Persistence Assessment of Chemicals: Trajectories toward New Approach Methodologies (P-NAMs)

Area of Science:

• Environmental Chemistry
• Toxicology
• Computational Chemistry

Background:

• Chemical persistence is crucial for ecosystem and human exposure, with legacy pollutants like DDT, PCBs, and PFAS highlighting this issue.
• Existing experimental data on chemical half-lives are insufficient, hindering accurate persistence assessments and regulatory efforts.
• Current testing frameworks struggle to address extensive data gaps, necessitating innovative solutions.

Purpose of the Study:

• To advocate for the development and implementation of New Approach Methodologies for Persistence Assessment (P-NAMs).
• To address the limitations of current testing frameworks in assessing chemical persistence.
• To promote a shift from persistence assessment as a bottleneck to a driver of innovation in chemical safety.

Main Methods:

• Utilizing high-throughput (HT) experimental systems for efficient data generation.
• Employing advanced in silico models for predictive assessments.
• Integrating transformation product analysis and FAIR data repositories to enhance mechanistic understanding.

Main Results:

• HT-testing can bridge the gap between basic screening and complex simulation studies.
• HT-testing generates large, consistent datasets crucial for improving biotransformation understanding.
• Improved mechanistic insights and predictive model accuracy are achievable through integrated approaches.

Conclusions:

• P-NAMs, combining HT-testing and in silico models, are essential for overcoming current persistence assessment challenges.
• Coordinated efforts are required to standardize reporting, expand data accessibility, and validate predictive tools.
• Advancing P-NAMs will safeguard human and ecosystem health and foster safer chemical design.