ECO44 – A toxicokinetic mammalian modelling framework for bioaccumulation assessment

Description

Historically, the globally accepted model for bioaccumulation (B) determination has been fish. The basis of B screening and assessment has been driven by the octanol-water partition coefficient (K_OW) and data and assessment endpoints for aquatic species (e.g., bioconcentration factors; BCFs); however, nearly two decades of evidence has highlighted the need to examine B in air-breathing organisms specifically. Emerging regulatory guidance, e.g., REACH Chapter R11: PBT / vPvB Assessment, includes B screening threshold criteria for air-breathing organisms linked to K_OW and the octanol-air partition coefficient (K_OA): ”An efficiently absorbed, non-biotransformed neutral organic substance with a log K_OA ≥ 5 in combination with a log K_OW ≥ 2 has the potential to biomagnify in terrestrial food chains and air-breathing marine wildlife as well as in humans, while the substances with log K_OW < 2 are being quickly eliminated by the urinary excretion, and therefore do not biomagnify even though their K_OA is high.” In addition to K_OW and K_OA, it is acknowledged that considerations of dietary absorption efficiency and biotransformation rates are also necessary for B assessment. While certain tools for simulating B in mammals and other air-breathing organisms exist, it is desirable to further develop and refine tools and data streams more explicitly.

General Objective

The general objective of this project is to build a toxicokinetic (TK) modelling framework for mammals and develop and integrate various data streams for mammalian B assessment. This research will expand the development, evaluation, and application of the CEFIC-LRI funded Bioaccumulation Assessment Tool (BAT) and other B, TK, and risk assessment models for mammals. A particular focus of this project is to address data gaps and uncertainty in biotransformation half-lives. To satisfy these general objectives, this project will:

1) Assimilate critically evaluated data from various sources of in vitro and in vivo TK data (rodents and humans), as well as field B data in mammals (TMF and BMF). Quantitative Structure-Activity Relationship (QSAR) model predictions will be included to compare and analyze various data streams.

2) Develop and test one-compartment TK (1-CoTK) and generic physiologically-based TK (G-PBTK) models for mammalian species. The models will be parameterized for laboratory test mammals (rats, mice), and evaluated along with in vitro-in vivo extrapolation (IVIVE) models to integrate TK data with collected in vivo and in vitro laboratory data.

3) Develop and test various QSAR models for predicting biotransformation half-lives and other endpoints relevant for TK and B model applications.

4) Refine the BAT for mammalian species and evaluate model predictions for mammals with field and laboratory data.

5) Synthesize the state of the science and available data streams to develop an integrated testing strategy (ITS) for additional priority chemicals. This will inform future testing needs to address current measurement gaps and QSAR model uncertainties.