Population pharmacokinetic modeling of glibenclamide in poorly controlled South African type 2 diabetic subjects

Virendra Rambiritch,1 Poobalan Naidoo,2 Breminand Maharaj,1 Goonaseelan Pillai3 1University of KwaZulu-Natal, Durban, 2Department of Internal Medicine, RK Khan Regional Hospital, Chatsworth, South Africa; 3Novartis Pharma AG, Basel, Switzerland Aim: The aim of this study was to describe th...

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Autores principales: Rambiritch V, Naidoo P, Maharaj B, Pillai G
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Publicado: Dove Medical Press 2016
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spelling oai:doaj.org-article:1308fa1e06f2436498108381527c0a042021-12-02T02:44:02ZPopulation pharmacokinetic modeling of glibenclamide in poorly controlled South African type 2 diabetic subjects1179-1438https://doaj.org/article/1308fa1e06f2436498108381527c0a042016-07-01T00:00:00Zhttps://www.dovepress.com/population-pharmacokinetic-modeling-of-glibenclamide-in-poorly-control-peer-reviewed-article-CPAAhttps://doaj.org/toc/1179-1438Virendra Rambiritch,1 Poobalan Naidoo,2 Breminand Maharaj,1 Goonaseelan Pillai3 1University of KwaZulu-Natal, Durban, 2Department of Internal Medicine, RK Khan Regional Hospital, Chatsworth, South Africa; 3Novartis Pharma AG, Basel, Switzerland 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. Keywords: type 2 diabetes mellitus, glibenclamide, pharmacokinetics, compartmental, NONMEM modelRambiritch VNaidoo PMaharaj BPillai GDove Medical Pressarticletype 2 diabetes mellitusglibenclamidepharmacokineticscompartment modelTherapeutics. PharmacologyRM1-950ENClinical Pharmacology: Advances and Applications, Vol 2016, Iss Issue 1, Pp 83-92 (2016)
institution DOAJ
collection DOAJ
language EN
topic type 2 diabetes mellitus
glibenclamide
pharmacokinetics
compartment model
Therapeutics. Pharmacology
RM1-950
spellingShingle type 2 diabetes mellitus
glibenclamide
pharmacokinetics
compartment model
Therapeutics. Pharmacology
RM1-950
Rambiritch V
Naidoo P
Maharaj B
Pillai G
Population pharmacokinetic modeling of glibenclamide in poorly controlled South African type 2 diabetic subjects
description Virendra Rambiritch,1 Poobalan Naidoo,2 Breminand Maharaj,1 Goonaseelan Pillai3 1University of KwaZulu-Natal, Durban, 2Department of Internal Medicine, RK Khan Regional Hospital, Chatsworth, South Africa; 3Novartis Pharma AG, Basel, Switzerland 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. Keywords: type 2 diabetes mellitus, glibenclamide, pharmacokinetics, compartmental, NONMEM model
format article
author Rambiritch V
Naidoo P
Maharaj B
Pillai G
author_facet Rambiritch V
Naidoo P
Maharaj B
Pillai G
author_sort Rambiritch V
title 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_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_sort population pharmacokinetic modeling of glibenclamide in poorly controlled south african type 2 diabetic subjects
publisher Dove Medical Press
publishDate 2016
url https://doaj.org/article/1308fa1e06f2436498108381527c0a04
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