| Literature DB >> 29662451 |
Lisa Accomasso1, Caterina Cristallini2, Claudia Giachino1.
Abstract
The use of nanomaterials in medicine has grown very rapidly, leading to a concern about possible health risks. Surely, the application of nanotechnology in medicine has many significant potentialities as it can improve human health in at least three different ways: by contributing to early disease diagnosis, improved treatment outcomes and containment of health care costs. However, toxicology or safety assessment is an integral part of any new medical technology and the nanotechnologies are no exception. The principle aim of nanosafety studies in this frame is to enable safer design of nanomedicines. The most urgent need is finding and validating novel approaches able to extrapolate acute in vitro results for the prediction of chronic in vivo effects and to this purpose a few European initiatives have been launched. While a "safe-by-design" process may be considered as utopic, "safer-by-design" is probably a reachable goal in the field of nanomedicine.Entities:
Keywords: nanomaterial; nanomedicine; nanosafety; risk assessment; risk minimization
Year: 2018 PMID: 29662451 PMCID: PMC5890110 DOI: 10.3389/fphar.2018.00228
Source DB: PubMed Journal: Front Pharmacol ISSN: 1663-9812 Impact factor: 5.810
Existing and emerging methods used as part of an ATS for NM evaluation.
| Genotoxicity | Rapid measurement of DNA damage, chromosomal damage; detection of upregulated DNA damage signaling pathways | - MN (Micronucleus assay) | Many factors can artificially influence assay results, as material and environment | Nelson et al., |
| QSAR (Quantitative Structure Activity Relationships) | Prediction of nanomaterial exposure-dose-response | Steps of data assembling, structure characterization, model construction, model evaluation, and lastly interpretation of mechanisms | Small number of data sets | Winkler, |
| SSDs (species sensitivity distributions) | Estimation of the maximum acceptable concentrations of chemicals in environmental risk assessment | Computational approaches | Few data known | Chen et al., |
| Band gap analysis | Prediction of toxic potential using metal oxide conduction band energy levels | Limited to metal based nanomaterials | Zhang et al., | |
| Cytotoxicity | Screening of nanomaterial-induced cytotoxicity | - Cellular metabolic activity | Time-consuming, labor-intensive, complex, and in some instances unreliable owing to NM interferences | Cimpan et al., |
| OMICS | Identification of new pathways and mechanisms in nanotoxicity not visible in conventional testing | 1.1.1 Epigenomics—miRNomics | Request for high sample quality (freezing, protection against degradation) | Fröhlich, |
| High-content analysis | Capacity for monitoring a range of morphometric, functional, and biochemical properties of cells | Simultaneous identification of different parameters using fluorescence | Possible fluorescence-dye toxicity Limitation in adequate cell line | Brayden et al., |