Nontarget Screening Analysis Combined with Computational Toxicology: A Promising Solution for Identification and Risk Assessment of Environmental Pollutants in the Big Data Era
Abstract
Synthetic chemicals are intensively utilized in modern societies, and their mixtures pose significant health and ecological threats. Nontarget screening (NTS) analysis allows for the simultaneous chemical identification and quantitative reporting of tens of thousands of chemicals in complex environmental matrices, whereas the computational toxicology (CT) serves as another high-throughput means of rapidly and comprehensively screening chemicals for toxicity. To date, there has been a lack of guidance on how to combine NTS experiments and CT for the risk assessment of chemical mixtures and the prioritization of pollutants. In this perspective, the combination of two "big data" approaches in field studies is systematically proposed. The basic principles of performing NTS and CT in environmental studies are briefly outlined. The "top-down" and "bottom-up" strategies are proposed to summarize the two technologies during the experimental design stage, in accordance with research objectives and available information and tools. Following this, a universal framework combining NTS and CT is thoroughly explored. Six recommendations for future research are highlighted to enhance the utilization of this paradigm, involving multistep combination, multidisciplinary database, application platform, multilayered functionality, effect validation, and standardization.
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