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@ARTICLE{Hamon:126658,
author = {J. Hamon and M. Renner and M. Jamei and A. Lukas and A.
Kopp-Schneider$^*$ and F. Y. Bois},
title = {{Q}uantitative in vitro to in vivo extrapolation of tissues
toxicity.},
journal = {Toxicology in vitro},
volume = {30},
number = {1 Pt A},
issn = {0887-2333},
address = {Amsterdam [u.a.]},
publisher = {Elsevier Science},
reportid = {DKFZ-2017-02686},
pages = {203 - 216},
year = {2015},
abstract = {Predicting repeated-dosing in vivo drug toxicity from in
vitro testing and omics data gathering requires significant
support in bioinformatics, mathematical modeling and
statistics. We present here the major aspects of the work
devoted within the framework of the European integrated
Predict-IV to pharmacokinetic modeling of in vitro
experiments, physiologically based pharmacokinetic (PBPK)
modeling, mechanistic models of toxicity for the kidney and
brain, large scale dose-response analyses methods and
biomarker discovery tools. All of those methods have been
applied to various extent to the drug datasets developed by
the project's partners. Our approach is rather generic and
could be adapted to other drugs or drug candidates. It marks
a successful integration of the work of the different teams
toward a common goal of predictive quantitative in vitro to
in vivo extrapolation.},
cin = {C060},
ddc = {610},
cid = {I:(DE-He78)C060-20160331},
pnm = {313 - Cancer risk factors and prevention (POF3-313)},
pid = {G:(DE-HGF)POF3-313},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:25678044},
doi = {10.1016/j.tiv.2015.01.011},
url = {https://inrepo02.dkfz.de/record/126658},
}