• Journal of Life Science
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• v.33 no.6
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• pp.490-497
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• 2023

Pregnant women may need to take medications to treat preexisting diseases or diseases that develop during pregnancy. However, some drugs may be fetotoxic and lead to, for example, teratogenicity and growth retardation. Predicting the fetotoxicity of drugs is thus important for the health of the mother and fetus. The fetotoxicity of many drugs has not been established because various challenges hinder the ability of researchers to determine their fetotoxicity. The need exists for in silico-based fetotoxicity assessment models, as they can modernize the testing paradigm, improve predictability, and reduce the use of animals and the costs of fetotoxicity testing. In this study, we collected data on the fetotoxicity of drugs and constructed fetotoxicity prediction models based on various machine learning algorithms. We optimized the models for more precise predictions by tuning the hyperparameters. We then performed quantitative performance evaluations. The results indicated that the constructed machine learning-based models had high performance (AUROC >0.85, AUPR >0.9) in fetotoxicity prediction. We also analyzed the feature importance of our model's predictions, which could be leveraged to identify the specific features of drugs that are strongly associated with fetotoxicity. The proposed model can be used to prescreen drugs and drug candidates at a lower cost and in less time. It provides a predictive score for fetotoxicity risk, which may be beneficial in the design of studies on fetotoxicity in human pregnancy.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.26 no.2
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• pp.119-138
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• 2016

Objectives: The purpose of this study is to review size, shape, and crystal structure-dependent toxicity of major metal oxide particles such as silicon dioxide, tungsten trioxide, aluminum oxide, and titanium dioxide as byproducts generated in semiconductor fabrication facility. Methods: To review the toxicity of major metal oxide particles, we used various reported research and review papers. The papers were searched by using websites such as Google Scholar and PubMed. Keyword search terms included '$SiO_2$(or $WO_3$ or $Al_2O_3$ or $TiO_2$) toxicity', 'health effects $SiO_2$(or $WO_3$ or $Al_2O_3$ or $TiO_2$). Additional papers were identified in references cited in the searched papers. Results: In various cell lines and organs of human and animals, cytotoxicity, genotoxicity, hepatoxicity, fetotoxicity, neurotoxicity, and histopathological changes were induced by silicon dioxide, tungsten trioxide, aluminium oxide, and titanium dioxide particles. Differences in toxicity were dependent on the cell lines, organs, doses, as well as the chemical composition, size, surface area, shape, and crystal structure of the particles. However, the doses used in the reported papers were higher than the possible exposure level in general work environment. Oxidative stress induced by the metal oxide particles plays a significant role in the expression of toxicity. Conclusions: The results cannot guarantee human toxicity of the metal oxide particles, because there is still a lack of available information about health effects on humans. In addition, toxicological studies under the exposure conditions in the actual work environment are needed.