asian and Asian Patients with Type 2 Diabetes and Chronic Kidney Disease

Chronic kidney disease is a prevalent complication of type 2 diabetes mellitus (T2DM). Sodium-glucose cotransporter type 2 inhibitors (SGLT2is) have a unique mode of action targeting the kidney. As their glucose-lowering potency declines with the reduction in estimated glomerular filtration rate, their clinical use in patients with T2DM with chronic kidney disease has been submitted to restriction. However, recent observations demonstrated that SGLT2is reduce the progression of renal impairment in patients with mild-to-moderate chronic kidney disease, with or without albuminuria. Furthermore, SGLT2is reduce the incidence of cardiovascular events in patients with T2DM at high cardiovascular risk, independently of baseline estimated glomerular filtration rate. Thus, recent guidelines recommend the prescription of SGLT2is in patients with T2DM with mild-to-moderate chronic kidney disease defined by an estimated glomerular filtration rate between ≥ 30 and < 90 mL/min/1.73 m² and/or albuminuria. The present comprehensive review describes the pharmacokinetic/pharmacodynamic properties of SGLT2is commercialised worldwide and in Japan in patients with T2DM with mild, moderate and severe chronic kidney disease. Drug exposure increases when the estimated glomerular filtration rate declines but without a clear-cut relationship with the severity of chronic kidney disease and in a rather moderate amplitude that most often does not require a dose reduction in the presence of mild-to-moderate chronic kidney disease. The urinary glucose excretion steadily declines with the reduction in estimated glomerular filtration rate. This may explain a lower effect on glucose control, yet the positive effects on body weight and blood pressure still remain. The efficacy and safety of these SGLT2is are analysed among patients with stages 3a and 3b chronic kidney disease in placebo-controlled randomised clinical trials, with almost similar results in Asian and non-Asian individuals with T2DM. In summary, there is no reason not to prescribe SGLT2is in patients with T2DM with mild-to-moderate chronic kidney disease, especially if the aim is to benefit from cardiovascular and/or renal protection.

Profile of Ipragliflozin, an Oral SGLT-2 Inhibitor for the Treatment of Type 2 Diabetes: The Evidence to Date

Background

Sodium-glucose cotransporter-2 (SGLT-2) inhibitors are a novel class of pharmacotherapeutics for type 2 diabetes management that work by reducing renal reabsorption of glucose. Ipragliflozin is a potent, selective SGLT-2 inhibitor used for the management of type 2 diabetes.

Objective

The primary aim of this review is to summarize the available evidence on the efficacy and safety of ipragliflozin for the management of type 2 diabetes. We also review the discovery, pharmacokinetic, and pharmacodynamic profile of ipragliflozin.

Methods

To inform our review, we searched MEDLINE, International Pharmaceutical Abstracts, and Embase to identify relevant papers to ipragliflozin use in type 2 diabetes. Clinical trial registries were also searched.

Results

Findings from randomized clinical trials demonstrate that compared to placebo, ipragliflozin significantly reduces glucose as measured via Hemoglobin A1c and fasting plasma glucose levels. Ipragliflozin is also associated with weight reduction and an improvement in some, but not all, cardiovascular risk markers. Ipragliflozin has a favourable safety profile with a low risk of hypoglycemia and the rates of common adverse events are not significantly different than placebo. Limited data are available to assess rare and long-term adverse effects.

Conclusion

Current evidence shows that ipragliflozin is an effective therapeutic option for the management of glucose control in type 2 diabetes. However, no cardiovascular outcome trials have been conducted to date. Real-world observational studies are still needed to accurately capture any possible rare or long-term adverse events.

Comparison of the Pharmacokinetic and Pharmacodynamic Relationship of Ipragliflozin Between Patients With Type 1 and Type 2 Diabetes Mellitus

PURPOSE

To characterize the pharmacokinetic and pharmacodynamic (PK/PD) relationship of ipragliflozin in Japanese patients with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) and to determine the appropriate dose regimen for a Phase III study of ipragliflozin in Japanese patients with T1DM.

METHODS

The PK (AUC_24h of plasma ipragliflozin) and PD (renal glucose clearance) properties in patients with T1DM and T2DM were assessed in 2 independent clinical pharmacologic studies of ipragliflozin. The same maximum efficacy (E_max) model described the PK/PD relationship in patients with T1DM and T2DM. Changes in fasting plasma glucose (FPG) in T1DM patients were simulated by applying a previously established FPG model for ipragliflozin in patients with T2DM.

FINDINGS

Data from 42 patients with T1DM and 28 patients with T2DM were used. Comparable AUC_24h of plasma ipragliflozin and similar dose dependency were observed on day 14 between patients with T1DM and those with T2DM. Decreases in renal glucose clearance were comparable regardless of the ipragliflozin dose in both groups of patients. The estimated mean E_max and AUC_24h producing 50% of E_max (EX₅₀) were 45.1 mL/min (95% CI, 37.0-53.2 mL/min) and 2160 ng·h/mL (95% CI, 929-3390 ng·h/mL), respectively, in all patients with T1DM and T2DM. Observed FPG in patients with T1DM was reproduced well by the simulation from the previously established FPG model.

IMPLICATIONS

The PK/PD properties for ipragliflozin were comparable between patients with T1DM and T2DM, suggesting no substantial difference in PK/PD relationships in both patient populations. The dose regimen used for patients with T2DM was also recommended for a Phase III study in Japanese patients with T1DM. ClinicalTrials.gov identifiers: NCT01023945 and NCT02529449.

