Literature DB >> 21953913

A semiphysiologically based pharmacokinetic modeling approach to predict the dose-exposure relationship of an antiparasitic prodrug/active metabolite pair.

Grace Zhixia Yan1, Claudia N Generaux, Miyoung Yoon, Rachel B Goldsmith, Richard R Tidwell, James E Hall, Carol A Olson, Harvey J Clewell, Kim L R Brouwer, Mary F Paine.   

Abstract

Dose selection during antiparasitic drug development in animal models and humans traditionally has relied on correlations between plasma concentrations obtained at or below maximally tolerated doses that are efficacious. The objective of this study was to improve the understanding of the relationship between dose and plasma/tissue exposure of the model antiparasitic agent, pafuramidine, using a semiphysiologically based pharmacokinetic (semi-PBPK) modeling approach. Preclinical and clinical data generated during the development of pafuramidine, a prodrug of the active metabolite, furamidine, were used. A whole-body semi-PBPK model for rats was developed based on a whole-liver PBPK model using rat isolated perfused liver data. A whole-body semi-PBPK model for humans was developed on the basis of the whole-body rat model. Scaling factors were calculated using metabolic and transport clearance data generated from rat and human sandwich-cultured hepatocytes. Both whole-body models described pafuramidine and furamidine disposition in plasma and predicted furamidine tissue (liver and kidney) exposure and excretion profiles (biliary and renal). The whole-body models predicted that the intestine contributes significantly (30-40%) to presystemic furamidine formation in both rats and humans. The predicted terminal elimination half-life of furamidine in plasma was 3- to 4-fold longer than that of pafuramidine in rats (170 versus 47 h) and humans (64 versus 19 h). The dose-plasma/tissue exposure relationship for the prodrug/active metabolite pair was determined using the whole-body models. The human model proposed a dose regimen of pafuramidine (40 mg once daily) based on a predefined efficacy-safety index. A similar approach could be used to guide dose-ranging studies in humans for next-in-class compounds.

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Year:  2011        PMID: 21953913      PMCID: PMC3250045          DOI: 10.1124/dmd.111.040063

Source DB:  PubMed          Journal:  Drug Metab Dispos        ISSN: 0090-9556            Impact factor:   3.922


  28 in total

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Review 5.  Physiological parameter values for physiologically based pharmacokinetic models.

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9.  Mechanisms underlying differences in systemic exposure of structurally similar active metabolites: comparison of two preclinical hepatic models.

Authors:  Grace Zhixia Yan; Kim L R Brouwer; Gary M Pollack; Michael Zhuo Wang; Richard R Tidwell; James E Hall; Mary F Paine
Journal:  J Pharmacol Exp Ther       Date:  2011-02-14       Impact factor: 4.030

10.  Metabolites of an orally active antimicrobial prodrug, 2,5-bis(4-amidinophenyl)furan-bis-O-methylamidoxime, identified by liquid chromatography/tandem mass spectrometry.

Authors:  Lian Zhou; Dhiren R Thakker; Robert D Voyksner; Mariappan Anbazhagan; David W Boykin; James E Hall; Richard R Tidwell
Journal:  J Mass Spectrom       Date:  2004-04       Impact factor: 1.982

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  3 in total

Review 1.  Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation Approaches: A Systematic Review of Published Models, Applications, and Model Verification.

Authors:  Jennifer E Sager; Jingjing Yu; Isabelle Ragueneau-Majlessi; Nina Isoherranen
Journal:  Drug Metab Dispos       Date:  2015-08-21       Impact factor: 3.922

Review 2.  The expanding role of prodrugs in contemporary drug design and development.

Authors:  Jarkko Rautio; Nicholas A Meanwell; Li Di; Michael J Hageman
Journal:  Nat Rev Drug Discov       Date:  2018-04-27       Impact factor: 84.694

Review 3.  Sandwich-Cultured Hepatocytes as a Tool to Study Drug Disposition and Drug-Induced Liver Injury.

Authors:  Kyunghee Yang; Cen Guo; Jeffrey L Woodhead; Robert L St Claire; Paul B Watkins; Scott Q Siler; Brett A Howell; Kim L R Brouwer
Journal:  J Pharm Sci       Date:  2016-02       Impact factor: 3.534

  3 in total

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