REGULATORY COOPERATION COUNCIL
NANOTECHNOLOGY INITIATIVE
Work Element 2
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Development of a classification scheme for nanomaterials regulated
under the New Substances Programs of Canada and the United
States
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1.0 Context
The Regulatory Cooperation Council (RCC) Nanotechnology Initiative aims at increasing
alignment in regulatory approaches for nanomaterials between Canada and the United States
(US)1. Towards that end, five different ‘work elements’ were created as part of the Work Plan
(Principles, Priority-Setting, Risk Assessment/Management, Commercial Information, and
Regulatory Cooperation in Areas of Emerging Technologies), each having specific final
deliverables2.
The RCC Nanotechnology initiative primarily focuses on nanomaterials considered to be new
substances regulated in Canada and the US under the Canadian Environmental Protection Act
(CEPA) and Toxic Substances Control Act (TSCA), respectively (referred to herein as
nanomaterials).
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By the 18th month of the work plan: Develop draft criteria for determining characteristics
of nanomaterials of concern/no-concern;
Beyond 18 months: Draft technical language providing common descriptions and criteria
of classes of nanomaterials, and incorporate into summary report; and
Beyond 18 months: Draft document on common CAN/US approach to definition,
characteristics and test methods for assessing nanomaterials
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This report deals with Work Element 2: “Priority-Setting”, whose overarching action item is to
identify common criteria for determining characteristics of nanomaterials of concern/no-concern.
The deliverables for this Work Element are:
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The first deliverable on the work plan was to develop draft criteria for determining
characteristics of nanomaterials of concern/no-concern. As part of this work element, the Canada
and US New Substances Programs (the Programs) have identified which nanomaterials are likely
to be of concern and no-concern from a nano-perspective. That is, nanomaterials which are likely
to behave differently on the nanometer scale when compared to their bulk or molecular
counterparts (concern) and which are not (no-concern). Currently, this list is used only for
sorting which nanomaterials need additional nano-specific consideration and which can be
considered as traditional chemicals; while exceptions will continue to be considered on a
case-by-case basis. To further develop this approach, information on how and which nanospecific properties affect organisms is still lacking and will be incorporated into this
classification scheme as it becomes available.
In addition, as conveyed to stakeholders at the RCC nanotechnology webinar on November 28,
2012, in the absence of a regulatory definition for nanomaterials, both Programs identify
nanomaterials based on: (1) a size range of 1-100nm; while the US also uses additional criteria to
identify nanomaterials: (2) a minimum of 10% of the particles need to be between 1-100nm
and/or (3) particles which exhibit properties unique to their nano size. These criteria to identify
nanomaterials continue to evolve as the science changes.
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It is expected that the outputs of this document together with the other RCC Nanotechnology
work elements will inform the development of such criteria for nanomaterials as the science
becomes available. In the absence of criteria to determine nanomaterials of concern/no-concern,
the Programs, in consultation with stakeholders, have developed a classification scheme for
nanomaterials based on similarities in chemical composition that will support the use of
analogue/read across information. The programs believe this is an appropriate first step as it
fosters discussion on the utilization of data for similar nanomaterials.
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The purpose of this classification scheme is to develop a framework to: (1) identify which
classes of nanomaterials typically require nano-specific considerations in risk assessments;
and (2) support the selection of appropriate analogue and/or read-across information to be
used in substance-specific risk assessments for nanomaterials. In addition, the scheme will
also highlight the type of information needed for characterization of the nanomaterials
within each class, thereby providing consistency within classes when requesting additional
regulatory information by the Programs.
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Using a class approach will help the Programs better utilize information from similar
nanomaterials. Ultimately, it should result in increased transparency, consistency, predictability
and alignment between the US and Canadian New Substances Programs for the assessment and
management of nanomaterials.
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This classification system is intended to be continually refined by Canada and the US as more
scientific knowledge becomes available. The Programs are hopeful the global research
community will help to validate and refine this approach.
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In this document, the terms “classification”, “groupings”, and “categories” may be used
interchangeably as all of them serve the same purpose (i.e., to organize nanomaterials for
regulatory purposes). In addition, the word classification is in no way meant to be similar to its
use in other regulatory/policy documents in Canada, the US or internationally.
1.1 Existing classification schemes for nanomaterials
There are many different ways to classify nanomaterials and each one serves a specific purpose.
