Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Advanced tools for the safety assessment of nanomaterials


Engineered nanomaterials (ENMs) have tremendous potential to produce beneficial technological impact in numerous sectors in society. Safety assessment is, of course, of paramount importance. However, the myriad variations of ENM properties makes the identification of specific features driving toxicity challenging. At the same time, reducing animal tests by introducing alternative and/or predictive in vitro and in silico methods has become a priority. It is important to embrace these new advances in the safety assessment of ENMs. Indeed, remarkable progress has been made in recent years with respect to mechanism-based hazard assessment of ENMs, including systems biology approaches as well as high-throughput screening platforms, and new tools are also emerging in risk assessment and risk management for humans and the environment across the whole life-cycle of nano-enabled products. Here, we highlight some of the key advances in the hazard and risk assessment of ENMs.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Enabling a harmonized knowledge infrastructure supporting environment, health and safety (EHS) assessment of nanomaterials.
Fig. 2: Systems biology paradigm for ENM hazard and risk assessment focusing on the identification of a minimal yet most informative set of features with which to predict toxicity.


  1. 1.

    Maynard, A. D. et al. Safe handling of nanotechnology. Nature 444, 267–269 (2006).

    Article  Google Scholar 

  2. 2.

    Krug, H. F. Nanosafety research--are we on the right track? Angew. Chem. Int. Ed. Engl. 53, 12304–12319 (2014).

    Google Scholar 

  3. 3.

    Valsami-Jones, E. & Lynch, I. NANOSAFETY. How safe are nanomaterials? Science 350, 388–389 (2015).

    Article  Google Scholar 

  4. 4.

    Sayes, C. M. & Warheit, D. B. Characterization of nanomaterials for toxicity assessment. Wiley Interdiscip. Rev. Nanomed. Nanobiotechnol. 1, 660–670 (2009).

    Article  Google Scholar 

  5. 5.

    Fadeel, B., Fornara, A., Toprak, M. S. & Bhattacharya, K. Keeping it real: the importance of material characterization in nanotoxicology. Biochem. Biophys. Res. Commun. 468, 498–503 (2015).

    Article  Google Scholar 

  6. 6.

    Walkey, C. D. & Chan, W. C. Understanding and controlling the interaction of nanomaterials with proteins in a physiological environment. Chem. Soc. Rev. 41, 2780–2799 (2012).

    Article  Google Scholar 

  7. 7.

    Monopoli, M. P., Åberg, C., Salvati, A. & Dawson, K. A. Biomolecular coronas provide the biological identity of nanosized materials. Nat. Nanotech. 7, 779–786 (2012).

    Article  Google Scholar 

  8. 8.

    Cohen, Y., Rallo, R., Liu, R. & Liu, H. H. In silico analysis of nanomaterials hazard and risk. Acc. Chem. Res. 46, 802–812 (2013).

    Article  Google Scholar 

  9. 9.

    Winkler, D. A. Recent advances, and unresolved issues, in the application of computational modelling to the prediction of the biological effects of nanomaterials. Toxicol. Appl. Pharmacol. 299, 96–100 (2016).

    Article  Google Scholar 

  10. 10.

    Fadeel, B. et al. There’s plenty of room at the forum: potential risks and safety assessment of engineered nanomaterials. Nanotoxicology 1, 73–84 (2007).

    Article  Google Scholar 

  11. 11.

    Savolainen, K. et al. Risk assessment of engineered nanomaterials and nanotechnologies--a review. Toxicology 269, 92–104 (2010).

    Article  Google Scholar 

  12. 12.

    Hussain, S. M. et al. At the crossroads of nanotoxicology in vitro: past achievements and current challenges. Toxicol. Sci. 147, 5–16 (2015).

    Article  Google Scholar 

  13. 13.

    Valsami-Jones, E., Lynch, I. & Charitidis, C. A. Nanomaterial ontologies for nanosafety: a rose by any other name…. J. Nanomed. Res. 3, 00070 (2016).

