Semiphysiologically based pharmacokinetic model of leflunomide disposition in rheumatoid arthritis patients

Ashley M. Hopkins; Michael D. Wiese; Susanna M. Proudman; Catherine E. O'Doherty; David John Foster; Richard Neil Upton

doi:10.1002/psp4.46

Semiphysiologically based pharmacokinetic model of leflunomide disposition in rheumatoid arthritis patients

Ashley M. Hopkins, Michael D. Wiese, Susanna M. Proudman, Catherine E. O'Doherty, David John Foster, Richard Neil Upton

Flinders University

Research output: Contribution to journal › Article › peer-review

16 Citations (Scopus)

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Abstract

A semiphysiologically based pharmacokinetic (semi-PBPK) population model was used to evaluate the influence of enterohepatic recycling and protein binding, as well as the effect of genetic variability in CYP1A2, CYP2C19, and ABCG2, on the large interindividual variability of teriflunomide (active metabolite) concentrations following leflunomide administration in rheumatoid arthritis (RA) patients. The model was developed with total and free teriflunomide concentrations determined in RA patients taking leflunomide, as well as mean teriflunomide concentrations following the administration of leflunomide or teriflunomide extracted from the literature. Once developed, the 15-compartment model was able to predict total and free teriflunomide concentrations and was used to screen demographic and genotypic covariates, of which only fat-free mass and liver function (ALT) improved prediction. This approach effectively evaluated the effects of multiple covariates on both total and free teriflunomide concentrations, which have only been explored previously through simplistic one-compartment models for total teriflunomide.

Original language	English
Pages (from-to)	362-371
Number of pages	10
Journal	CPT: Pharmacometrics and Systems Pharmacology
Volume	4
Issue number	6
DOIs	https://doi.org/10.1002/psp4.46
Publication status	Published - Jun 2015

Bibliographical note

This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Keywords

Teriflunomide
leflunomide
pharmacogenetic markers
rheumatoid arthritis

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Hopkins_Semiphysiologically_P2015Final published version, 575 KBLicence: CC BY-NC

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title = "Semiphysiologically based pharmacokinetic model of leflunomide disposition in rheumatoid arthritis patients",

abstract = "A semiphysiologically based pharmacokinetic (semi-PBPK) population model was used to evaluate the influence of enterohepatic recycling and protein binding, as well as the effect of genetic variability in CYP1A2, CYP2C19, and ABCG2, on the large interindividual variability of teriflunomide (active metabolite) concentrations following leflunomide administration in rheumatoid arthritis (RA) patients. The model was developed with total and free teriflunomide concentrations determined in RA patients taking leflunomide, as well as mean teriflunomide concentrations following the administration of leflunomide or teriflunomide extracted from the literature. Once developed, the 15-compartment model was able to predict total and free teriflunomide concentrations and was used to screen demographic and genotypic covariates, of which only fat-free mass and liver function (ALT) improved prediction. This approach effectively evaluated the effects of multiple covariates on both total and free teriflunomide concentrations, which have only been explored previously through simplistic one-compartment models for total teriflunomide.",

keywords = "Teriflunomide, leflunomide, pharmacogenetic markers, rheumatoid arthritis",

author = "Hopkins, {Ashley M.} and Wiese, {Michael D.} and Proudman, {Susanna M.} and O'Doherty, {Catherine E.} and Foster, {David John} and Upton, {Richard Neil}",

note = "This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.",

year = "2015",

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AU - Wiese, Michael D.

AU - Proudman, Susanna M.

AU - O'Doherty, Catherine E.

AU - Foster, David John

AU - Upton, Richard Neil

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N2 - A semiphysiologically based pharmacokinetic (semi-PBPK) population model was used to evaluate the influence of enterohepatic recycling and protein binding, as well as the effect of genetic variability in CYP1A2, CYP2C19, and ABCG2, on the large interindividual variability of teriflunomide (active metabolite) concentrations following leflunomide administration in rheumatoid arthritis (RA) patients. The model was developed with total and free teriflunomide concentrations determined in RA patients taking leflunomide, as well as mean teriflunomide concentrations following the administration of leflunomide or teriflunomide extracted from the literature. Once developed, the 15-compartment model was able to predict total and free teriflunomide concentrations and was used to screen demographic and genotypic covariates, of which only fat-free mass and liver function (ALT) improved prediction. This approach effectively evaluated the effects of multiple covariates on both total and free teriflunomide concentrations, which have only been explored previously through simplistic one-compartment models for total teriflunomide.

AB - A semiphysiologically based pharmacokinetic (semi-PBPK) population model was used to evaluate the influence of enterohepatic recycling and protein binding, as well as the effect of genetic variability in CYP1A2, CYP2C19, and ABCG2, on the large interindividual variability of teriflunomide (active metabolite) concentrations following leflunomide administration in rheumatoid arthritis (RA) patients. The model was developed with total and free teriflunomide concentrations determined in RA patients taking leflunomide, as well as mean teriflunomide concentrations following the administration of leflunomide or teriflunomide extracted from the literature. Once developed, the 15-compartment model was able to predict total and free teriflunomide concentrations and was used to screen demographic and genotypic covariates, of which only fat-free mass and liver function (ALT) improved prediction. This approach effectively evaluated the effects of multiple covariates on both total and free teriflunomide concentrations, which have only been explored previously through simplistic one-compartment models for total teriflunomide.

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KW - pharmacogenetic markers

KW - rheumatoid arthritis

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M3 - Article

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JO - CPT: Pharmacometrics and Systems Pharmacology

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Semiphysiologically based pharmacokinetic model of leflunomide disposition in rheumatoid arthritis patients

Abstract

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Keywords

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