Terry Wilkins

Nano(Q)SAR: Challenges, pitfalls and perspectives

Abstract Regulation for nanomaterials is urgently needed, and the drive to adopt an intelligent testing strategy is evident. Such a strategy will not only provide economic benefits but will also reduce moral and ethical concerns arising from animal testing. For regulatory purposes, such an approach is promoted by REACH, particularly the use of quantitative structure–activity relationships [(Q)SAR] as a tool for the categorisation of compounds according to their physicochemical and toxicological properties. In addition to compounds, (Q)SAR has also been applied to nanomaterials in the form of nano(Q)SAR. Although (Q)SAR in chemicals is well established, nano(Q)SAR is still in early stages of development and its successful uptake is far from reality. This article aims to identify some of the pitfalls and challenges associated with nano-(Q)SARs in relation to the categorisation of nanomaterials. Our findings show clear gaps in the research framework that must be addressed if we are to have reliable predictions from such models. Three major barriers were identified: the need to improve quality of experimental data in which the models are developed from, the need to have practical guidelines for the development of the nano(Q)SAR models and the need to standardise and harmonise activities for the purpose of regulation. Of these three, the first, i.e. the need to improve data quality requires immediate attention, as it underpins activities associated with the latter two. It should be noted that the usefulness of data in the context of nano-(Q)SAR modelling is not only about the quantity of data but also about the quality, consistency and accessibility of those data.

Accurate and interpretable nanoSAR models from genetic programming-based decision tree construction approaches.

Abstract The number of engineered nanomaterials (ENMs) being exploited commercially is growing rapidly, due to the novel properties they exhibit. Clearly, it is important to understand and minimize any risks to health or the environment posed by the presence of ENMs. Data-driven models that decode the relationships between the biological activities of ENMs and their physicochemical characteristics provide an attractive means of maximizing the value of scarce and expensive experimental data. Although such structure–activity relationship (SAR) methods have become very useful tools for modelling nanotoxicity endpoints (nanoSAR), they have limited robustness and predictivity and, most importantly, interpretation of the models they generate is often very difficult. New computational modelling tools or new ways of using existing tools are required to model the relatively sparse and sometimes lower quality data on the biological effects of ENMs. The most commonly used SAR modelling methods work best with large datasets, are not particularly good at feature selection, can be relatively opaque to interpretation, and may not account for nonlinearity in the structure–property relationships. To overcome these limitations, we describe the application of a novel algorithm, a genetic programming-based decision tree construction tool (GPTree) to nanoSAR modelling. We demonstrate the use of GPTree in the construction of accurate and interpretable nanoSAR models by applying it to four diverse literature datasets. We describe the algorithm and compare model results across the four studies. We show that GPTree generates models with accuracies equivalent to or superior to those of prior modelling studies on the same datasets. GPTree is a robust, automatic method for generation of accurate nanoSAR models with important advantages that it works with small datasets, automatically selects descriptors, and provides significantly improved interpretability of models.

Application of isothermal titration calorimetry in evaluation of protein–nanoparticle interactions

Nanoparticles (NPs) offer a number of advantages over small organic molecules for controlling protein behaviour inside the cell. Protein binding to the surface of NPs depends on their surface characteristics, composition and method of preparation (Mandal et al. in J Hazard Mater 248–249:238–245, 2013). It is important to understand the binding affinities, stoichiometries and thermodynamical parameters of NP–protein interactions in order to see which interaction will have toxic and hazardous consequences and thus to prevent it. On the other side, because proteins are on the brink of stability, they may experience interactions with some types of NPs that are strong enough to cause denaturation or significantly change their conformations with concomitant loss of their biological function. Structural changes in the protein may cause exposure of new antigenic sites, “cryptic” peptide epitopes, potentially triggering an immune response which can promote autoimmune disease (Treuel et al. in ACS Nano 8(1):503–513, 2014). Mechanistic details of protein structural changes at NP surface have still remained elusive. Understanding the formation and persistence of the protein corona is critical issue; however, there are no many analytical methods which could provide detailed information about the NP–protein interaction characteristics and about protein structural changes caused by interactions with nanoparticles. The article reviews recent studies in NP–protein interactions research and application of isothermal titration calorimetry (ITC) in this research. The study of protein structural changes upon adsorption on nanoparticle surface and application of ITC in these studies is emphasized. The data illustrate that ITC is a versatile tool for evaluation of interactions between NPs and proteins. When coupled with other analytical methods, it is important analytical tool for monitoring conformational changes in proteins.