    Article  Google Scholar 

  14. 14.

    Worth, A. et al. Evaluation of the Availability and Applicability of Computational Approaches in the Safety Assessment of Nanomaterials (Joint Research Centre, 2017);

  15. 15.

    Hastings, J. et al. eNanoMapper: harnessing ontologies to enable data integration for nanomaterial risk assessment. J. Biomed. Semant. 6, 1–15 (2015).

    Article  Google Scholar 

  16. 16.

    Jeliazkova, N. et al. The eNanoMapper database for nanomaterial safety information. Beilstein J. Nanotechnol. 6, 1609–1634 (2015).

    Article  Google Scholar 

  17. 17.

    Farcal, L. et al. Comprehensive in vitro toxicity testing of a panel of representative oxide nanomaterials: first steps towards an intelligent testing strategy. PLoS ONE 10, e0127174 (2015).

    Article  Google Scholar 

  18. 18.

    Collins, A. R. et al. High throughput toxicity screening and intracellular detection of nanomaterials. Wiley Interdiscip. Rev. Nanomed. Nanobiotechnol. 9, e1413 (2017).

    Article  Google Scholar 

  19. 19.

    Richard, A. M. et al. ToxCast chemical landscape: paving the road to 21st century toxicology. Chem. Res. Toxicol. 29, 1225–1251 (2016).

    Article  Google Scholar 

  20. 20.

    Nel, A. E. & Malloy, T. F. Policy reforms to update chemical safety testing. Science 355, 1016–1018 (2017).

    Article  Google Scholar 

  21. 21.

    Anguissola, S., Garry, D., Salvati, A., O’Brien, P. J. & Dawson, K. A. High content analysis provides mechanistic insights on the pathways of toxicity induced by amine-modified polystyrene nanoparticles. PLoS ONE 9, e108025 (2014).

    Article  Google Scholar 

  22. 22.

    Harris, G. et al. Iron oxide nanoparticle toxicity testing using high-throughput analysis and high-content imaging. Nanotoxicology 9, 87–94 (2015).

    Article  Google Scholar 

  23. 23.

    Liu, R. et al. Classification NanoSAR development for cytotoxicity of metal oxide nanoparticles. Small 7, 1118–1126 (2011).

    Article  Google Scholar 

  24. 24.

    Rallo, R. et al. Self-organizing map analysis of toxicity-related cell signaling pathways for metal and metal oxide nanoparticles. Environ. Sci. Technol. 45, 1695–1702 (2011).

    Article  Google Scholar 

  25. 25.

    George, S. et al. Use of a high-throughput screening approach coupled with in vivo zebrafish embryo screening to develop hazard ranking for engineered nanomaterials. ACS Nano 5, 1805–1817 (2011).

    Article  Google Scholar 

  26. 26.

    Liu, R. et al. Automated phenotype recognition for zebrafish embryo based in vivo high throughput toxicity screening of engineered nano-materials. PLoS ONE 7, e35014 (2012).

    Article  Google Scholar 

  27. 27.

    Marchese Robinson, R. L. et al. How should the completeness and quality of curated nanomaterial data be evaluated? Nanoscale 8, 9919–9943 (2016).

    Article  Google Scholar 

  28. 28.

    Nel, A. et al. Nanomaterial toxicity testing in the 21st century: use of a predictive toxicological approach and high-throughput screening. Acc. Chem. Res. 46, 607–621 (2013).

    Article  Google Scholar 

  29. 29.

    Briffa, S. M. et al. Development of scalable and versatile nanomaterial libraries for nanosafety studies: polyvinylpyrrolidone (PVP) capped metal oxide nanoparticles. RSC Adv. 7, 3894–3906 (2017).

    Article  Google Scholar 

  30. 30.

    Hansjosten, I. et al. Microscopy-based high-throughput assays enable multi-parametric analysis to assess adverse effects of nanomaterials in various cell lines. Arch. Toxicol. 92, 633–649 (2018).

