Chemical and Biomolecular Engineering Department and Center for Environmental Implications of Nanotechnology, University of California, Los Angeles, Los Angeles, CA 90064, USA.
Acc Chem Res. 2013 Mar 19;46(3):802-12. doi: 10.1021/ar300049e. Epub 2012 Nov 8.
Because a variety of human-related activities, engineer-ed nanoparticles (ENMs) may be released to various environmental media and may cross environmental boundaries, and thus will be found in most media. Therefore, the potential environmental impacts of ENMs must be assessed from a multimedia perspective and with an integrated risk management approach that considers rapid developments and increasing use of new nanomaterials. Accordingly, this Account presents a rational process for the integration of in silico ENM toxicity and fate and transport analyses for environmental impact assessment. This approach requires knowledge of ENM toxicity and environmental exposure concentrations. Considering the large number of current different types of ENMs and that those numbers are likely to increase, there is an urgent need to accelerate the evaluation of their toxicity and the assessment of their potential distribution in the environment. Developments in high throughput screening (HTS) are now enabling the rapid generation of large data sets for ENM toxicity assessment. However, these analyses require the establishment of reliable toxicity metrics, especially when HTS includes data from multiple assays, cell lines, or organisms. Establishing toxicity metrics with HTS data requires advanced data processing techniques in order to clearly identify significant biological effects associated with exposure to ENMs. HTS data can form the basis for developing and validating in silico toxicity models (e.g., quantitative structure-activity relationships) and for generating data-driven hypotheses to aid in establishing and/or validating possible toxicity mechanisms. To correlate the toxicity of ENMs with their physicochemical properties, researchers will need to develop quantitative structure-activity relationships for nanomaterials (i.e., nano-SARs). However, as nano-SARs are applied in regulatory applications, researchers must consider their applicability and the acceptance level of false positive relative to false negative predictions and the reliability of toxicity data. To establish the environmental impact of ENMs identified as toxic, researchers will need to estimate the potential level of environmental exposure concentration of ENMs in the various media such as air, water, soil, and vegetation. When environmental monitoring data are not available, models of ENMs fate and transport (at various levels of complexity) serve as alternative approaches for estimating exposure concentrations. Risk management decisions regarding the manufacturing, use, and environmental regulations of ENMs would clearly benefit from both the assessment of potential ENMs exposure concentrations and suitable toxicity metrics. The decision process should consider the totality of available information: quantitative and qualitative data and the analysis of nanomaterials toxicity, and fate and transport behavior in the environment. Effective decision-making to address the potential impacts of nanomaterials will require considerations of the relevant environmental, ecological, technological, economic, and sociopolitical factors affecting the complete lifecycle of nanomaterials, while accounting for data and modeling uncertainties. Accordingly, researchers will need to establish standardized data management and analysis tools through nanoinformatics as a basis for the development of rational decision tools.
由于各种人为活动,工程纳米粒子(ENMs)可能会释放到各种环境介质中,并可能跨越环境边界,因此会在大多数介质中被发现。因此,必须从多媒体的角度并采用综合风险管理方法来评估 ENMs 的潜在环境影响,该方法考虑到新纳米材料的快速发展和日益增加的使用。因此,本说明提出了一种合理的方法,用于整合纳米材料毒性和归宿与传输分析,以进行环境影响评估。这种方法需要了解纳米材料毒性和环境暴露浓度。考虑到目前大量不同类型的 ENMs,而且这些数量可能会增加,因此迫切需要加速评估它们的毒性以及评估它们在环境中的潜在分布。高通量筛选(HTS)的发展现在使快速生成大量的纳米材料毒性评估数据集成为可能。然而,当 HTS 包括来自多个测定、细胞系或生物体的数据时,这些分析需要建立可靠的毒性指标。建立基于 HTS 数据的毒性指标需要先进的数据处理技术,以便清楚地识别与暴露于 ENMs 相关的显著生物学效应。HTS 数据可以作为开发和验证基于计算机的毒性模型(例如定量构效关系)的基础,并生成数据驱动的假设,以帮助建立和/或验证可能的毒性机制。为了将 ENMs 的毒性与其物理化学性质相关联,研究人员将需要为纳米材料开发定量构效关系(即纳米 SAR)。然而,随着纳米 SAR 在监管应用中的应用,研究人员必须考虑它们的适用性和假阳性相对于假阴性预测的可接受水平,以及毒性数据的可靠性。为了确定被确定为有毒的 ENMs 的环境影响,研究人员需要估计 ENMs 在空气、水、土壤和植被等各种介质中的潜在环境暴露浓度。在没有环境监测数据的情况下,ENMs 归宿和传输模型(在不同的复杂程度上)可以作为估计暴露浓度的替代方法。ENMs 的制造、使用和环境法规的风险管理决策显然将受益于对潜在 ENMs 暴露浓度和合适的毒性指标的评估。决策过程应考虑到所有可用信息:定量和定性数据以及纳米材料毒性分析,以及环境中的归宿和传输行为。要解决纳米材料的潜在影响,需要考虑影响纳米材料整个生命周期的相关环境、生态、技术、经济和社会政治因素,同时考虑数据和建模的不确定性。因此,研究人员需要通过纳米信息学建立标准化的数据管理和分析工具,作为开发合理决策工具的基础。
Acc Chem Res. 2012-11-8
Methods Mol Biol. 2013
Acc Chem Res. 2012-7-3
Int J Hyg Environ Health. 2010-12-17
Food Chem Toxicol. 2011-12-29
Nanomaterials (Basel). 2024-1-10
Nanomaterials (Basel). 2022-4-14
NanoImpact. 2019-4-6
Nanomaterials (Basel). 2020-10-15
Naunyn Schmiedebergs Arch Pharmacol. 2019-5-17