Title: A biology-based dynamic approach for the modelling of toxicity in cell assays.Part II: Models for cell population growth and toxicity
Authors: ZALDIVAR COMENGES Jose'MENNECOZZI MILENAMACKO PeterRODRIGUES RobimBOUHIFD MounirBARAIBAR FENTANES Joaquin
Publisher: Publications Office of the European Union
Publication Year: 2011
JRC N┬░: JRC63686
ISBN: 978-92-79-19568-6
ISSN: 1831-9424
Other Identifiers: EUR 24374 EN
OPOCE LB-NB-24374-EN-N
URI: http://publications.jrc.ec.europa.eu/repository/handle/JRC63686
DOI: 10.2788/61603
Type: EUR - Scientific and Technical Research Reports
Abstract: There is a need to extrapolate from in vitro concentrations to in vivo dose. To do this extrapolation it is necessary to be able to calculate free concentrations in both systems and then compare them. Concerning the in vitro side, in the first part of this work, we had developed and implemented, based on HTS (High Throughput Screening) laboratory data, a compound fate model using the partitioning approach. The developed fate model was able to predict the role of serum in toxicity assays as well as provide estimation on the partitioning of a certain compound between the headspace, plastic wall and the medium: attached to serum, free dissolved and attached to the cells. However, the partitioning approach assumes that the equilibrium is fast in comparison with the duration of the experiments, which could not be the case for the partitioning to the cells. For this reason, a DEB (Dynamic Energy Budget) stage-based toxicity model has been developed and experimentally verified in the second part of this work. In addition, the model allows using internal concentrations as another toxicity scale allowing a toxicodynamics┬┐ independent raking of the toxic potency of a chemical and the possibility of toxicity data reconciliation from several sources taking into account the inherent dynamics always present during cell-based assays. The results show that this approach opens a new way of analyzing this type of data sets and offers the possibility of extrapolating the values obtained to calculate in vivo human toxicology thresholds using a PBTK modelling approach.
JRC Institute:Institute for Health and Consumer Protection

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