Prof. Wilhelmus Jozef Gerardus Maria Peijnenburg
University of Leiden, Netherlands
Abstract: Increasing concerns about the adverse effects of persistent organic pollutants (POPs) have induced a societal shift towards replacing POPs by less hydrophobic compounds. This has in turn, however, caused novel concerns for this emerging class of chemicals that are typically hydrophilic, mobile and toxic. Thereupon, there is increased concern on their environmental persistence. To reduce the latter concerns, whilst as efficient as possible assessing adverse impacts of emerging compounds in an early stage of development of the emerging compounds, there is increased focus on developing and validating in silico methods for prediction of their fate and effect properties. This contribution will provide an overview of the shift in concerns and corresponding shift in regulatory attention of POPs to more hydrophilic, persistent, mobile, and toxic (PMT) chemicals. Furthermore, an approach will be demonstrated of applying Artificial Intelligence and Machine Learning (AI/ML) in prediction of the toxicity profile of organic chemicals for a suite of aquatic organisms of different trophic levels. The models developed basically cover a major part of the chemical universe, as based of over 93,000 toxicity records, and deal with acute as well as chronic toxicity. Furthermore, the application of the models for the design of chemicals that are safe-by-design, will be highlighted and the development of a classification models that can directly be implemented in risk assessment, is presented.
Host：Assist. Prof. Yang Liu
EEH Early Career Board Member
Kunming University of Science and Technology
Time：3:00pm July 12, 2022 (Beijing time)
Zoom ID: 816 9975 7155
Bilibili: 25002335