These range from classifying nanomaterials by chemical composition, to similarities in shapes, to
location within the final end-use product, to risk-based analysis. The classification schemes
based on similarities in chemical composition are discussed below, while other examples can be
found in Appendix I. Some classification schemes not discussed in this document3,4 are omitted
for focus.
Classification of nanomaterials by chemical composition
One way to classify nanomaterials is by similarities in chemical composition. Such a
classification scheme could work well for regulatory programs which are based on traditional
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chemical frameworks, since it acknowledges that nanomaterials are nano-scale counterparts of
traditional chemicals.
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The Organization for Economic Cooperation and Development (OECD) Working Party on
Manufactured Nanomaterials (WPMN) is an international group aimed at understanding the
human health and environmental safety implications of manufactured nanomaterials5.The
WPMN has multiple projects underway, one of which is the safety testing of 13 different
representative nanomaterials. These 13 nanomaterials were selected according to volume and
expected presence in the respective WPMN countries (amongst other criteria). Within each 'class'
of the 13 nanomaterials, different forms of chemically similar nanomaterials were tested (e.g.,
different sizes and surface coatings of the same core nanomaterial such as titanium dioxide). One
of the intents of this testing is to be able to utilize read-across information on these chemically
similar nanomaterials. To build on this theme, the OECD WPMN is also organizing an expert
workshop in 2014 to establish categories of nanomaterials for the expected goal of feeding into
testing, read across/structure-activity relationships, risk assessment and risk management.
Discussions are already underway to ensure knowledge-transfer between the RCC and WPMN
projects (the reader is invited to contact the OECD WPMN Secretariat for more information).
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Stone et al. (2010) have developed a classification scheme for nanomaterials based on
similarities in chemical composition from an environmental perspective6. In their work, the
proposed classes are carbon, metals or metal oxides, and organic (see Figure 1 below).
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Figure 1: Classification scheme suggested by Stone et al. (2010) based on similarities in
chemical composition.
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Classification for regulatory purposes
Within the RCC context, discussions with stakeholders and other experts at the March 20th RCC
Nanotechnology Initiative Workshop7 led to several suggestions for classification schemes in
addition to the examples discussed above and in Appendix I. There were suggestions that one
could classify nanomaterials based on (if/when sufficient science is available):
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Exposures: powdery/aerosolized, liquid exposure, life cycle analysis, and consumer
exposure,
Use profiles: industrial use only, consumer, commercial,
Toxicological mode of action of nanomaterials: e.g., structure activity relationships
Physicochemical properties: e.g., surface activity, catalytic activity, electronic activity.
The aim of the classification system under the RCC Nanotechnology Initiative is to develop a
framework to support the selection of appropriate analogue and/or read-across information to be
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used in substance-specific risk assessments for nanomaterials when possible. There are currently
no nanomaterial specific regulatory frameworks for nanomaterials in either country.
The Programs acknowledge that sufficient comprehensive scientific knowledge does not yet
exist to develop a validated classification scheme of nanomaterials, as was done when the
schemes were created for traditional chemicals. The Programs nonetheless believe that a
classification scheme for nanomaterials based on similarities in chemical composition is suitable
given the existing regulatory frameworks and provides a good starting point from which to move
forward.
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Moving forward, the Programs will be using the current classification scheme to select analogues
and/or appropriate read –across information to better inform risk assessments to increase weightof-evidence, accept analogue information in lieu of testing where appropriate, and/or to provide
predictability in risk management. The Programs intend to refine this proposed classification
approach as the scientific knowledge of nanomaterials continues to increase to eventually focus
on issues such as the mode of action.
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The following section introduces the classification scheme developed as part of the RCC
Nanotechnology Initiative. It also highlights certain physicochemical parameters that may be
important in identifying if two nanomaterials share sufficient similarities to utilize read-across
and/or analogue information.
2.0 Proposed Chemical Classification Scheme
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The US EPA originally worked on developing a classification approach based on similarities in
chemical composition in 2009 drawing primarily on literature and submissions to their program.
This classification scheme was further developed under the RCC Nanotechnology Initiative’s
Work Element 2, in order to arrive at the chemical classification scheme proposed in this
document (see Figure 2). This classification scheme will be used to select appropriate
analogues/read-across information within a class and as science develops approaches for
selecting analogues/read-across information across different classes will be considered.
To seek expert input into this classification approach, a breakout session was held during the
March 20th, 2013 RCC Nanotechnology Initiative Workshop with stakeholders and experts to
further refine the proposed classification scheme. The refined scheme is presented below in
Figure 2. Stakeholders and experts at the workshop agreed that this proposed classification
scheme is an appropriate starting point7.
