Background

To solve current issues using big data, solve current issues related to the semiconductor and electronics industry, I tried to establish the data for each toxicity mechanism for adverse outcome pathway (AOP) for the exposure.

Objective

I planned to increase the efficiency of human hazard assessment by searching, analyzing, and linking test data on the relationship between key events occurred at each level, which are the biological targets of chemicals in semiconductor manufacturing.

Results

It was found that 48 kinds of chemicals had 11 AOPs, while 103 chemicals had multiple AOPs, and 26 had case evidence. As a result of AOP analysis, it was found that a total of 320 chemicals had 42 AOPs, and 190 major chemicals corresponded to 11 AOPs. It was found necessary to develop a complex AOP and secure an (inhalation or dermal) exposure scenario for combined exposure at work. As a comparative search (41 out of 190 chemicals) of biomarkers specific to occupational diseases, 12 biomarkers were found to be related to breast cancer. The AOPs for 50 specific chemicals were presented, together with occupational disease-specific AOPs and key events relationship from 50 chemicals, and taxonomic classification for each AOP analysis could be found. With a comparative search, 41 out of 190 chemicals were associated with specific biomarkers for occupational diseases, and 12 mRNA or protein biomarkers were found to be related to breast cancer by cross-validation with the attached Table 24 of the Enforcement Regulations of the OSHAct and the CTD.

Conclusion

The mechanism of occupational diseases caused by chemicals was presented, together with pathological preventions. I believe that a strategy is needed to expand the target organization for each chemical by linking with activities, such as work environment measurement, and cooperating with screening items and methods suitable for toxic chemicals, like AOP tools.

中文翻译：

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应用不良结果通路框架预测半导体制造业中化学品的毒性

背景

为了利用大数据解决当前问题，解决与半导体和电子行业相关的当前问题，我尝试建立针对暴露的不良结果通路 (AOP) 的每种毒性机制的数据。

客观的

我计划通过搜索、分析和链接每个级别发生的关键事件之间关系的测试数据来提高人类危害评估的效率，这些事件是半导体制造中化学品的生物学目标。

结果

发现48种化学品有11种AOP，103种化学品有多种AOP，26种有案例证据。通过 AOP 分析发现，共有 320 种化学品有 42 个 AOP，190 种主要化学品对应 11 个 AOP。发现有必要开发一个复杂的 AOP 并确保（吸入或皮肤）暴露场景，以便在工作中进行联合暴露。作为对职业病特异性生物标志物的比较搜索（190 种化学物质中的 41 种），发现 12 种生物标志物与乳腺癌有关。介绍了 50 种特定化学品的 AOP，以及 50 种化学品的职业病特定 AOP 和关键事件关系，并且可以找到每种 AOP 分析的分类分类。通过比较搜索，

结论

介绍了化学品引起职业病的机理，并提出了病理预防措施。我认为需要一种策略，通过与工作环境测量等活动联系起来，并与适合有毒化学品的筛选项目和方法（如 AOP 工具）合作，扩大每种化学品的目标组织。