Toward a Predictive Model For Nanoparticle Toxicity

Researchers report the first model to predict nanoparticle toxicity based on the materials’ water solubility and electronic properties (ACS Nano, DOI: 10.1021/nn3010087). Metal oxide nanoparticles are semiconducting materials that drive oxidation and reduction reactions in devices such as fuel cells and electronics. Andre E. Nel of the University of California, Los Angeles, wondered whether these particles’ toxicity could be linked to their band gaps, the energy gaps between occupied and unoccupied electron energy levels. He thought that if the magnitude of the band gap matched the energies required to drive oxidation and reduction reactions in human cells, the materials could disrupt these well-regulated cellular reactions, leading to cellular damage and inflammation. To test the hypothesis, Nel and his team studied 24 metal oxide nanomaterials and predicted that six would be toxic: TiO₂, Ni₂O₃, CoO, Cr₂O₃, Co₃O₄, and Mn₂O₃. When applied to human and mouse cells, five of the six predicted metal oxides—all but TiO₂—caused toxic effects, including reducing cell survival by as much as 80%. Two materials not predicted by their band gaps, CuO and ZnO, were also toxic. Nel says these metal oxides dissolve readily in water to release toxic metal ions, making solubility another crucial part of the toxicity model.