| Chapter title |
An Integrated Data-Driven Strategy for Safe-by-Design Nanoparticles: The FP7 MODERN Project
|
|---|---|
| Chapter number | 9 |
| Book title |
Modelling the Toxicity of Nanoparticles
|
| Published in |
Advances in experimental medicine and biology, February 2017
|
| DOI | 10.1007/978-3-319-47754-1_9 |
| Pubmed ID | |
| Book ISBNs |
978-3-31-947752-7, 978-3-31-947754-1
|
| Authors |
Martin Brehm, Alexander Kafka, Markus Bamler, Ralph Kühne, Gerrit Schüürmann, Lauri Sikk, Jaanus Burk, Peeter Burk, Tarmo Tamm, Kaido Tämm, Suman Pokhrel, Lutz Mädler, Anne Kahru, Villem Aruoja, Mariliis Sihtmäe, Janeck Scott-Fordsmand, Peter B. Sorensen, Laura Escorihuela, Carlos P. Roca, Alberto Fernández, Francesc Giralt, Robert Rallo |
| Editors |
Lang Tran, Miguel A. Bañares, Robert Rallo |
| Abstract |
The development and implementation of safe-by-design strategies is key for the safe development of future generations of nanotechnology enabled products. The safety testing of the huge variety of nanomaterials that can be synthetized is unfeasible due to time and cost constraints. Computational modeling facilitates the implementation of alternative testing strategies in a time and cost effective way. The development of predictive nanotoxicology models requires the use of high quality experimental data on the structure, physicochemical properties and bioactivity of nanomaterials. The FP7 Project MODERN has developed and evaluated the main components of a computational framework for the evaluation of the environmental and health impacts of nanoparticles. This chapter describes each of the elements of the framework including aspects related to data generation, management and integration; development of nanodescriptors; establishment of nanostructure-activity relationships; identification of nanoparticle categories; hazard ranking and risk assessment. |
X Demographics
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|---|---|---|
| Spain | 2 | 29% |
| United Kingdom | 1 | 14% |
| United States | 1 | 14% |
| Germany | 1 | 14% |
| Ireland | 1 | 14% |
| Unknown | 1 | 14% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 57% |
| Scientists | 3 | 43% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 31 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 39% |
| Student > Master | 3 | 10% |
| Professor | 2 | 6% |
| Student > Ph. D. Student | 2 | 6% |
| Other | 2 | 6% |
| Other | 4 | 13% |
| Unknown | 6 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 4 | 13% |
| Environmental Science | 2 | 6% |
| Agricultural and Biological Sciences | 2 | 6% |
| Engineering | 2 | 6% |
| Materials Science | 2 | 6% |
| Other | 6 | 19% |
| Unknown | 13 | 42% |