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Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation

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Published on: February 10, 2023

Bioaccumulation assessment using predictive approaches.

John W Nichols¹, Mark Bonnell, Sabcho D Dimitrov

¹US Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Mid-Continent Ecology Division, 6201 Congdon Boulevard, Duluth, Minnesota 55804, USA. nichols.john@epa.gov

Integrated Environmental Assessment and Management

|September 25, 2009

Summary

This summary is machine-generated.

Regulatory assessments for chemical bioaccumulation face data gaps. In vitro testing and computational methods offer predictive solutions for absorption, distribution, metabolism, and elimination (ADME) processes, improving environmental risk evaluation.

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Area of Science:

Environmental toxicology and risk assessment
Chemical kinetics and modeling

Background:

Increasing regulatory demands for chemical bioaccumulation assessments are hampered by data inadequacy.
Predictive tools are essential for timely and cost-effective regulatory compliance.
Absorption, distribution, metabolism, and elimination (ADME) processes govern chemical bioaccumulation in biota.

Purpose of the Study:

To explore the potential of in vitro test systems and computational methods for bioaccumulation modeling.
To address data limitations for critical input parameters in existing bioaccumulation models.
To propose a strategy for integrating predictive approaches into regulatory weight-of-evidence assessments.

Main Methods:

Review of in vitro test systems for providing ADME data.
Description of computational methods predicting ADME processes from chemical structure.
Development of a strategy for incorporating predictive data into bioaccumulation assessments.

Main Results:

In vitro systems show utility and provide proof of concept for bioaccumulation prediction models.
Computational structure-based methods can predict ADME processes.
Understanding the domain of applicability for predictive methods is crucial for implementation.

Conclusions:

In vitro and structure-based predictive approaches can significantly enhance bioaccumulation modeling.
These methods help overcome data limitations in regulatory assessments.
A strategic integration into weight-of-evidence approaches is recommended for effective risk evaluation.