Electrochemical and morphological investigation of silver and zinc modified calcium phosphate bioceramic coatings on metallic implant materials

In our research nanostructured silver and zinc doped calcium-phosphate (CaP) bioceramic coatings were prepared on commonly used orthopaedic implant materials (Ti6Al4V). The deposition process was carried out by the pulse current technique at 70 °C from electrolyte containing the appropriate amount of Ca(NO3)2 and NH4H2PO4 components. During the electrochemical deposition Ag(+) and Zn(2+) ions were introduced into the solution. The electrochemical behaviour and corrosion rate of the bioceramic coatings were investigated by potentiodynamic polarization and Electrochemical Impedance Spectroscopy (EIS) measurements in conventional Ringers solution in a three electrode open cell. The coating came into contact with the electrolyte and corrosion occurred during immersion. In order to achieve antimicrobial properties, it is important to maintain a continuous release of silver ions into physiological media, while the bioactive CaP layer enhances the biocompatibility properties of the layer by fostering the bone cell growth. The role of Zn(2+) is to shorten wound healing time. Morphology and composition of coatings were studied by Scanning Electron Microscopy, Transmission Electron Microscopy and Energy-dispersive X-ray spectroscopy. Differential thermal analyses (DTA) were performed to determine the thermal stability of the pure and modified CaP bioceramic coatings while the structure and phases of the layers were characterized by X-ray diffraction (XRD) measurements.

Evaluation of existing control measures in reducing health and safety risks of engineered nanomaterials

While the risk management of engineered nanomaterials (ENMs) receives significant attention, there is still a limited understanding of how to select optimal risk management measures (RMMs) for controlling and mitigating the risks associated with exposure to ENMs. Clearly, there exists a need to expand current risk management practices to ensure safe production, handling and use of ENMs. Moreover, the performance of the existing RMMs should be re-evaluated for ENMs since control options that are proven to be effective for preventing or limiting risks associated with traditional particles might give unsatisfactory results in the case of nano-scale particles. This paper has brought together the evidence on the adequacy of traditional controls to minimize potential health and environmental risks resulting from exposure to ENMs. The aim here is to advance our understanding of the risk management approaches relevant for ENMs, and ultimately to support the selection of the most suitable RMMs when handling ENMs. To that end, evaluative evidence collected from the review of relevant literature and survey of nanotechnology institutions are combined and summarised to understand the level of protection offered by each control measure, as well as the relative costs of their implementation. The findings suggest that most relevant risk control options are based on isolating people from hazard through engineering measures (e.g. ventilation and chemical fume hoods) or personal protective equipment (PPE), rather than eliminating hazard at source (e.g. substitution). Although control measures related to the modification of ENMs have high efficiency in the occupational risk control hierarchy, they are not widely employed since there is currently a high degree of uncertainty regarding the impact of manipulating nano-characteristics on the performance of final product. Lastly, despite its low cost, PPE is the least effective category in the occupational risk control hierarchy and should not be used on its own when significant risk reduction is required. Clearly, further quantitative data is needed to fully assess the feasibility and cost-effectiveness of risk control options to prevent risks from exposure to ENMs. When there is little information on the efficiency of control measures specific to ENMs, the default efficiencies can be used for initial assessment purposes although it should not be considered exhaustive.

Characterization of Nanoparticle Batch-To-Batch Variability

A central challenge for the safe design of nanomaterials (NMs) is the inherent variability of NM properties, both as produced and as they interact with and evolve in, their surroundings. This has led to uncertainty in the literature regarding whether the biological and toxicological effects reported for NMs are related to specific NM properties themselves, or rather to the presence of impurities or physical effects such as agglomeration of particles. Thus, there is a strong need for systematic evaluation of the synthesis and processing parameters that lead to potential variability of different NM batches and the reproducible production of commonly utilized NMs. The work described here represents over three years of effort across 14 European laboratories to assess the reproducibility of nanoparticle properties produced by the same and modified synthesis routes for four of the OECD priority NMs (silica dioxide, zinc oxide, cerium dioxide and titanium dioxide) as well as amine-modified polystyrene NMs, which are frequently employed as positive controls for nanotoxicity studies. For 46 different batches of the selected NMs, all physicochemical descriptors as prioritized by the OECD have been fully characterized. The study represents the most complete assessment of NMs batch-to-batch variability performed to date and provides numerous important insights into the potential sources of variability of NMs and how these might be reduced.