Frameworks and tools for risk assessment of manufactured nanomaterials.

Commercialization of nanotechnologies entails a regulatory requirement for understanding their environmental, health and safety (EHS) risks. Today we face challenges to assess these risks, which emerge from uncertainties around the interactions of manufactured nanomaterials (MNs) with humans and the environment. In order to reduce these uncertainties, it is necessary to generate sound scientific data on hazard and exposure by means of relevant frameworks and tools. The development of such approaches to facilitate the risk assessment (RA) of MNs has become a dynamic area of research. The aim of this paper was to review and critically analyse these approaches against a set of relevant criteria. The analysis concluded that none of the reviewed frameworks were able to fulfill all evaluation criteria. Many of the existing modelling tools are designed to provide screening-level assessments rather than to support regulatory RA and risk management. Nevertheless, there is a tendency towards developing more quantitative, higher-tier models, capable of incorporating uncertainty into their analyses. There is also a trend towards developing validated experimental protocols for material identification and hazard testing, reproducible across laboratories. These tools could enable a shift from a costly case-by-case RA of MNs towards a targeted, flexible and efficient process, based on grouping and read-across strategies and compliant with the 3R (Replacement, Reduction, Refinement) principles. In order to facilitate this process, it is important to transform the current efforts on developing databases and computational models into creating an integrated data and tools infrastructure to support the risk assessment and management of MNs.

[1]  Lei Zhang Functionalization of single walled carbon nanotubes , 2006 .

[2]  Jo Anne Shatkin,et al.  Nanotechnology: Health and Environmental Risks , 2008 .

[3]  Steffen Foss Hansen,et al.  NanoRiskCat: a conceptual tool for categorization and communication of exposure potentials and hazards of nanomaterials in consumer products , 2013, Journal of Nanoparticle Research.

[4]  R W Scholz,et al.  Engineered nanomaterials in rivers--exposure scenarios for Switzerland at high spatial and temporal resolution. , 2011, Environmental pollution.

[5]  W. D. de Jong,et al.  The kinetics of the tissue distribution of silver nanoparticles of different sizes. , 2010, Biomaterials.

[6]  A. Boxall,et al.  Detection and characterization of engineered nanoparticles in food and the environment , 2008, Food additives & contaminants. Part A, Chemistry, analysis, control, exposure & risk assessment.

[7]  Andrew P Worth,et al.  A theoretical framework for predicting the oxidative stress potential of oxide nanoparticles , 2011, Nanotoxicology.

[8]  Reinhard Kreiling,et al.  A decision-making framework for the grouping and testing of nanomaterials (DF4nanoGrouping). , 2015, Regulatory toxicology and pharmacology : RTP.

[9]  Wouter Fransman,et al.  Conceptual model for assessment of inhalation exposure to manufactured nanoparticles , 2011, Journal of Exposure Science and Environmental Epidemiology.

[10]  Till Zimmermann,et al.  Influences of use activities and waste management on environmental releases of engineered nanomaterials. , 2015, The Science of the total environment.

[11]  Albert Duschl,et al.  Development of an on-line exposure system to determine freshly produced diesel engine emission-induced cellular effects. , 2013, Toxicology in vitro : an international journal published in association with BIBRA.

[12]  Craig A. Poland,et al.  Nanotoxicity: challenging the myth of nano-specific toxicity. , 2013, Current opinion in biotechnology.

[13]  Björn A. Sandén,et al.  Challenges in Exposure Modeling of Nanoparticles in Aquatic Environments , 2011 .

[14]  Dick Roelofs,et al.  Integrating transcriptomics into triad‐based soil‐quality assessment , 2014, Environmental toxicology and chemistry.

[15]  D Geraci,et al.  Risk assessment model of occupational exposure to nanomaterials , 2009, Human & experimental toxicology.

[16]  Lang Tran,et al.  ITS-NANO - Prioritising nanosafety research to develop a stakeholder driven intelligent testing strategy , 2014, Particle and Fibre Toxicology.

[17]  Patrick L. Gurian,et al.  Risk assessment strategies as nanomaterials transition into commercial applications , 2012, Journal of Nanoparticle Research.

[18]  Taimur Hassan,et al.  HDAT: web-based high-throughput screening data analysis tools , 2013 .

[19]  Eva Roblegg,et al.  Assessment of Long-Term Effects of Nanoparticles in a Microcarrier Cell Culture System , 2013, PloS one.

[20]  Sir,et al.  Nanomaterials under REACH. Nanosilver as a case study , 2009 .