Prior information for population pharmacokinetic and pharmacokinetic/pharmacodynamic analysis: overview and guidance with a focus on the NONMEM PRIOR subroutine

Abstract

Population pharmacokinetic analysis is used to estimate pharmacokinetic parameters and their variability from concentration data. Due to data sparseness issues, available datasets often do not allow the estimation of all parameters of the suitable model. The PRIOR subroutine in NONMEM supports the estimation of some or all parameters with values from previous models, as an alternative to fixing them or adding data to the dataset. From a literature review, the best practices were compiled to provide a practical guidance for the use of the PRIOR subroutine in NONMEM. Thirty-three articles reported the use of the PRIOR subroutine in NONMEM, mostly in special populations. This approach allowed fast, stable and satisfying modelling. The guidance provides general advice on how to select the most appropriate reference model when there are several previous models available, and to implement and weight the selected parameter values in the PRIOR function. On the model built with PRIOR, the similarity of estimates with the ones of the reference model and the sensitivity of the model to the PRIOR values should be checked. Covariates could be implemented a priori (from the reference model) or a posteriori, only on parameters estimated without prior (search for new covariates).

Graphic abstract

Electronic supplementary material

The online version of this article (10.1007/s10928-020-09695-z) contains supplementary material, which is available to authorized users.

Model-based Prediction of the Long-term Glucose-Lowering Effects of Ipragliflozin, a Selective Sodium-Glucose Cotransporter 2 (SGLT2) Inhibitor, in Patients with Type 2 Diabetes Mellitus

INTRODUCTION

Sodium-dependent glucose cotransporter 2 (SGLT2) inhibitors inhibit the reabsorption of glucose from the kidneys and increase urinary glucose excretion (UGE), thereby lowering the blood glucose concentration in people suffering from type 1 and type 2 diabetes mellitus (T2DM). In a previous study, we reported a pharmacokinetics/pharmacodynamics model to estimate individual change in UGE (ΔUGE), which is a direct pharmacological effect of SGLT2 inhibitors. In this study, we report our enhancement of the previous model to predict the long-term effects of ipragliflozin on clinical outcomes in patients with T2DM.

METHODS

The time course of fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) in patients with T2DM following ipragliflozin treatment that had been observed in earlier clinical trials was modeled using empirical models combined with the maximum drug effect (E_max) model and disease progression model. As a predictive factor of drug effect, estimated ΔUGE was introduced into the E_max model, instead of ipragliflozin exposure. The developed models were used to simulate the time course of FPG and HbA1c following once-daily treatment with placebo or ipragliflozin at doses of 12.5, 25, 50 and 100 mg, and the changes at 52 weeks at the approved dose of 50 mg were summarized by renal function category.

RESULTS

The developed models that included UGE as a dependent variable of response were found to well describe observed time courses in FPG and HbA1c. Baseline blood glucose level and renal function had significant effects on the glucose-lowering effect of ipragliflozin, and these models enabled quantification of these impacts on clinical outcomes. Simulated median changes in HbA1c in T2DM patients with mild and moderate renal impairment were 25 and 63% lower, respectively, than those in T2DM patients with normal renal function. These results are consistent with the observed clinical data from a previous renal impairment study.

CONCLUSIONS

Empirical models established based on the effect of UGE well predicted the renal function-dependent long-term glucose-lowering effects of ipragliflozin in patients with T2DM.

Pharmacokinetic and pharmacodynamic modelling for renal function dependent urinary glucose excretion effect of ipragliflozin, a selective sodium-glucose cotransporter 2 inhibitor, both in healthy subjects and patients with type 2 diabetes mellitus

AIMS

To provide a model-based prediction of individual urinary glucose excretion (UGE) effect of ipragliflozin, we constructed a pharmacokinetic/pharmacodynamic (PK/PD) model and a population PK model using pooled data of clinical studies.

METHODS

A PK/PD model for the change from baseline in UGE for 24 hours (ΔUGE_24h ) with area under the concentration-time curve from time of dosing to 24 h after administration (AUC_24h ) of ipragliflozin was described by a maximum effect model. A population PK model was also constructed using rich PK sampling data obtained from 2 clinical pharmacology studies and sparse data from 4 late-phase studies by the NONMEM $PRIOR subroutine. Finally, we simulated how the PK/PD of ipragliflozin changes in response to dose regime as well as patients' renal function using the developed model.

RESULTS

The estimated individual maximum effect were dependent on fasting plasma glucose and renal function, except in patients who had significant UGE before treatment. The PK of ipragliflozin in type 2 diabetes mellitus (T2DM) patients was accurately described by a 2-compartment model with first order absorption. The population mean oral clearance was 9.47 L/h and was increased in patients with higher glomerular filtration rates and body surface area. Simulation suggested that medians (95% prediction intervals) of AUC_24h and ΔUGE_24h were 5417 (3229-8775) ng·h/mL and 85 (51-145) g, respectively. The simulation also suggested a 1.17-fold increase in AUC_24h of ipragliflozin and a 0.76-fold in ΔUGE_24h in T2DM patients with moderate renal impairment compared to those with normal renal function.

CONCLUSIONS

The developed models described the clinical data well, and the simulation suggested mechanism-based weaker antidiabetic effect in T2DM patients with renal impairment.