ICT2025 - lUTOX 17th International Congress of Toxicology

Date	Time	Local Time	Room	Forum	Session	Role	Topic
2025-10-17	12:00-12:15	2025-10-17,12:00-12:15	Room A - Guojin Hall	Symposium Program （Session）	Young Scientist Lecture 02：AI-empowered Computational Toxicology	Speaker	Integrative Systematic Evidence Mapping and In Silico Molecular Docking for Prioritizing Plastic Additives Leaching from Polymers Plastic additive chemicals represent emerging contaminants due to their potential release from polymer matrices, posing significant toxicological risks. To comprehensively assess their environmental and human health impacts, we first conducted a Systematic Evidence Mapping (SEM) to review, classify, and synthesize current research on the leaching potential of plastic additives across various polymer types and environmental scenarios. This mapping process identified substantial gaps in empirical knowledge, particularly concerning the toxicological assessment of leached additives. Building on these findings, we employed in silico molecular docking simulations, an innovative new approach methodology (NAM), to predict binding affinities between selected plastic additives and key human nuclear receptors. Specifically, 150 functional additives registered under REACH were screened against seven nuclear receptors (ERs, AR, GR, PPARs, FXR, PXR, CAR), which represent molecular initiating events (MIEs) within established adverse outcome pathways (AOPs).

Plastic additive chemicals represent emerging contaminants due to their potential release from polymer matrices, posing significant toxicological risks. To comprehensively assess their environmental and human health impacts, we first conducted a Systematic Evidence Mapping (SEM) to review, classify, and synthesize current research on the leaching potential of plastic additives across various polymer types and environmental scenarios. This mapping process identified substantial gaps in empirical knowledge, particularly concerning the toxicological assessment of leached additives.

Building on these findings, we employed in silico molecular docking simulations, an innovative new approach methodology (NAM), to predict binding affinities between selected plastic additives and key human nuclear receptors. Specifically, 150 functional additives registered under REACH were screened against seven nuclear receptors (ERs, AR, GR, PPARs, FXR, PXR, CAR), which represent molecular initiating events (MIEs) within established adverse outcome pathways (AOPs).