By identifying these classes of nanomaterials, the Programs are indicating which nanomaterials
they believe behave differently from their non-nanoscale forms. For example, gold nanoparticles
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display different properties compared to bulk gold. On the other hand, substances such as organic
polymers and pigments have not typically been found to exhibit unique nanoscale
properties/phenomena and have been on the nanometer scale only due to their synthetic route and
as such have undergone traditional chemical risk assessments. The Programs will not use this
classification approach for substances which display unique nanoscale behaviour but which are
not part of the classes described herein. The classes in Figure 2 are not exhaustive and will be
modified as new nanomaterials are notified to the Canada and the US Programs and the scientific
knowledge-base increases.
Hybrid nanomaterials (for example, a carbon nanotube with a metal oxide surface modification)
are not part of the proposed classification scheme as they fall into multiple classes. For that
reason, all hybrid nanomaterials will continue to be assessed on a case-by-case basis without the
inclusion of analogue and/or read-across information.
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The class for organics (section 2.6) was added to the classification scheme based on stakeholder
feedback received at the March 20th RCC Nanotechnology Initiative Workshop as it represents
an emerging area of nanotechnology. The Programs currently know relatively little about this
category but that is expected to change as scientific knowledge increases.
Figure 2: Proposed classification scheme based on similarities in chemical composition.
The blue boxes in Figure 2 above represent the classes for which the Programs believe that
nanomaterials can fall into based on similarities in chemical composition. In this classification
scheme, “solubility” refers to the degradation/dissolution of the particle over time as result of
surface interaction with solvent media.
The parameters listed in Figure 2 represent the intrinsic physicochemical parameters which must
be similar between two nanomaterials for them to be considered for read-across or analogue
information (e.g., if two nanomaterials within a class have the same parameters, it is likely that
they have similar behavior in wastewater treatment plants). Size in this list of parameters refers
to primary particle size. In addition to utilizing these parameters to support road-across/analogue
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information, many of these parameters are also important to understand nanomaterial fate and
behavior during risk assessments. With this in mind, it is likely that the Programs will request the
relevant amount of information (in case of identifying analogues/read-across, all the parameters
listed are required) during the regulatory process. Extrinsic parameters such as
aggregation/agglomeration behavior are used in the risk assessment process but are not part of
this classification scheme may nonetheless be requested during the regulatory process to help
assess hazard, fate, and effects.
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The classification scheme presented in this document should not be used to infer toxicological
modes of action for nanomaterials as the science for this is still emerging (e.g., Nel et al.
(2012)8). The work by Nel and others on toxicological modes of action still needs to be evaluated
for reproducibility within the proposed classes and across different classes to determine their
applicability in classification processes. However, available information on two nanomaterials
which have been found to have similar chemical composition and parameters outlined in Figure
2 could be used to increase the weight-of-evidence to support toxicology assessments. For
example, if one had two submissions for multi-walled carbon nanotubes (MWCNT) which had
sufficiently similar* parameters listed in Figure 2, data from one could potentially be used as
read-across for the other to increase the weight-of-evidence in the assessment. In addition, while
still very early, it may also be of benefit to consider extrapolations between nanoparticles of
different compositions if their physicochemical parameters are sufficiently similar* within a
class, e.g., if titanium dioxide and silicon dioxide display the same physicochemical parameters,
they may also display the same environmental fate.
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Sections 2.1-2.7 contain discussion on each of the nanomaterial classes listed in Figure 2 and
how differences in their parameters can lead to differences in their fate and effects.
2.1 Carbon Nanotubes
Carbon nanotubes (CNTs) are typically described as seamlessly rolled sheets of graphite9. These
rolls can be of single sheets (single-walled carbon nanotubes, SWCNT), or multiple sheets
(double and MWCNT). Both Programs consider CNTs as new substances that do not have any
non-nano counterparts (this includes graphite and graphene) and as such, have assessed and
continue to assess each CNT (SWCNT and MWCNT) individually.
There exists scientific information showing links between the physicochemical parameters
outlined in Figure 2 and fate and effects, such as:
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The term “sufficiently similar” is undefined and will be discussed and agreed to once this classification scheme is implemented in
the regulatory process. The authors welcome any ideas on what constitutes two parameters to be similar – e.g., differences of 10
%? Or similarity based on a minimum number of identified parameters?
