Romeo Daina, Salieri Beatrice, Hischier Roland, Nowack Bernd, Wick Peter
Empa, Swiss Federal Laboratories for Materials Science and Technology, Particles-Biology Interactions Laboratory, Lerchenfeldstrasse 5, 9014 St. Gallen, Switzerland.
Empa, Swiss Federal Laboratories for Materials Science and Technology, Technology and Society Laboratory, Lerchenfeldstrasse 5, 9014 St. Gallen, Switzerland.
Environ Int. 2020 Apr;137:105505. doi: 10.1016/j.envint.2020.105505. Epub 2020 Jan 31.
In line with the 3R concept, nanotoxicology is shifting from a phenomenological to a mechanistic approach based on in vitro and in silico methods, with a consequent reduction in animal testing. Risk Assessment (RA) and Life Cycle Assessment (LCA) methodologies, which traditionally rely on in vivo toxicity studies, will not be able to keep up with the pace of development of new nanomaterials unless they adapt to use this new type of data. While tools and models are already available and show a great potential for future use in RA and LCA, currently none is able alone to quantitatively assess human hazards (i.e. calculate chronic NOAEL or ED values). By highlighting which models and approaches can be used in a quantitative way with the available knowledge and data, we propose an integrated pathway for the use of in vitro data in RA and LCA. Starting with the characterization of nanoparticles' properties, the pathway then investigates how to select relevant in vitro human data, and how to bridge in vitro dose-response relationships to in vivo effects. If verified, this approach would allow RA and LCA to stir up the development of nanotoxicology by giving indications about the data and quality requirements needed in risk methodologies.
根据3R概念，纳米毒理学正从基于现象学的方法转向基于体外和计算机模拟方法的机制性方法，从而减少动物试验。传统上依赖体内毒性研究的风险评估（RA）和生命周期评估（LCA）方法，除非适应使用这种新型数据，否则将无法跟上新型纳米材料的发展步伐。虽然工具和模型已经存在，并且在RA和LCA的未来应用中显示出巨大潜力，但目前没有一种能够单独定量评估人类危害（即计算慢性无观察到有害作用水平或有效剂量值）。通过强调哪些模型和方法可以利用现有知识和数据进行定量分析，我们提出了一条在RA和LCA中使用体外数据的综合途径。该途径从纳米颗粒特性的表征开始，接着研究如何选择相关的体外人体数据，以及如何将体外剂量反应关系与体内效应联系起来。如果得到验证，这种方法将使RA和LCA能够通过指明风险方法所需的数据和质量要求来推动纳米毒理学的发展。