[21]  Zhiqiang Hu,et al.  Potential nanosilver impact on anaerobic digestion at moderate silver concentrations. , 2012, Water research.

[22]  Andrew P. Worth,et al.  QSAR modeling of nanomaterials. , 2011, Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology.

[23]  Theo Vermeire,et al.  Risk assessment of chemicals : an introduction , 2007 .

[24]  Jason M Unrine,et al.  Ceria-engineered nanomaterial distribution in, and clearance from, blood: size matters. , 2012, Nanomedicine.

[25]  Albert Duschl,et al.  Biocompatible micro-sized cell culture chamber for the detection of nanoparticle-induced IL8 promoter activity on a small cell population , 2011, Nanoscale research letters.

[26]  Jason M Unrine,et al.  Brain distribution and toxicological evaluation of a systemically delivered engineered nanoscale ceria. , 2010, Toxicological sciences : an official journal of the Society of Toxicology.

[27]  Robert Landsiedel,et al.  Hazard identification of inhaled nanomaterials: making use of short-term inhalation studies , 2012, Archives of Toxicology.

[28]  Jerzy Leszczynski,et al.  Using nano-QSAR to predict the cytotoxicity of metal oxide nanoparticles. , 2011, Nature nanotechnology.

[29]  Robert Rallo,et al.  Association rule mining of cellular responses induced by metal and metal oxide nanoparticles. , 2014, The Analyst.

[30]  M. Marinovich,et al.  Risk Assessment of Products of Nanotechnologies , 2009 .

[31]  Elizabeth A. Casman,et al.  Modeling nanosilver transformations in freshwater sediments. , 2013, Environmental science & technology.

[32]  Eric A. Grulke,et al.  Biodistribution and oxidative stress effects of a systemically-introduced commercial ceria engineered nanomaterial , 2009 .

[33]  Dick Roelofs,et al.  Transcriptome assembly and microarray construction for Enchytraeus crypticus, a model oligochaete to assess stress response mechanisms derived from soil conditions , 2013, BMC Genomics.

[34]  José María Navas,et al.  Graphene nanoplatelets spontaneously translocate into the cytosol and physically interact with cellular organelles in the fish cell line PLHC-1. , 2014, Aquatic toxicology.

[35]  R. Furth Possibilities and limitations of vaccination , 2005, Infection.

[36]  E. Cummins,et al.  A Risk Assessment Framework for Assessing Metallic Nanomaterials of Environmental Concern: Aquatic Exposure and Behavior , 2011, Risk analysis : an official publication of the Society for Risk Analysis.

[37]  Dana Kühnel,et al.  The OECD expert meeting on ecotoxicology and environmental fate--towards the development of improved OECD guidelines for the testing of nanomaterials. , 2014, The Science of the total environment.

[38]  B. Nowack,et al.  Exposure modeling of engineered nanoparticles in the environment. , 2008, Environmental science & technology.

[39]  Michael Goodman,et al.  Distribution, elimination, and biopersistence to 90 days of a systemically introduced 30 nm ceria-engineered nanomaterial in rats. , 2012, Toxicological sciences : an official journal of the Society of Toxicology.

[40]  Christoph Studer,et al.  Sameness: The regulatory crux with nanomaterial identity and grouping schemes for hazard assessment. , 2015, Regulatory toxicology and pharmacology : RTP.

[41]  Anders Baun,et al.  NanoRiskCat – a conceptual decision support tool for nanomaterials , 2011 .

[42]  Sergio Gómez,et al.  Structural Patterns in Complex Systems Using Multidendrograms , 2014, Entropy.

[43]  K. Hungerbühler,et al.  Comprehensive probabilistic modelling of environmental emissions of engineered nanomaterials. , 2014, Environmental pollution.

[44]  Helmut Rechberger,et al.  Practical handbook of material flow analysis , 2003 .

[45]  Jerzy Leszczynski,et al.  Predicting water solubility and octanol water partition coefficient for carbon nanotubes based on the chiral vector , 2007, Comput. Biol. Chem..

[46]  Igor Linkov,et al.  Environmental risk analysis for nanomaterials: Review and evaluation of frameworks , 2012, Nanotoxicology.

[47]  Judith C. Madden,et al.  Development of computational models for the prediction of the toxicity of nanomaterials , 2018 .

[48]  J. Figueira,et al.  A survey on stochastic multicriteria acceptability analysis methods , 2008 .

[49]  P. Swuste,et al.  Evaluating the Control Banding Nanotool: a qualitative risk assessment method for controlling nanoparticle exposures , 2009 .

[50]  Claudia Röhl,et al.  Manufactured nanomaterials: categorization and approaches to hazard assessment , 2014, Archives of Toxicology.

