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        0 IN SILICO TOOLS TO PRIORITIZE TRANSFORMATION PRODUCTS OF PESTICIDES ORIGINATING FROM DRINKING WATER TREATMENTS: S-METOLACHLOR AS A PROOF OF PRINCIPLE

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        Report Adele Selma Ferrario.pdf (2.321Mb)
        Publication date
        2023
        Author
        Ferrario, Adele
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        Summary
        Environmental contaminants are present in water sources, so drinking water treatments are applied. However, these contaminants can be transformed into new chemicals – called transformation products (TPs) – often unknown and undetected by analytical techniques (Gogoi et al., 2018; Brunner et al., 2019; Zahn et al., 2019; Menger et al., 2021). Therefore, predicting TPs' formation during drinking water treatments must be addressed (Kiefer et al., 2019). At the same time, predictive toxicology can help identify TPs of great toxicological concern and steer further analysis. However, there is an urge to assemble available methods to design and implement the next-generation risk assessment (NGRA) in regulatory frameworks (Pallocca et al., 2022). Therefore, this research focused on developing a rational scheme for predicting TPs formation because of drinking water treatments, their physicochemical characteristics (PCC), and toxicological hazards. The effectiveness of freely available in silico tools in predicting, prioritizing, and evaluating TPs was discussed here. S-metolachlor TPs were used as proof of the applicability of the methodology. The reliability of the methods varies depending on the specific reaction pathway, PCC, or endpoint considered. The Chemical Transformation Simulator (CTS) and enviPath were demonstrated to be the best available combination for predicting TPs originating from drinking water treatments. EpiSuiteTM was recommended for the PCC evaluation, and VEGA QSAR for the hazard prioritization. Whether the predicted prioritized S-metolachlor TPs could represent a human health risk via drinking water or an environmental concern for their impact on ecosystems requires further research, as well as the development of an automation workflow for the use of the applied in silico tools, is required.
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        https://studenttheses.uu.nl/handle/20.500.12932/43422
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