A Model-Informed Method for the Purpose of Precision Dosing of Isoniazid in Pulmonary Tuberculosis.


Journal

Clinical pharmacokinetics
ISSN: 1179-1926
Titre abrégé: Clin Pharmacokinet
Pays: Switzerland
ID NLM: 7606849

Informations de publication

Date de publication:
07 2021
Historique:
accepted: 28 11 2020
pubmed: 23 2 2021
medline: 29 10 2021
entrez: 22 2 2021
Statut: ppublish

Résumé

This study aimed to develop and evaluate a population pharmacokinetic model and limited sampling strategy for isoniazid to be used in model-based therapeutic drug monitoring. A population pharmacokinetic model was developed based on isoniazid and acetyl-isoniazid pharmacokinetic data from seven studies with in total 466 patients from three continents. Three limited sampling strategies were tested based on the available sampling times in the dataset and practical considerations. The tested limited sampling strategies sampled at 2, 4, and 6 h, 2 and 4 h, and 2 h after dosing. The model-predicted area under the concentration-time curve from 0 to 24 h (AUC Performance of the developed model was acceptable and the uncertainty in parameter estimations was generally low (the highest relative standard error was 39% coefficient of variation). The limited sampling strategy with sampling at 2 and 4 h was determined as most suitable with an ME of 1.1% and RMSE of 23.4% for AUC A model-based therapeutic drug monitoring strategy for personalized dosing of isoniazid using sampling at 2 and 4 h after dosing was successfully developed. Prospective evaluation of this strategy will show how it performs in a clinical therapeutic drug monitoring setting.

Sections du résumé

BACKGROUND AND OBJECTIVE
This study aimed to develop and evaluate a population pharmacokinetic model and limited sampling strategy for isoniazid to be used in model-based therapeutic drug monitoring.
METHODS
A population pharmacokinetic model was developed based on isoniazid and acetyl-isoniazid pharmacokinetic data from seven studies with in total 466 patients from three continents. Three limited sampling strategies were tested based on the available sampling times in the dataset and practical considerations. The tested limited sampling strategies sampled at 2, 4, and 6 h, 2 and 4 h, and 2 h after dosing. The model-predicted area under the concentration-time curve from 0 to 24 h (AUC
RESULTS
Performance of the developed model was acceptable and the uncertainty in parameter estimations was generally low (the highest relative standard error was 39% coefficient of variation). The limited sampling strategy with sampling at 2 and 4 h was determined as most suitable with an ME of 1.1% and RMSE of 23.4% for AUC
CONCLUSIONS
A model-based therapeutic drug monitoring strategy for personalized dosing of isoniazid using sampling at 2 and 4 h after dosing was successfully developed. Prospective evaluation of this strategy will show how it performs in a clinical therapeutic drug monitoring setting.

Identifiants

pubmed: 33615419
doi: 10.1007/s40262-020-00971-2
pii: 10.1007/s40262-020-00971-2
pmc: PMC8249295
doi:

Substances chimiques

Isoniazid V83O1VOZ8L

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

943-953

Investigateurs

M J Boeree (MJ)
E Burhan (E)
R Dawson (R)
A H Diacon (AH)
S Gillespie (S)
C M Mtabho (CM)
N E Ntingiya (NE)
N Heinrich (N)
W Hoefsloot (W)
M Hoelscher (M)
G Kibiki (G)
K Reither (K)
I Sanne (I)
H H Semvua (HH)
A Tostmann (A)

