Literature DB >> 16291521

Physiologically-based pharmacokinetic and toxicokinetic models in cancer risk assessment.

Kannan Krishnan1, Gunnar Johanson.   

Abstract

Physiologically-based pharmacokinetic (PBPK) and toxicokinetic models are increasingly being used for the conduct of high dose to low dose and interspecies extrapolations required in cancer risk assessment. These models, by simulating tissue dose of toxic chemicals, help address the uncertainty associated with the default approaches for interspecies and high dose to low dose extrapolations. The applicability of PBPK models in cancer risk assessment has been demonstrated with a number of chemicals (e.g., acrylonitrile, 2-butoxyethanol, chloroform, 1,4-dioxane, methyl chloroform, methylene chloride, styrene, trichloroethylene, tetrachloroethylene, vinyl chloride, vinyl acetate). Recent advances in PBPK modeling facilitate the consideration of population distribution of parameter values, age-dependent changes in physiology and metabolism, multi-route exposures as well as multichemical interactions for application in cancer risk assessment. Whereas the average values for various input parameters have been used to evaluate the age-dependency of tissue dose, the Markov Chain Monte Carlo technique can be applied to address variability and uncertainty in parameter estimates, thus facilitating a more accurate estimation of cancer risk in the population. The PBPK models also uniquely facilitate the simulation of tissue dose, and thereby cancer risks, associated with multi-route and multichemical exposure situations. Overall, the recent advances reviewed in this article point to the continued enhancement of the scientific basis and applicability of PBPK models in cancer risk assessment.

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Year:  2005        PMID: 16291521     DOI: 10.1081/GNC-200051856

Source DB:  PubMed          Journal:  J Environ Sci Health C Environ Carcinog Ecotoxicol Rev        ISSN: 1059-0501            Impact factor:   3.781


  2 in total

1.  A physiologically based pharmacokinetic model of rifampin in mice.

Authors:  Michael A Lyons; Brad Reisfeld; Raymond S H Yang; Anne J Lenaerts
Journal:  Antimicrob Agents Chemother       Date:  2013-01-28       Impact factor: 5.191

2.  A computational systems biology software platform for multiscale modeling and simulation: integrating whole-body physiology, disease biology, and molecular reaction networks.

Authors:  Thomas Eissing; Lars Kuepfer; Corina Becker; Michael Block; Katrin Coboeken; Thomas Gaub; Linus Goerlitz; Juergen Jaeger; Roland Loosen; Bernd Ludewig; Michaela Meyer; Christoph Niederalt; Michael Sevestre; Hans-Ulrich Siegmund; Juri Solodenko; Kirstin Thelen; Ulrich Telle; Wolfgang Weiss; Thomas Wendl; Stefan Willmann; Joerg Lippert
Journal:  Front Physiol       Date:  2011-02-24       Impact factor: 4.566

  2 in total

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