Cargando…
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...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6624389/ https://www.ncbi.nlm.nih.gov/pubmed/31026084 http://dx.doi.org/10.1111/bcp.13972 |
Sumario: | 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. |
---|