During a webinar earlier this afternoon, the National Nanotechnology Initiative (NNI) — spanning 25 Federal agencies engaged in nanotechnology research — released its 2011 Environmental, Health, and Safety (EHS) Research Strategy, “a comprehensive, integrated approach to produce the research data that will ensure the safe, effective, and responsible development and use of nanotechnology” in the coming years. The EHS Research Strategy, which updates a 2008 version, summarizes the current state of nano science and provides guidance to agencies as they develop their agency-specific EHS research programs. Importantly, for the first time, the research strategy includes a core area of research in predictive modeling and informatics — at the same level as nanomaterial measurement, human exposure assessment, human health, environment, and risk assessment and management.

From the EHS Research Strategy:

Expanding informatics capabilities will aid development, analysis, organization, archiving, sharing, and use of data that is acquired in nanoEHS research projects… Effective management of reliable, high-quality data will also help support advanced modeling and simulation capabilities in support of future nanoEHS R&D and nanotechnology-related risk management.

Research needs highlighted span “Big Data”…

Data acquisition: Improvements in data reliability and reproducibility can be effected quickly by leveraging the widespread use of wireless and video-enabled devices by the public and by standards development organizations to capture protocol detail through videos…

 

Data analysis: The need for sensitivity analysis in conjunction with error and uncertainty analysis is urgent for hazard and exposure estimation and the rational design of nanomaterials… Collaborative efforts in nanomaterial design [will include] curation of datasets with known uncertainties and errors, the use of sensitivity analysis to predict changes in nanomaterial properties, and the development of computational models to augment and elucidate experimental data.

 

Data sharing: Improved data sharing is a crucial need to accelerate progress in nanoscience by removing the barriers presented by the current “siloed” data environment. Because data must be curated by those who have the most intimate knowledge of how it was obtained and analyzed and how it will be used, a central repository to facilitate sharing is not an optimal solution. However, federating database systems through common data elements would permit rapid semantic search and transparent sharing over all associated databases, while leaving control and curation of the data in the hands of the experts. The use of nanomaterial ontologies to define those data elements together with their computer-readable logical relationships can provide a semantic search capability.

…and predictive modeling:

Predictive models and simulations: The turnaround times for the development and validation of predictive models is measured in years. Pilot websites, applications, and tools should be added to the NCN [Network for Computational Nanotechnology] to speed collaborative code development among relevant modeling and simulation disciplines, including the risk modeling community. The infrastructure should provide for collaborative code development by public and private scientists, code validation exercises, feedback through interested user communities, and the transfer of validated versions to centers such as NanoHUB… Collaborative efforts could supplement nanomaterial characterization measurements to provide more complete sensitivity information and structure-property relationships.

The EHS Research Strategy also enumerates a list of goals for “computational models of engineered nanomaterial (ENM) structure-property-activity relationships to support the design and development of ENMs with maximum benefit and minimum risk to humans and the environment”:

• Validate the predictive capability of in vitro and in vivo assays and employ that subset of assays in data generation to establish computational models to predict ENM behavior in humans and the environment
• Establish a standard set of physical and chemical characterization parameters, dose metrics, and biological response metrics
• Design and establish structures and ontologies for methods development, data capture, sharing, and analysis
• Evaluate and adapt as necessary existing computational models by beginning with existing models for exposure and dosimetry and using data generated from validated assays
• Use ENM exposure and dosimetry models to develop ENM structure-activity models to predict ENM behavior in humans and the environment
• Establish training sets and beta test sites to refine and validate ENM structure-activity models
• Disseminate ENM structure-activity models through publicly accessible nanotechnology websites

Check out the EHS Research Plan in its entirety here. And read more about its release today in a blog post by the White House Office of Science and Technology Policy (OSTP).

NCN Solicitation

A related point: the National Science Foundation (NSF) recently issued a solicitation for the Network for Computational Nanotechnology (NCN). The NCN — a facility that provides researchers the tools to explore nanoscale phenomena through theory, modeling, and simulation — was established in 2002 at Purdue University as part of the NNI. The current NCN award expires in fall 2012, and this solicitation is an opportunity for the broader community to compete to reconfigure it. Letters of intent must be submitted by Dec. 16, and full proposals are due Jan. 17, 2012.

(Contributed by Erwin Gianchandani, CCC Director)