Cefic-lri Programme | European Chemical Industry Council

ECO6.2-ILSIHESI: Pre-validation of an in vitro fish liver S9 assay to optimize the prediction of bioaccumulation

Principal Investigator

Dr. Susan Erhardt
Toxicology Research and Consulting Laboratories
1803 Building, Door E
Midland, MI, 48674, USA
Tel: +1 989-638-8424
Fax: +1 989-638-9305

Collaborators

Beate Escher, Ph.D. – EAWAG, CH
Jasminder Sahi, Ph.D. – CellzDirect, Inc, USA
Karla Johanning, Ph.D. – CellzDirect, Inc, USA
Annie Weisbrod, Ph.D. – Procter & Gamble, USA
Scott Dyer, Ph.D. – Procter & Gamble, USA
Mary Jo Bernhard – Procter & Gamble, USA
Alan Sharpe – Brixham Environmental Laboratory, AstraZeneca Ltd, UK
Curtis Eickhoff Ph.D. – CANTEST, CA

Description

The specific objectives of this project are to support incorporation of in vitro metabolism data into BCF prediction models and to extrapolate in vitro test results to whole body biotransformation rates (kmet) to be used to refine BCF model predictions. The in vitro biotransformation data generated during this study will be scaled to in vivo biotransformation rates using whole tissue and whole body values.  The in vivo estimated rate of metabolism will be incorporated into calculations of BCF such as those developed by Gobas and Arnot [3].  This in vitro approach will have the potential to reduce the need for the whole animal testing currently required by the OECD 305 bioaccumulation test [4].  In particular, we intend to:

  1. Identify chemical structures associated with susceptibility to metabolism, as either limited or specific metabolism or recalcitrant and use a subset of these as our test chemicals for pre-validation of the S9 test method.
  2. Assess intra- and inter-laboratory variability of the in vitro S9 trout hepatic fraction assay.
  3. Evaluate the relevance of metabolic stability assays with S9 trout hepatic fractions to predict in vivo kMET values that can be used to refine the accuracy of in silico BCF models.
  4. Determine the impact of bioavailability on the in vitro to in vivo prediction model by determining bound and unbound fraction of test chemical.
  5. Compare in vitro S9 trout hepatic fraction data rates of metabolism to published data on various species of fish and other organisms

Related Publications

Publications are expected in 2011.

Timeline: April 2008 > April 2010

LRI funding: €175,000

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