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Population pharmacokinetic modeling of glibenclamide in poorly controlled South African type 2 diabetic subjects
AIM: The aim of this study was to describe the pharmacokinetics (PK) of glibenclamide in poorly controlled South African type 2 diabetic subjects using noncompartmental and model-based methods. METHODS: A total of 24 subjects with type 2 diabetes were administered increasing doses (0 mg/d, 2.5 mg/d,...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4948726/ https://www.ncbi.nlm.nih.gov/pubmed/27471411 http://dx.doi.org/10.2147/CPAA.S102676 |
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author | Rambiritch, Virendra Naidoo, Poobalan Maharaj, Breminand Pillai, Goonaseelan |
author_facet | Rambiritch, Virendra Naidoo, Poobalan Maharaj, Breminand Pillai, Goonaseelan |
author_sort | Rambiritch, Virendra |
collection | PubMed |
description | AIM: The aim of this study was to describe the pharmacokinetics (PK) of glibenclamide in poorly controlled South African type 2 diabetic subjects using noncompartmental and model-based methods. METHODS: A total of 24 subjects with type 2 diabetes were administered increasing doses (0 mg/d, 2.5 mg/d, 5 mg/d, 10 mg/d, and 20 mg/d) of glibenclamide daily at 2-week intervals. Plasma glibenclamide, glucose, and insulin determinations were performed. Blood sampling times were 0 minute, 30 minutes, 60 minutes, 90 minutes, and 120 minutes (post breakfast sampling) and 240 minutes, 270 minutes, 300 minutes, 330 minutes, 360 minutes, and 420 minutes (post lunch sampling) on days 14, 28, 42, 56, and 70 for doses of 0 mg, 2.5 mg, 5.0 mg, 10 mg, and 20 mg, respectively. Blood sampling was performed after the steady state was reached. A total of 24 individuals in the data set contributed to a total of 841 observation records. The PK was analyzed using noncompartmental analysis methods, which were implemented in WinNonLin(®), and population PK analysis using NONMEM(®). Glibenclamide concentration data were log transformed prior to fitting. RESULTS: A two-compartmental disposition model was selected after evaluating one-, two-, and three-compartmental models to describe the time course of glibenclamide plasma concentration data. The one-compartment model adequately described the data; however, the two-compartment model provided a better fit. The three-compartment model failed to achieve successful convergence. A more complex model, to account for enterohepatic recirculation that was observed in the data, was unsuccessful. CONCLUSION: In South African diabetic subjects, glibenclamide demonstrates linear PK and was best described by a two-compartmental model. Except for the absorption rate constant, the other PK parameters reported in this study are comparable to those reported in the scientific literature. The study is limited by the small study sample size and inclusion of poorly controlled type 2 diabetic subjects. |
format | Online Article Text |
id | pubmed-4948726 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-49487262016-07-28 Population pharmacokinetic modeling of glibenclamide in poorly controlled South African type 2 diabetic subjects Rambiritch, Virendra Naidoo, Poobalan Maharaj, Breminand Pillai, Goonaseelan Clin Pharmacol Original Research AIM: The aim of this study was to describe the pharmacokinetics (PK) of glibenclamide in poorly controlled South African type 2 diabetic subjects using noncompartmental and model-based methods. METHODS: A total of 24 subjects with type 2 diabetes were administered increasing doses (0 mg/d, 2.5 mg/d, 5 mg/d, 10 mg/d, and 20 mg/d) of glibenclamide daily at 2-week intervals. Plasma glibenclamide, glucose, and insulin determinations were performed. Blood sampling times were 0 minute, 30 minutes, 60 minutes, 90 minutes, and 120 minutes (post breakfast sampling) and 240 minutes, 270 minutes, 300 minutes, 330 minutes, 360 minutes, and 420 minutes (post lunch sampling) on days 14, 28, 42, 56, and 70 for doses of 0 mg, 2.5 mg, 5.0 mg, 10 mg, and 20 mg, respectively. Blood sampling was performed after the steady state was reached. A total of 24 individuals in the data set contributed to a total of 841 observation records. The PK was analyzed using noncompartmental analysis methods, which were implemented in WinNonLin(®), and population PK analysis using NONMEM(®). Glibenclamide concentration data were log transformed prior to fitting. RESULTS: A two-compartmental disposition model was selected after evaluating one-, two-, and three-compartmental models to describe the time course of glibenclamide plasma concentration data. The one-compartment model adequately described the data; however, the two-compartment model provided a better fit. The three-compartment model failed to achieve successful convergence. A more complex model, to account for enterohepatic recirculation that was observed in the data, was unsuccessful. CONCLUSION: In South African diabetic subjects, glibenclamide demonstrates linear PK and was best described by a two-compartmental model. Except for the absorption rate constant, the other PK parameters reported in this study are comparable to those reported in the scientific literature. The study is limited by the small study sample size and inclusion of poorly controlled type 2 diabetic subjects. Dove Medical Press 2016-07-12 /pmc/articles/PMC4948726/ /pubmed/27471411 http://dx.doi.org/10.2147/CPAA.S102676 Text en © 2016 Rambiritch et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. |
spellingShingle | Original Research Rambiritch, Virendra Naidoo, Poobalan Maharaj, Breminand Pillai, Goonaseelan Population pharmacokinetic modeling of glibenclamide in poorly controlled South African type 2 diabetic subjects |
title | Population pharmacokinetic modeling of glibenclamide in poorly controlled South African type 2 diabetic subjects |
title_full | Population pharmacokinetic modeling of glibenclamide in poorly controlled South African type 2 diabetic subjects |
title_fullStr | Population pharmacokinetic modeling of glibenclamide in poorly controlled South African type 2 diabetic subjects |
title_full_unstemmed | Population pharmacokinetic modeling of glibenclamide in poorly controlled South African type 2 diabetic subjects |
title_short | Population pharmacokinetic modeling of glibenclamide in poorly controlled South African type 2 diabetic subjects |
title_sort | population pharmacokinetic modeling of glibenclamide in poorly controlled south african type 2 diabetic subjects |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4948726/ https://www.ncbi.nlm.nih.gov/pubmed/27471411 http://dx.doi.org/10.2147/CPAA.S102676 |
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