27 April 2011
| General, CMST, MPNS
Quantitative Nanostructure Toxicity Relationships (QNTR): Outcome of the COST Exploratory Workshop of April 2011
The COST Exploratory Workshop on Quantitative Nanostructure Toxicity Relationships (QNTR) was held on 3 - 6 April 2011 near Maastricht in The Netherlands in order to explore the potential for computational modelling techniques to predict the biological effects of nanomaterials from their physical and chemical properties.
It brought together leaders from all areas required for the successful development of the emerging field of computational nanotoxicology, including computational modellers, experimentalists, materials scientists, chemists, biologists and toxicologists, ontologists, database developers, policy-makers and representatives from industry.
While a number of computational approaches were discussed, the focus of the workshop was on Quantitative Nanostructure Toxicity Relationships (QNTR) that use statistical or machine-learning methods such as neural networks, decision trees and support vector machines to model the relationships between the physical and chemical properties of nanomaterials and their biological effects.
Participants discussed the many requirements for the successful development of QNTR methods including the need for a commonly accepted nomenclature, frameworks and standards, the choice of appropriate mathematical descriptors of nanomaterial properties, the types of experimental data available (and also those urgently required), and the necessity of creating and maintaining supporting scientific networks.
Because of the large diversity of pristine nanomaterials and the complexity of their interactions with biological systems, the immediate requirement is for large amounts of relevant and reproducible experimental data in order to develop and validate QNTR techniques. There is a particular need to develop high-throughput in vitro assays that reflect in vivo responses, and to characterise particles as they are “seen“ by the body or organism. There was strong agreement that optimal progress and collection of the most relevant data could best be achieved by very close collaboration between modellers and experimentalists. It was concluded that effective validated QNTR methods will probably only be available for the simplest of systems in the very near future. In the mid- to long-term, QNTR techniques will need to be refined and further developed to address the more complex nanomaterial-biological systems, and it is here that both Government and industry are required to work together to ensure that the right conditions for promoting such development prevail.
There was widespread acknowledgement that the QNTR workshop was both important and timely as regulators urgently need information in order to assess potential exposures and hazards of manufactured nanomaterials, and to know when characteristics of the pristine, primary particles can be used as predictors of behaviour or those of the bioactive entity are required. Although the experimental (eco-)testing of the safety of novel nanomaterials will always be required, participants expected that computational approaches such as QNTR would help to reduce the extent of this testing with resulting savings in time, expenditure, and numbers of experimental animals. It was also recognised that QNTR may be useful in aiding the design of safer nanomaterials, again resulting in savings.
The information provided by the participants will be incorporated into two deliverables, both of which will be realised by the end of this year:
- A 10-year plan to produce QNTR-based software useful for regulators and industry (which will be published in a peer-reviewed journal),
- An application for a COST Action to support an international Community of Practice to fast-track the development of QNTR.
More information: http://www.cost.eu/events/qntr