Using a Mathematical Modeling To Simulate Pharmacokinetics and Urinary Glucose Excretion of Luseogliflozin and Explore the Role of SGLT1/2 in Renal Glucose Reabsorption

Abstract

(1) Purpose: To develop a mathematical model combining physiologically based pharmacokinetic and urinary glucose excretion (PBPK-UGE) to simultaneously predict pharmacokinetic (PK) and UGE changes of luseogliflozin (LUS) as well as to explore the role of sodium-glucose cotransporters (SGLT1 and SGLT2) in renal glucose reabsorption (RGR) in humans. (2) Methods: The PBPK-UGE model was built using physicochemical and biochemical properties, binding kinetics data, affinity to SGLTs for glucose, and physiological parameters of renal tubules. (3) Results: The simulations using this model clarified that SGLT1/2 contributed 15 and 85%, respectively, to RGR in the absence of LUS. However, in the presence of LUS, the contribution proportion of SGLT1 rose to 52–76% in healthy individuals and 55–83% in T2DM patients, and that of SGLT2 reduced to 24–48 and 17–45%, respectively. Furthermore, this model supported the underlying mechanism that only 23–40% inhibition of the total RGR with 5 mg of LUS is resulted from SGLT1’s compensatory effect and the reabsorption activity of unbound SGLT2. (4) Conclusion: This PBPK-UGE model can predict PK and UGE in healthy individuals and T2DM patients and can also analyze the contribution of SGLT1/2 to RGR with and without LUS.

Mechanistic Modeling of Empagliflozin: Predicting Pharmacokinetics, Urinary Glucose Excretion, and Investigating Compensatory Role of SGLT1 in Renal Glucose Reabsorption

“…The PBPK-UGE workflow in this study is primarily based on 2 published papers. 11,13 It involves the construction of a PBPK model and a UGE model. The model is developed using PK-Sim and MoBi software (Version 11.2, https://github.…”

“…A detailed summary of these modeling parameters can be found in Table 1. 11,13,[16][17][18][19][20][21] During the development of the PBPK model, the Weibull time was optimized, along with the shape parameter, to match the observed peak time in clinical PK profiles, representing absorption. The distribution method, K ki,p and fraction of plasma free concentration (f up ) are implicated in tissue distribution of EMP.…”

“…The predictive performance of the model was evaluated using fold error, with a commonly acceptable range of 0.5-2.0 for PK assessments and 1.5-fold for UGE evaluations. 11 Sensitivity Analysis A sensitivity analysis was performed to evaluate the impact of all modeling parameters in Table 1 on the AUC, C max , and UGE in patients with T2DM administered at 10 mg once daily. The impact of these parameters on the AUC, C max , and UGE was estimated by altering each parameter by ±20%.…”

“…Various hypotheses have been proposed to explain the differences between in vitro inhibition and in vivo observations for SGLT2 inhibitors, mainly including drug concentration in the kidney and potential compensation by SGLT1. 10,11 To date, there are only a few papers that have used quantitative pharmacology modeling to predict the effects of several SGLT2 inhibitors on urinary glucose excretion (UGE) in humans. [10][11][12][13][14][15] Additionally, 1 publication employed a physiologically based pharmacokinetic (PBPK) model to simulate the inhibition of SGLT1/2 by EMP.…”

“…10,11 To date, there are only a few papers that have used quantitative pharmacology modeling to predict the effects of several SGLT2 inhibitors on urinary glucose excretion (UGE) in humans. [10][11][12][13][14][15] Additionally, 1 publication employed a physiologically based pharmacokinetic (PBPK) model to simulate the inhibition of SGLT1/2 by EMP. 16 However, none of these studies specifically focused on quantitatively simulating the effect of EMP on UGE in humans.…”