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

Article date: August 2019

By: Masako Saito, Atsunori Kaibara, Takeshi Kadokura, Junko Toyoshima, Satoshi Yoshida, Kenichi Kazuta, Eiji Ueyama in Volume 85, Issue 8, pages 1808-1819


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.


A PK/PD model for the change from baseline in UGE for 24 hours (ΔUGE24h) with area under the concentration–time curve from time of dosing to 24 h after administration (AUC24h) 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.


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 AUC24h and ΔUGE24h were 5417 (3229–8775) ng·h/mL and 85 (51–145) g, respectively. The simulation also suggested a 1.17‐fold increase in AUC24h of ipragliflozin and a 0.76‐fold in ΔUGE24h in T2DM patients with moderate renal impairment compared to those with normal renal function.


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

DOI: 10.1111/bcp.13972

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