Estimation of toxicokinetic population parameters in a four-stage hierarchical model

Silvia Selinski

No 2000,01, Technical Reports from Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen

Abstract: A basic part in the risk assessment of potential carcinogens is the determination of toxicokinetic parameters. The partition of the xenobiotic in the body of experimental animals is a first step of the biochemical pathway of the formation of DNA adducts which might lead to the development of cancer. Fundamental in the extrapolation from one species to another is the characterisation of processes by means of population parameters. Nevertheless, the consideration of individual parameters varying between repeated experiments and different doses is of great importance to obtain a more precise insight into the variability structure of the process so that a valid basis for further research is the final result. Two nonlinear four-stage hierarchical models for a repeated measurement design and for repeated exposures to different doses are presented. The estimation of the individual and population parameters as well as of the covariance matrices is performed by an EM algorithm.

Keywords: ethylene; ethylene oxide; risk assessment; toxicokinetics; population parameters; two-compartment model; nonlinear hierarchical model; Bayes estimates; EM algorithm; repeated measurement (search for similar items in EconPapers)
Date: 2000
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/77310/2/2000-01.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:zbw:sfb475:200001

Access Statistics for this paper

More papers in Technical Reports from Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().