Chemical Safety and the Exposome

Area of Science:

• Environmental toxicology
• Computational toxicology
• Mechanistic toxicology

Background:

• Chemical intensification and pollution pose significant environmental and human health risks.
• Current chemical testing strategies are insufficient to address the vast number of chemicals produced.
• Existing methods rely heavily on animal testing and morphological endpoints, necessitating a paradigm shift.

Purpose of the Study:

• To highlight the critical role of mechanistic toxicology in chemical safety assessment.
• To advocate for New Approach Methodologies (NAMs) integrating diverse data types.
• To emphasize the need for understanding the exposome and individual susceptibility in risk assessment.

Main Methods:

• Review of current toxicological approaches and limitations.
• Discussion of advanced technologies like imaging and omics for data generation.
• Exploration of in silico methods, including machine learning, for toxicological prediction.
• Emphasis on integrated approaches combining molecular, in vitro, and human data.

Main Results:

• New Approach Methodologies (NAMs) enable faster, high-quality toxicological data collection.
• Advanced in silico approaches, including machine learning, improve toxicological potential prediction.
• Mechanistic toxicology provides a framework for understanding chemical interactions and the exposome.
• Personalized risk assessment considering individual exposomes and susceptibility is essential.

Conclusions:

• Mechanistic toxicology is central to chemical safety and understanding complex environmental interactions.
• A shift towards safe-and-sustainable-by-design approaches is vital for planetary and human health.
• Future risk assessments must incorporate individual susceptibility and the broader exposome for precision medicine and public health.