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A Cheminformatics Workflow to Select Representative TSCA Chemicals for New Approach Methodology (NAM) Screening.

Grace Patlewicz¹, Antony J Williams¹, Matthew Adams^1,2

¹Center for Computational Toxicology & Exposure (CCTE), U.S. Environmental Protection Agency, Research Triangle Park, Durham, North Carolina 27709, United States.

Chemical Research in Toxicology

|December 10, 2024

Summary

This summary is machine-generated.

This study developed a cheminformatics workflow to select 318 diverse chemicals from the TSCA inventory for in vitro screening using New Approach Methods (NAMs). This approach aids in filling data gaps for new chemical assessments.

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NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode

NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode

Published on: June 4, 2021

Area of Science:

Environmental Chemistry
Toxicology
Computational Chemistry

Background:

The Toxic Substances Control Act (TSCA) mandates hazard and exposure evaluations for chemicals.
Data gaps in new chemical notifications often necessitate predictive approaches.
New Approach Methods (NAMs) offer opportunities to enhance chemical assessments.

Purpose of the Study:

To develop and apply a cheminformatics workflow for selecting representative chemicals for in vitro screening.
To create a case study for an adaptable NAMs-based approach for new chemical evaluations.
To identify candidate chemicals from the TSCA inventory for hazard and exposure assessment.

Main Methods:

Utilized ClassyFire for chemical categorization and hierarchical clustering to define 180 terminal structural categories.
Filtered the TSCA inventory based on screening history, physicochemical properties, procurement likelihood, and analytical amenability.
Excluded substances with potential reactivity or instability concerns.
Selected structurally representative chemicals meeting screenability criteria.

Main Results:

A workflow was developed to identify a set of 318 candidate chemicals from the TSCA inventory.
These candidates are structurally diverse and suitable for in vitro screening.
In silico tools were used to predict hazard profiles of the selected candidates.

Conclusions:

The developed cheminformatics workflow provides an adaptable strategy for selecting diverse chemical sets for NAMs-based assessments.
This approach supports data-poor new chemical evaluations under TSCA.
The selected 318 chemicals represent a valuable resource for future toxicological studies.