[51]  D van de Meent,et al.  Heteroaggregation and sedimentation rates for nanomaterials in natural waters. , 2014, Water research.

[52]  Robert T. Clemen,et al.  Making Hard Decisions with DecisionTools , 2013 .

[53]  Teresa F. Fernandes,et al.  The MARINA Risk Assessment Strategy: A Flexible Strategy for Efficient Information Collection and Risk Assessment of Nanomaterials , 2015, International journal of environmental research and public health.

[54]  J. M. Navas,et al.  Internalization and cytotoxicity of graphene oxide and carboxyl graphene nanoplatelets in the human hepatocellular carcinoma cell line Hep G2 , 2013, Particle and Fibre Toxicology.

[55]  J. Leszczynski,et al.  A new approach to the characterization of nanomaterials : Predicting Young's modulus by correlation weighting of nanomaterials codes , 2006 .

[56]  Derk H Brouwer,et al.  Control banding approaches for nanomaterials. , 2012, The Annals of occupational hygiene.

[57]  Eugenia Valsami-Jones,et al.  A strategy for grouping of nanomaterials based on key physico-chemical descriptors as a basis for safer-by-design NMs , 2014 .

[58]  Ian Lerche,et al.  Environmental Risk Analysis , 2001 .

[59]  Christie M Sayes,et al.  A framework for grouping nanoparticles based on their measurable characteristics , 2013, International journal of nanomedicine.

[60]  Eva Roblegg,et al.  Reaction of monocytes to polystyrene and silica nanoparticles in short-term and long-term exposures. , 2014, Toxicology research.

[61]  Jim E Riviere,et al.  Comparison of quantum dot biodistribution with a blood-flow-limited physiologically based pharmacokinetic model. , 2009, Nano letters.

[62]  P. Swuste,et al.  Application of a pilot control banding tool for risk level assessment and control of nanoparticle exposures. , 2008, The Annals of occupational hygiene.

[63]  T. Xia,et al.  Development of structure-activity relationship for metal oxide nanoparticles. , 2013, Nanoscale.

[64]  Marco Vighi,et al.  SCCP (Scientific Committee on Consumer Products) / SCHER (Scientific Committee on Health& Environment Risks) / SCENIHR (Scientific Committee on Emerging and Newly- Identified Health Risks) opinion on: Risk assessment methodologies and approaches for genotoxic and carcinogenic substances , 2009 .

[65]  Fadri Gottschalk,et al.  Stochastic fate analysis of engineered nanoparticles in incineration plants , 2014 .

[66]  Bernd Nowack,et al.  Flows of engineered nanomaterials through the recycling process in Switzerland. , 2015, Waste management.

[67]  Wouter Fransman,et al.  LICARA nanoSCAN - A tool for the self-assessment of benefits and risks of nanoproducts. , 2016, Environment international.

[68]  Reynold Sequeira,et al.  Risk analysis and protection measures in a carbon nanofiber manufacturing enterprise: an exploratory investigation. , 2009, The Science of the total environment.

[69]  T. Puzyn,et al.  Toward the development of "nano-QSARs": advances and challenges. , 2009, Small.

[70]  Fadri Gottschalk,et al.  A probabilistic method for species sensitivity distributions taking into account the inherent uncertainty and variability of effects to estimate environmental risk , 2013, Integrated environmental assessment and management.

[71]  Mark R Wiesner,et al.  The use of Bayesian networks for nanoparticle risk forecasting: model formulation and baseline evaluation. , 2012, The Science of the total environment.

[72]  Teresa F. Fernandes,et al.  Risk Assessment of Engineered Nanomaterials, State of the Art and Roadmap for Future Research , 2013 .

[73]  Khara Grieger,et al.  A relative ranking approach for nano-enabled applications to improve risk-based decision making: a case study of Army materiel , 2014, Environment Systems and Decisions.

[74]  Andrey A Toropov,et al.  Mutagenicity: QSAR - quasi-QSAR - nano-QSAR. , 2015, Mini reviews in medicinal chemistry.

[75]  Tomasz Puzyn,et al.  Nano-quantitative structure-activity relationship modeling using easily computable and interpretable descriptors for uptake of magnetofluorescent engineered nanoparticles in pancreatic cancer cells. , 2014, Toxicology in vitro : an international journal published in association with BIBRA.

[76]  Peter Wick,et al.  Toward the development of decision supporting tools that can be used for safe production and use of nanomaterials. , 2013, Accounts of chemical research.

