Rachelle D Arcega, - and Rong-Jane Chen, - and Pei-Shana Chih, - and Yi-Hsuana Huang, - and Wei-Hsianga Chang, - and Ting-Khaia Kong, - and Ching-Chang Lee, - and Trias Mahmudiono, - and Hou Chun-Chihe, - and Hsueh Wen-Chef, - and Chen Hsin-Tag, - and Chen Hsiu-Ling, - (2023) Toxicity prediction: An application of alternative testing and computational toxicology in contaminated groundwater sites in Taiwan. Journal of Environmental Management, 328 (116982). ISSN 03014797

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Abstract

Groundwater contamination remains a global threat due to its toxic effects to humans and the environment. The remediation of contaminated groundwater sites can be costly, thus, identifying the priority areas of concern is important to reduce money spent on resources. In this study, we aimed to identify and rank the priority groundwater sites in a contaminated petrochemical district by combining alternative, non-animal approaches – chemical analysis, cell-based high throughput screening (HTS), and Toxicological Priority Index (ToxPi) computational toxicology tool. Groundwater samples collected from ten different sites in a contaminated district showed pollutant levels below the detection limit, however, hepatotoxic bioactivity was demonstrated in human hepatoma HepaRG cells. Integrating the pollutants information (i.e., pollutant characteristics and concentration data) with the bioactivity data of the groundwater samples, an evidence-based ranking of the groundwater sites for future remediation was established using ToxPi analysis. The currently presented combinatorial approach of screening groundwater sites for remediation purposes can further be refined by including relevant parameters, which can boost the utility of this approach for groundwater screening and future remediation.

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