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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...

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Autores principales: Saito, Masako, Kaibara, Atsunori, Kadokura, Takeshi, Toyoshima, Junko, Yoshida, Satoshi, Kazuta, Kenichi, Ueyama, Eiji
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
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author Saito, Masako
Kaibara, Atsunori
Kadokura, Takeshi
Toyoshima, Junko
Yoshida, Satoshi
Kazuta, Kenichi
Ueyama, Eiji
author_facet Saito, Masako
Kaibara, Atsunori
Kadokura, Takeshi
Toyoshima, Junko
Yoshida, Satoshi
Kazuta, Kenichi
Ueyama, Eiji
author_sort Saito, Masako
collection PubMed
description 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.
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spelling pubmed-66243892019-07-17 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 Saito, Masako Kaibara, Atsunori Kadokura, Takeshi Toyoshima, Junko Yoshida, Satoshi Kazuta, Kenichi Ueyama, Eiji Br J Clin Pharmacol Original Articles 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. John Wiley and Sons Inc. 2019-06-20 2019-08 /pmc/articles/PMC6624389/ /pubmed/31026084 http://dx.doi.org/10.1111/bcp.13972 Text en © 2019 Astellas Pharma Inc. British Journal of Clinical Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Original Articles
Saito, Masako
Kaibara, Atsunori
Kadokura, Takeshi
Toyoshima, Junko
Yoshida, Satoshi
Kazuta, Kenichi
Ueyama, Eiji
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
title 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_short 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
title_sort 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
topic Original Articles
url 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
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