[77]  Arturo A. Keller,et al.  Global life cycle releases of engineered nanomaterials , 2013, Journal of Nanoparticle Research.

[78]  Hugh J. Byrne,et al.  Concern-driven integrated approaches to nanomaterial testing and assessment – report of the NanoSafety Cluster Working Group 10 , 2013, Nanotoxicology.

[79]  Jacintha Ellers,et al.  Effects of a natural toxin on life history and gene expression of Eisenia andrei , 2014, Environmental toxicology and chemistry.

[80]  Antonio Marcomini,et al.  Review of decision analytic tools for sustainable nanotechnology , 2015, Environment Systems and Decisions.

[81]  Stephan Barcikowski,et al.  Cytotoxicity and ion release of alloy nanoparticles , 2012, Journal of Nanoparticle Research.

[82]  Roland W. Scholz,et al.  Probabilistic material flow modeling for assessing the environmental exposure to compounds: Methodology and an application to engineered nano-TiO2 particles , 2010, Environ. Model. Softw..

[83]  Antonio Marcomini,et al.  Risk assessment of engineered nanomaterials: a review of available data and approaches from a regulatory perspective , 2012, Nanotoxicology.

[84]  K. Hungerbühler,et al.  Estimation of cumulative aquatic exposure and risk due to silver: contribution of nano-functionalized plastics and textiles. , 2008, The Science of the total environment.

[85]  I. Linkov,et al.  Risk-based classification system of nanomaterials , 2009 .

[86]  Jerzy Leszczynski,et al.  Predicting water solubility of congeners: chloronaphthalenes--a case study. , 2009, Journal of hazardous materials.

[87]  Andrew D Maynard,et al.  Nanotechnology: the next big thing, or much ado about nothing? , 2007, The Annals of occupational hygiene.

[88]  Dik van de Meent,et al.  Multimedia Modeling of Engineered Nanoparticles with SimpleBox4nano: Model Definition and Evaluation , 2014, Environmental science & technology.

[89]  Miriam Dwek,et al.  Functionalization of single-walled carbon nanotubes and their binding to cancer cells , 2012, International journal of nanomedicine.

[90]  David J. Hansen,et al.  A model of the oxidation of iron and cadmium sulfide in sediments , 1996 .

[91]  Jim E Riviere,et al.  Pharmacokinetics of nanomaterials: an overview of carbon nanotubes, fullerenes and quantum dots. , 2009, Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology.

[92]  R. Scholz,et al.  Modeled environmental concentrations of engineered nanomaterials (TiO(2), ZnO, Ag, CNT, Fullerenes) for different regions. , 2009, Environmental science & technology.

[93]  Antonio Marcomini,et al.  Demonstration of a modelling-based multi-criteria decision analysis procedure for prioritisation of occupational risks from manufactured nanomaterials , 2016, Nanotoxicology.

[94]  R. Scholz,et al.  Possibilities and limitations of modeling environmental exposure to engineered nanomaterials by probabilistic material flow analysis , 2010, Environmental toxicology and chemistry.

[95]  Geert Cornelis,et al.  A signal deconvolution method to discriminate smaller nanoparticles in single particle ICP-MS , 2014 .

[96]  Keld Alstrup Jensen,et al.  NanoSafer vs. 1.1 Nanomaterial risk assessment using first order modeling , 2013 .

[97]  W. D. de Jong,et al.  Novel insights into the risk assessment of the nanomaterial synthetic amorphous silica, additive E551, in food , 2015, Nanotoxicology.

[98]  Elizabeth A. Casman,et al.  Stream dynamics and chemical transformations control the environmental fate of silver and zinc oxide nanoparticles in a watershed-scale model. , 2015, Environmental science & technology.

[99]  F. Gottschalk,et al.  Engineered nanomaterials in water and soils: A risk quantification based on probabilistic exposure and effect modeling , 2013, Environmental toxicology and chemistry.

[100]  Antonio Marcomini,et al.  Species sensitivity weighted distribution for ecological risk assessment of engineered nanomaterials: The n‐TiO2 case study , 2015, Environmental toxicology and chemistry.

[101]  Antonio Marcomini,et al.  Grouping and Read-Across Approaches for Risk Assessment of Nanomaterials , 2015, International journal of environmental research and public health.

[102]  C. Berndt,et al.  Biocompatibility of transition metal-substituted cobalt ferrite nanoparticles , 2014, Journal of Nanoparticle Research.

[103]  Geert Cornelis,et al.  Improving the accuracy of single particle ICPMS for measurement of size distributions and number concentrations of nanoparticles by determining analyte partitioning during nebulisation , 2014 .