| 英文摘要 |
This report is based on the US Tox21 and ToxCast results to explore the in vitro toxicity testing results of the substance of unknown or variable composition, complex reaction products or biological materials (UVCBs) through in vitro toxicity testing or computational simulation. Also, by combining the high-throughput screening toxicology database and computational toxicology to complete the preliminary establishment of the high-throughput platform of chemical hazard assessment and risk prediction for the future usage on new and existing chemical substances and environmental pollutant related chemicals’ risk assessment and management. This report had compiled a chemical list of 210 chemicals along with related information from the Taiwan emergence chemical incidents and contaminated sites since 2005. The Read Across Guidelines (and databases used in the read-across application) proposed by the developed countries or international organizations were collected to build the Taiwan Chemical Substance Read Across Procedure. The read across application has been carried out with examples based on the Taiwan Chemical Substance Read Across Procedure. The read across prediction for 1,1,2-trichloroethane and toluene by MACCS fingerprint showed a closest result to its experimental results, while for 1,1,2,2-tetrachloroethane, the analogs obtained by PubChem, Circular and Extended fingerprints showed a better prediction on LD50, NOAEL and LOAEL. Furthermore, the information and variables required to assess and to manage the multiple chemicals spill to the environment were also compiled. The managing principles to handle the multiple chemical spill into the environment were explored and consolidated. Moreover, the collection of.latest chemical sampling method and transmission model were completed. An exploration and identification of complex chemical substances and its hazard from the local contaminated site has been done.The internationally published alternative test guidelines were used to build the relevant high-throughput screening (HTS) and high content screening (HCS) test modules using 4 cell lines and evaluating 11 toxicity endpoints including cell death, 3 liver cell metabolic enzyme activities, mitochondrial damage, oxidative stress, 2 endocrine disrupting effects, cell cycle arrest, apoptosis, and micronuclei assay. The selected chemical substances and samples acquiring from the environment will be applied to relevant test modules for toxicity assessment. The results of the test model building show that the liver enzyme activity model needs to be calibrated, and the rest of the models can provide a certain accuracy level for subsequent analysis. Samples from the environment have undergone liver toxicity-related model tests, and it has been shown that samples 24, 34, 37, 38, 39, 40, and 41 have liver toxicity. The hierarchical clustering method algorithm of the Toxicity Estimation Software Tool (T.E.S.T.) module in Quantitative Structure Activity Relationship (QSAR) prediction model showed a better result for the rat oral LD50 toxicity classification with an accuracy of 66.7%. The reproductive and developmental toxicity prediction in all of the QSAR models showed poor specificity performance for external verification, however, the concordance performance for all QSAR models are greater than 70%, which indicates that the overall prediction of the models is still convincing. Hence, QSAR could be an emerging tool for rapid assessing and screening the environmental complex contaminants and organic components. The chemical list mentioned in the earlier part (172 chemicals with CASRN) were merged with the ToxCast database chemical list (8574 chemicals with CASRN), and the merged chemical substances list was then used to build the self-organizing map (SOM) module.Then, the chemicals in bin 217 and bin 305 of SOM were priorly selected for the read-across procedure building and verification, in order to understand the read across application to predict the hazard and toxicity data for unknown chemicals. The results of 16 scenarios show that among 191 chemicals, isopropanol, methyl tert-butyl ether, 1,1,2,2-tetrachloroethane and cumene are the chemicals that get the high Toxicological Priority Index (ToxPi) score, should be given priority attention. Besides, the information source of the parameters and the setting of parameter weights will affect the priority ranking of chemicals. So that the parameter weights should be set according to the issues of concern will make the evaluation results more suitable for the evaluation purpose.
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