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. 2023 Nov;16(11):2163-2176.
doi: 10.1111/cts.13614. Epub 2023 Sep 15.

Application of a physiologically based pharmacokinetic model to predict isoniazid disposition during pregnancy

Affiliations

Application of a physiologically based pharmacokinetic model to predict isoniazid disposition during pregnancy

Ogochukwu U Amaeze et al. Clin Transl Sci. 2023 Nov.

Abstract

Pregnancy can increase the risk of latent tuberculosis infection (LTBI) progression to tuberculosis (TB) disease. Isoniazid (INH) is the preferred preventative treatment for LTBI in pregnancy. INH is mainly cleared by N-acetyltransferase 2 (NAT2) but the pharmacokinetics (PK) of INH in different NAT2 phenotypes during pregnancy is not well characterized. To address this knowledge gap, we used physiologically based pharmacokinetic (PBPK) modeling to evaluate NAT2 phenotype-specific effects of pregnancy on INH disposition. A whole-body PBPK model for INH was developed and verified for non-pregnant NAT2 fast (FA), intermediate (IA), and slow (SA) acetylators. Model predictive performance was assessed using a drug-specific model acceptance criterion for mean plasma area under the curve (AUC) and peak plasma concentration (Cmax ), and the absolute average fold error (AAFE) for individual plasma concentrations. The verified model was extended to simulate INH disposition during pregnancy in NAT2 SA, IA, and FA populations. A sensitivity analysis was conducted using the verified PBPK model and known changes in INH disposition during pregnancy to determine whether NAT2 activity changes during pregnancy or other INH clearance pathways are altered. This analysis suggested that NAT2 activity is unchanged while other INH clearance pathways increase by ~80% during pregnancy. The model was applied to explore the effect of pregnancy on INH disposition in two ethnic populations with different NAT2 phenotype distributions and with high TB burden. Our PBPK model can be used to predict INH disposition during pregnancy in diverse populations and expanded to other drugs cleared by NAT2 during pregnancy.

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Conflict of interest statement

N.I. reports consultancy agreements with Boehringer‐Ingelheim and Johnson and Johnson, and honoraria from ASPET and McGraw Hill. O.U.A. has declared no competing interests for this work.

Figures

FIGURE 1
FIGURE 1
Workflow for the isoniazid physiologically based pharmacokinetic model development and verification in N‐acetyltransferase 2 fast, intermediate, and slow acetylators. Abbreviations: FA, fast acetylators; IA, intermediate acetylators; i.v., intravenous; NAT2, N‐acetyltransferase 2; PBPK, physiologically based pharmacokinetic; SA, slow acetylators.
FIGURE 2
FIGURE 2
Simulated plasma concentration–time profiles following intravenous (i.v.) and oral (p.o.) administration of isoniazid (INH) overlaid with mean observed plasma INH concentrations in non‐pregnant N‐acetyltransferase 2 (NAT2) fast acetylators (FA). Open circles represent the mean observed data, gray solid lines show simulated plasma concentrations in 10 trials, and the green solid line represents the mean of the trials. The mean observed INH concentrations are from Kinzig‐Schippers et al. (a–c); Boxenbaum and Riegelman (d); Kubota et al. (e–g); Bing et al. (h); and Yoo et al. (i‐j). (a–c) were used for model development and (d–j) were used for model verification. The insets show the dose and route of administration in each study and the absolute average fold error (AAFE) calculated from the mean simulated and observed concentrations of each respective dataset.
FIGURE 3
FIGURE 3
Simulated plasma concentration–time profiles following intravenous (i.v.) and oral (p.o.) administration of isoniazid (INH) overlaid with mean observed plasma INH concentrations in non‐pregnant N‐acetyltransferase 2 (NAT2) intermediate acetylators (IA) and slow acetylators (SA). Open circles (purple: SA, red: IA) represent the mean observed data, gray solid lines show simulated plasma concentrations in 10 trials, and the green solid line represents the mean of the trials. The mean observed INH concentrations are from Kinzig‐Schippers et al. (a–c, j–l); Boxenbaum and Riegelman (d); Bing et al. (e, m); and Yoo et al. (f–i). (a–c) were used for model development and (d–n) were used for model verification. The insets show the dose and route of administration in each study and the absolute average fold error (AAFE) calculated from the simulated and mean observed concentrations of each respective dataset.
FIGURE 4
FIGURE 4
Simulated plasma concentration–time profiles of isoniazid (INH) in N‐acetyltransferase 2 (NAT2) (a) fast acetylators, (b) intermediate acetylators, and (c) slow acetylators during pregnancy (gestational week 28) following administration of a single 300 mg INH dose. The solid line shows the mean plasma concentration of the simulated population, and the dashed lines show the 10th and 90th percentiles of the simulated data. The dotted horizontal lines represent the recommended therapeutic Cmax range for isoniazid following a 300 mg oral dose.
FIGURE 5
FIGURE 5
Simulated plasma concentration–time profiles of isoniazid (INH) following oral (p.o.) administration of a single 300 mg INH dose in pregnant (gestational week 28) populations with various N‐acetyltransferase 2 (NAT2) phenotype distributions. The populations shown are (a) Africa (AFR) fast acetylators (FA), (b) Africa intermediate acetylators (IA), (c) Africa slow acetylators (SA), (d) Africa combined NAT2 phenotypes, (e) South Asia (SAS) FA, (f) South Asia IA, (g) South Asia SA, and (h) South Asia combined NAT2 phenotypes. The solid lines show the population mean simulated plasma concentration, and the dashed lines show the 10th and 90th percentiles of the simulated data. The horizontal dotted lines represent the recommended therapeutic range (3–6 mg/L) for isoniazid Cmax following a 300 mg oral dose.

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