Finnish Institute of Occupational Health, New Technologies and Risks, Topeliuksenkatu 41 aA, 00250 Helsinki, Finland.
Toxicology. 2010 Mar 10;269(2-3):92-104. doi: 10.1016/j.tox.2010.01.013. Epub 2010 Jan 25.
With the increasing utilization of engineered nanomaterials (ENM), the potential exposure of workers to ENM is likely to increase significantly. Very little is known though, of the risks posed by ENM to human health, in particular concerning those characteristics that are technologically attractive: small size, high surface to mass ratio, and surface reactivity. ENM risk assessment is hampered by a lack of exposure as well as toxicity data specific to the multitude of ENM being developed. An economical approach to this problem urgently calls for intelligent testing strategies to capture essential features of ENM, thereby allowing over-arching ENM risk assessment. The data gaps of ENM risk assessment include (1) ENM aerosol standards and agreement on ENM key metrics; (2) dependable exposure scenarios, affordable monitoring technologies, exposure data and models; and (3) biomedical data on ENM translocation and toxicity, and associated testing strategies (which must be linked to the exposure scenarios). The special features of ENM do not, however, create a need to amend the current overall approach to the risk assessment of chemicals.
随着工程纳米材料（ENM）的应用越来越广泛，工人接触 ENM 的潜在风险可能会显著增加。然而，人们对 ENM 对人类健康构成的风险知之甚少，特别是对于那些具有技术吸引力的特性：小尺寸、高表面积与质量比和表面反应性。ENM 风险评估受到缺乏暴露数据和针对众多正在开发的 ENM 的毒性数据的阻碍。解决这个问题的经济方法迫切需要智能测试策略来捕捉 ENM 的基本特征，从而允许进行全面的 ENM 风险评估。ENM 风险评估的数据差距包括：（1）ENM 气溶胶标准和对 ENM 关键指标的协议；（2）可靠的暴露情景、负担得起的监测技术、暴露数据和模型；以及（3）关于 ENM 转移和毒性的生物医学数据，以及相关的测试策略（必须与暴露情景相关联）。然而，ENM 的特殊性质并没有要求修改目前对化学品风险评估的总体方法。
