title: Predictive models for nanotoxicology: current challenges and future opportunities.
abstract: Characterizing the risks posed by nanomaterials is extraordinarily complex because these materials can have a wide range of sizes, shapes, chemical compositions and surface modifications, all of which may affect toxicity. There is an urgent need for a testing strategy that can rapidly and efficiently provide a screening approach for evaluating the potential hazard of nanomaterials and inform the prioritization of additional toxicological testing where necessary. Predictive toxicity models could form an integral component of such an approach by predicting which nanomaterials, as a result of their physico-chemical characteristics, have potentially hazardous properties. Strategies for directing research towards predictive models and the ancillary benefits of such research are presented here.
authors.affiliation: Dept. of Environmental Health Sciences, Johns Hopkins University, Bloomberg School of Public Health, USA; Institute for Work and Health, Universities of Lausanne and Geneva, Switzerland. katherine.clark@hospvd.ch
authors.forename: Katherine A
authors.initials: KA
authors.lastname: Clark
authors.forename: Ronald H
authors.initials: RH
authors.lastname: White
authors.forename: Ellen K
authors.initials: EK
authors.lastname: Silbergeld
mesh_terms: D000818:Animals; D005544:Forecasting; D006801:Humans; D008962:Models, Theoretical; D049329:Nanostructures / Q000633:toxicity*; D018675:Toxicity Tests / Q000639:trends*; D014116:Toxicology / Q000379:methods / Q000639:trends*