Commentaires et corrections

Type : ErratumIn

Références

Antimicrob Agents Chemother. 2015 Nov;59(11):6791-9
pubmed: 26282412
Br J Clin Pharmacol. 2019 Jun;85(6):1326-1336
pubmed: 30767254
Br J Clin Pharmacol. 2005 Feb;59(2):189-98
pubmed: 15676041
J Pharmacokinet Pharmacodyn. 2001 Oct;28(5):481-504
pubmed: 11768292
PLoS One. 2015 Oct 26;10(10):e0141002
pubmed: 26501782
Intern Med J. 2017 May;47(5):593-600
pubmed: 28503880
J Pharmacokinet Pharmacodyn. 2016 Dec;43(6):583-596
pubmed: 27730482
J Pharmacokinet Pharmacodyn. 2019 Jun;46(3):241-250
pubmed: 30968312
Pulm Pharmacol Ther. 2012 Feb;25(1):83-6
pubmed: 22179055
Clin Infect Dis. 2018 Nov 13;67(11):1743-1749
pubmed: 29697766
Antimicrob Agents Chemother. 1997 Dec;41(12):2670-9
pubmed: 9420037
J Pharmacokinet Pharmacodyn. 2017 Dec;44(6):509-520
pubmed: 28887735
CPT Pharmacometrics Syst Pharmacol. 2018 Dec;7(12):785-787
pubmed: 30255663
J Antimicrob Chemother. 2014 May;69(5):1339-49
pubmed: 24486870
Antivir Ther. 2013;18(1):105-13
pubmed: 23043067
Annu Rev Pharmacol Toxicol. 2008;48:303-32
pubmed: 17914927
J Pharmacokinet Biopharm. 1981 Aug;9(4):503-12
pubmed: 7310648
J Antimicrob Chemother. 2019 Jan 1;74(1):139-148
pubmed: 30239829
Antimicrob Agents Chemother. 2015 Sep;59(9):5181-9
pubmed: 26077251
Drugs. 2014 Jun;74(8):839-54
pubmed: 24846578
Am J Respir Crit Care Med. 1997 May;155(5):1717-22
pubmed: 9154882
Lancet Infect Dis. 2017 Jan;17(1):39-49
pubmed: 28100438
CPT Pharmacometrics Syst Pharmacol. 2013 Jun 26;2:e50
pubmed: 23836189
Antimicrob Agents Chemother. 2017 Oct 24;61(11):
pubmed: 28827417
Int J Antimicrob Agents. 2014 Sep;44(3):229-34
pubmed: 24985091
Br J Clin Pharmacol. 2012 Sep;74(3):465-76
pubmed: 22300396
AAPS J. 2011 Jun;13(2):143-51
pubmed: 21302010
Antimicrob Agents Chemother. 2007 Jul;51(7):2329-36
pubmed: 17438043
J Infect Dis. 2013 Nov 1;208(9):1464-73
pubmed: 23901086
Int J Tuberc Lung Dis. 2016 Jul;20(7):955-60
pubmed: 27287650
Antimicrob Agents Chemother. 2003 Jul;47(7):2118-24
pubmed: 12821456
Eur Respir J. 2015 Jul;46(1):268-71
pubmed: 25882800
Br J Clin Pharmacol. 2011 Jul;72(1):51-62
pubmed: 21320152
Eur Respir J. 2016 Oct;48(4):1237-1239
pubmed: 27492836
Antimicrob Agents Chemother. 2013 Jul;57(7):3208-13
pubmed: 23629715
Clin Infect Dis. 2017 May 15;64(10):1350-1359
pubmed: 28205671
Antimicrob Agents Chemother. 2013 Aug;57(8):3614-9
pubmed: 23689725
Clin Pharmacokinet. 2019 Jun;58(6):815-826
pubmed: 30671890
Antimicrob Agents Chemother. 2004 Aug;48(8):2951-7
pubmed: 15273105
AAPS J. 2009 Mar;11(1):148-54
pubmed: 19277871
Clin Pharmacol Ther. 2020 Jul;108(1):73-80
pubmed: 32017035
Clin Infect Dis. 2012 Jul;55(2):169-77
pubmed: 22467670

Auteurs

Stijn W van Beek (SW)

Department of Pharmacy, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein zuid 10, 864, 6500 HB, Nijmegen, The Netherlands. Stijn.vanBeek@radboudumc.nl.

Rob Ter Heine (R)

Department of Pharmacy, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein zuid 10, 864, 6500 HB, Nijmegen, The Netherlands.

Jan-Willem C Alffenaar (JC)

School of Pharmacy, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia.
Westmead Hospital, Sydney, NSW, Australia.
Marie Bashir Institute of Infectious Diseases and Biosecurity, University of Sydney, Sydney, NSW, Australia.

Cecile Magis-Escurra (C)

Department of Respiratory Diseases, Radboud University Medical Center, Nijmegen, The Netherlands.

Rob E Aarnoutse (RE)

Department of Pharmacy, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein zuid 10, 864, 6500 HB, Nijmegen, The Netherlands.

Elin M Svensson (EM)

Department of Pharmacy, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein zuid 10, 864, 6500 HB, Nijmegen, The Netherlands.
Department of Pharmacy, Uppsala University, Uppsala, Sweden.

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