    Article  Google Scholar 

  31. 31.

    Gallud, A. et al. Cytotoxicity screening of a panel of 31 nanomaterials in the human monocytic cell line THP.1 versus primary human monocyte-derived macrophages: assessing the role of surface modification. In New Tools and Approaches for Nanomaterial Safety Assessment: Book of Abstracts (2017);

  32. 32.

    Hongisto, V. et al. High-throughput screening approach evaluated toxicity of 31 engineered nanomaterials generated for the NANOSOLUTIONS project. In New Tools and Approaches for Nanomaterial Safety Assessment : Book of Abstracts (2017);

  33. 33.

    Walkey, C. D. et al. Protein corona fingerprinting predicts the cellular interaction of gold and silver nanoparticles. ACS Nano 8, 2439–2455 (2014).

    Article  Google Scholar 

  34. 34.

    Collins, F. S., Gray, G. M. & Bucher, J. R. TOXICOLOGY. Transforming environmental health protection. Science 319, 906–907 (2008).

    Article  Google Scholar 

  35. 35.

    Sturla, S. J. et al. Systems toxicology: from basic research to risk assessment. Chem. Res. Toxicol. 27, 314–329 (2014).

    Article  Google Scholar 

  36. 36.

    Hartung, T. et al. Systems toxicology: real world applications and opportunities. Chem. Res. Toxicol. 30, 870–882 (2017).

    Article  Google Scholar 

  37. 37.

    Costa, P. M. & Fadeel, B. Emerging systems biology approaches in nanotoxicology: towards a mechanism-based understanding of nanomaterial hazard and risk. Toxicol. Appl. Pharmacol. 299, 101–111 (2016).

    Article  Google Scholar 

  38. 38.

    Nymark, P. et al. A data fusion pipeline for generating and enriching adverse outcome pathway descriptions. Toxicol. Sci. 162, 264–275 (2018).

    Article  Google Scholar 

  39. 39.

    Fortino, V. & Greco, D. ENM SAFETY CLASSIFIER – a multi-view feature selection and classification algorithm for prediction of engineered nanomaterials (ENM) safety. In New Tools and Approaches for Nanomaterial Safety Assessment : Book of Abstracts (2017);

  40. 40.

    Kinaret, P. et al. Network analysis reveals similar transcriptomic responses to intrinsic properties of carbon nanomaterials in vitro and in vivo. ACS Nano 11, 3786–3796 (2017).

    Article  Google Scholar 

  41. 41.

    Bornholdt, J. et al. Identification of gene transcription start sites and enhancers responding to pulmonary carbon nanotube exposure in vivo. ACS Nano 11, 3597–3613 (2017).

    Article  Google Scholar 

  42. 42.

    Hristozov, D. R., Gottardo, S., Critto, A. & Marcomini, A. Risk assessment of engineered nanomaterials: a review of available data and approaches from a regulatory perspective. Nanotoxicology 6, 880–898 (2012).

    Article  Google Scholar 

  43. 43.

    Park, M. et al. Hazard evaluation in GUIDENANO: a web-based guidance tool for risk assessment and mitigation of nano-enabled products. In New Tools and Approaches for Nanomaterial Safety Assessment: Book of Abstracts (2017);

  44. 44.

    Subramanian, V. et al. Sustainable nanotechnology decision support system: bridging risk management, sustainable innovation and risk governance. J. Nanopart. Res. 8, 1–13 (2016).

    Google Scholar 

  45. 45.

    Zabeo, A. et al. SUNDS, a multi-criteria decision support system for nanotechnology risk assessment and management. In New Tools and Approaches for Nanomaterial Safety Assessment : Book of Abstracts (2017);

  46. 46.

    Dekkers, S. et al. Towards a nanospecific approach for risk assessment. Regul. Toxicol. Pharmacol. 80, 46–59 (2016).

