Maojo et al Information on early research in nanomedicine primarily consisted of journal publications, results of workshops and symposia, and reporting in the public media on these and other innovations and their benefits and risks. Later, a broader agenda for nanoinformatics evolved as the field progressed. Better characterization of nanomaterial struc- tures, their physico-chemical properties, and their in vitro and in vivo interactions was necessary.66,67 For example, the US National Cancer Institute (NCI) established the Nano- technology Characterization Laboratory as an integral part of its Cancer Nanotechnology Plan. It was evident that better instrumentation was needed in the laboratory, factory, and field for experiment, production process control, and separa- tion techniques. This was due to the wide variability in their internal structures, surface ligand distributions, impurities, and transformational changes such as protein coatings. New positive and negative controls were needed for existing standard analytical methods. Similarly, new meth- ods were needed to standardize newly emerging sensing, delivery, release, and imaging modalities. Quantifying data reproducibility, uncertainty, and error of these new or modi- fied methods would require ruggedness testing and sensitivity analysis of the methods. As the field evolved, a demand for reference and study materials grew, both for interlaboratory testing as well as for consistent studies of material trans- formation due to aging, handling, and contamination. In addition, it became evident that a nanomaterial registry was needed to provide unique identifiers for nanomaterials at the level of individual manufactured lots. The lot-to-lot property variations and libraries of well-characterized nanomaterials with controlled variations in their component structures were also needed to elucidate the correlation between the structures and their properties. Finally, there was a need for an extensive, coordinated terminology for nanomaterials, their structures, and their properties. Such terminology would allow a more unam- biguous interpretation of the accuracy and reliability of data developed by researchers in different disciplines and different material providers. The availability of standard materials and material libraries soon led to efforts to formulate quantita- tive structure–activity relationships for these materials.68 At the same time, more extensive modeling and simula- tion was needed to provide a detailed understanding of the mechanisms of efficacy and toxicity. Similarly, it required an improved understanding of nanomaterials production, modification, transformation, and disposal – which could be met only through multilevel modeling. An ultimate goal for this activity was improving data quality both for experiment 3870 submit your manuscript | www.dovepress.com Dovepress Dovepress and modeling and simulation. In parallel, this would lead to improve risk-assessment capability for the design of nano- material products and for evaluating their possible effects on the environment and human health and safety.66,67,69 State of the art and present challenges The previous examples should be viewed from an informa- tional perspective: is there a relevant role for informatics to support research, development, and translation in most of these nanomedical applications? Our answer is yes. Most of these examples included issues such as the development of large databases, device control, new biomedical imag- ing modalities, computerized decision support systems, the management and exchange of enormous amounts of heterogeneous data and knowledge, and/or creating models and simulators for characterizing nanoparticles and their efficacy and toxicity. Examples of nanomedical applications are now increasing rapidly in scientific publications such as the International Journal of Nanomedicine (which is nearing its first 1000 papers at the time of writing). A major problem is that the science of nanomaterial– biological interactions is still at a very early stage. This means that we do not know yet how to engineer nanoparticles to minimize toxic effects in animals and on the environment. Modeling and simulation are essential here. Data mining of large databases of results from in vitro and in vivo experiments will be needed to help predict their possible side effects – as mentioned above. Nanoinformatics methods will be central to integrating many different methodologies involving discrete and continuous modeling, design, simulation, experimenta- tion, visualization, and interpretation techniques. All this should improve our understanding of the risks presented by nanomaterials. A systematic nomenclature for nanoparticle formulations and characterization is sorely needed for improving clarity and standardization in searching, locating, and comparing data on specific nanostructures within large preclinical and clinical databases. At the same time, the development of such a nomenclature would involve text mining of the complex scientific literature. Current approaches are based almost entirely on simple statistical associations among short seg- ments of text. The use of novel, “visual” nano-ontologies could provide greater semantic content, together with research on more advanced methods of text mining from the literature. As mentioned, the choice of unique material identifiers is an important subtopic of ongoing research by the new Nanoma- terials Registry supported jointly by the NCI, the National International Journal of Nanomedicine 2012:7