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

Chemical persistence has long been recognized as a critical determinant of ecosystem and human exposure, exemplified by legacy pollutants such as DDT, PCBs, and, more recently, PFAS. Despite decades of regulation and research, robust experimental half-life data are available for only a fraction of chemicals in use, hampering their persistence assessment. Current testing frameworks, while refined, lack the efficacy to address these large data gaps, underscoring the need for innovative approaches. We argue that new approach methodologies for persistence assessment (P-NAMs)─including high-throughput (HT) experimental systems and advanced in silico models─are needed. HT-testing can bridge the gap between biodegradability screening tests and resource-intensive simulation studies. Simultaneously, HT-testing can generate large, consistent data sets needed to improve the mechanistic understanding of biotransformation and train more accurate predictive models. Integration of transformation product analysis and FAIR (findable, accessible, interoperable, and reusable) data repositories will further enhance mechanistic understanding and model reliability. We call for coordinated efforts across academia, industry, and regulatory bodies to establish standardized reporting, expand accessible data sets, and validate predictive tools. By advancing P-NAMs, the scientific community can ensure that persistence assessment evolves from a regulatory bottleneck into a driver of innovation, safeguarding human and ecosystem health and promoting safe chemical design.