Alexa Canchola , Lillian N. Tran , Wonsik Woo , Linhui Tian , Ying-Hsuan Lin , Wei-Chun Chou
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引用次数: 0
Abstract
Emerging environmental contaminants (EECs) such as pharmaceuticals, pesticides, and industrial chemicals pose significant challenges for detection and identification due to their structural diversity and lack of analytical standards. Traditional targeted screening methods often fail to detect these compounds, making non-target analysis (NTA) using high-resolution mass spectrometry (HRMS) essential for identifying unknown or suspected contaminants. However, interpreting the vast datasets generated by HRMS is complex and requires advanced data processing techniques. Recent advancements in machine learning (ML) models offer great potential for enhancing NTA applications. As such, we reviewed key developments, including optimizing workflows using computational tools, improved chemical structure identification, advanced quantification methods, and enhanced toxicity prediction capabilities. It also discusses challenges and future perspectives in the field, such as refining ML tools for complex mixtures, improving inter-laboratory validation, and further integrating computational models into environmental risk assessment frameworks. By addressing these challenges, ML-assisted NTA can significantly enhance the detection, quantification, and evaluation of EECs, ultimately contributing to more effective environmental monitoring and public health protection.
期刊介绍:
Environmental Health publishes manuscripts focusing on critical aspects of environmental and occupational medicine, including studies in toxicology and epidemiology, to illuminate the human health implications of exposure to environmental hazards. The journal adopts an open-access model and practices open peer review.
It caters to scientists and practitioners across all environmental science domains, directly or indirectly impacting human health and well-being. With a commitment to enhancing the prevention of environmentally-related health risks, Environmental Health serves as a public health journal for the community and scientists engaged in matters of public health significance concerning the environment.