    Article  Google Scholar 

  47. 47.

    Oomen, A. G. et al. Grouping and read-across approaches for risk assessment of nanomaterials. Int. J. Environ. Res. Public Health 12, 13415–13434 (2015).

    Article  Google Scholar 

  48. 48.

    González-Gálvez, D., Janer, G., Vilar, G., Vílchez, A. & Vázquez-Campos, S. The life cycle of engineered nanoparticles. Adv. Exp. Med. Biol. 947, 41–69 (2017).

    Article  Google Scholar 

  49. 49.

    Fernández-Rosas, E. et al. Influence of nanomaterial compatibilization strategies on polyamide nanocomposites properties and nanomaterial release during the use phase. Environ. Sci. Technol. 50, 2584–2594 (2016).

    Article  Google Scholar 

  50. 50.

    Mitrano, D. M., Lombi, E., Dasilva, Y. A. & Nowack, B. Unraveling the complexity in the aging of nanoenhanced textiles: a comprehensive sequential study on the effects of sunlight and washing on silver nanoparticles. Environ. Sci. Technol. 50, 5790–5799 (2016).

    Article  Google Scholar 

  51. 51.

    Wohlleben, W. et al. A pilot interlaboratory comparison of protocols that simulate aging of nanocomposites and detect released fragments. Environ. Chem. 11, 402–418 (2014).

    Article  Google Scholar 

  52. 52.

    Nowack, B. et al. Meeting the needs for released nanomaterials required for further testing - the SUN approach. Environ. Sci. Technol. 50, 2747–2753 (2016).

    Article  Google Scholar 

  53. 53.

    Tsang, M. P., Kikuchi-Uehara, E., Sonnemann, G. W., Aymonier, C. & Hirao, M. Evaluating nanotechnology opportunities and risks through integration of life-cycle and risk assessment. Nat. Nanotech. 12, 734–739 (2017).

    Article  Google Scholar 

  54. 54.

    Linkov, I. et al. Integrate life-cycle assessment and risk analysis results, not methods. Nat. Nanotech. 12, 740–743 (2017).

    Article  Google Scholar 

  55. 55.

    Guinée, J. B., Heijungs, R., Vijver, M. G. & Peijnenburg, W. J. G. M. Setting the stage for debating the roles of risk assessment and life-cycle assessment of engineered nanomaterials. Nat. Nanotech. 12, 727–733 (2017).

    Article  Google Scholar 

  56. 56.

    Bishop, L. et al. In vivo toxicity assessment of occupational components of the carbon nanotube life cycle to provide context to potential health effects. ACS Nano 11, 8849–8863 (2017).

    Article  Google Scholar 

  57. 57.

    Rasmussen, K. et al. Review of achievements of the OECD Working Party on Manufactured Nanomaterials’ Testing and Assessment Programme. From exploratory testing to test guidelines. Regul. Toxicol. Pharmacol. 74, 147–160 (2016).

    Article  Google Scholar 

  58. 58.

    Fadeel, B. Systems biology in nanosafety research. Nanomed. (Lond.) 10, 1039–1041 (2015).

    Article  Google Scholar 

Download references


The authors and their laboratories were supported, in part, by the European Commission through the Seventh Framework Programme (FP7-eNANOMAPPER, grant no. 604134; FP7-GUIDENANO, grant no. 604387; FP7-NANOMILE, grant no. 310451; FP7-NANOSOLUTIONS, grant no. 309329; FP7-SUN, grant no. 604305). We thank all the project partners for invaluable contributions to these projects, and the project officers for their guidance.

Author information



Corresponding author

Correspondence to Kai Savolainen.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Fadeel, B., Farcal, L., Hardy, B. et al. Advanced tools for the safety assessment of nanomaterials. Nature Nanotech 13, 537–543 (2018).

Download citation

Further reading


Quick links

Find nanotechnology articles, nanomaterial data and patents all in one place. Visit Nano by Nature Research