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Length10 and diameter11 (aspect ratio) have been demonstrated to be physical features of
carbon nanotubes that are considered determinants for the pulmonary toxicity of carbon
nanotubes. Bussy et al. (2012) have shown linkages between the changes in surface
chemistry as a result of changing aspect ratios of CNTs and corresponding CNT-induced
inflammation;
Surface functionalization12 - Pasquini et al. (2012) have demonstrated the differences in
cell viability (invitro toxicological endpoint) as a function of surface chemistry on singlewalled carbon nanotubes, suggesting that surface chemistry may be an important
parameter to understand CNTs behavior;
Number of walls, reactivity (which includes status of end-caps), and chirality - Liu et al.
(2013)13 have reviewed the physicochemical parameters important in understanding the
toxicity of CNTs. The number of walls and reactivity (driven in part by the CNT endcaps and chirality14) were found to be important factors in understanding effects.
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The Programs believe that the physicochemical parameters listed in Figure 2 are important to
distinguish CNTs within the same class. The examples cited clearly demonstrate that differences
in these parameters can lead to differences in behaviors. If these parameters are the same (or
sufficiently similar (see footnote), it is expected that read-across and/or analogue information can
be used.
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For example, this approach was recently used on a CNT assessment in Canada. Through the
selection of an appropriate analogue using the criteria above, differences in CNT environmental
behavior and effects due to the dispersability in environmental media were identified.
2.2 Inorganic Carbon
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The Programs have limited datasets on the inorganic carbon class, which from their experience
have included graphenes (2D sp2 bonded carbon sheets15), fullerenes (soccerball-shaped carbon
macrostructures16), and nano-carbon black (carbon based filler17). CNTs were excluded from this
category because there is sufficient information indicating that their behavior is dictated by
physical attributes unique to CNTs/tubular structures (e.g., aspect ratio, etc.; see section 2.1).
Similar to the CNTs, there is a lot of literature suggesting differences in behavior and effects
based on the parameters identified in Figure 2. A lot of uncertainties remain in this class, such as
which other materials could fall into this class, and if information from one type of material can
be used to increase the weight-of-evidence for another type of material in this class.
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For graphene, Jachak et al. (2012)18 found that the biological effects of graphenes are
driven by the number of layers, surface area, lateral dimensions, stiffness, and surface
chemistry.
For fullerenes, similar findings have been discussed in a review by Sergio et al. (2012)19.
They found size, chemical modifications such as the introduction of zinc inside the
fullerenes and surface functionalization affects reactivity among other properties.
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This class of inorganic carbon is also consistent with the work done by Stone et al. (2010) on the
development of classes (see Section 1.1).
2.3 Metal Oxides and Metalloid Oxides
According to a global marketplace report20, metal oxide and metalloid oxide nanoparticles
represent one of the largest classes of nanomaterials in terms of volumes, uses, and applications.
This class does not represent a specific chemical composition, but rather generic compositional
information (MOx, MaMbOx, in which M is a metal/metalloid and O is oxygen). There is a wealth
of information on the fate and effects of metal oxides and metalloid oxides being driven by size,
shape, composition, crystal structure (e.g., titanium dioxide), surface reactivity and surface
functionalization. Horie and Fujita (2011)21 demonstrate the importance of those properties on
the effects of metal oxide and metalloid oxide nanoparticles. For simplicity, the reader is referred
to their book chapter for a detailed account on these physicochemical parameters.
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In addition to those parameters, where the metal oxides or metalloid oxides are soluble, the
solubility will need to be measured as well before read-across analogue can be considered
between two substances. The concept of dissolution of nanomaterials is currently being
discussed internationally within the OECD WPMN and within European projects on
nanomaterials to help understand how the dissolution of a nanomaterial into its ionic forms
would impact its consideration from a risk assessment perspective.
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In this document, the terms solubility, degradation of the nanomaterial surface, and dissolution
are used interchangeably and are meant to mean the release of ions from the nanoparticle in
solvent media.
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With this and the following class, only nanoparticles of the same chemical composition will be
considered for use of read-across or analogue information. For example, two nanoparticles of
titanium dioxide with similar physical-chemical characteristics can be considered for
analogue/read-across using the approach described herein. Moving forward, as Program and
scientific knowledge increases, considerations will be given to using read-across/analogues for
compounds of varying compositions when their parameters are sufficiently similar*.
2.4 Metal, Metal Salts, and Metalloid nanoparticles
Metals, metal salts, and metalloids (M0+) behave similarly to the metal oxides and metalloid
oxides (section 2.3) in terms of the important physicochemical parameters. In addition, solubility
is very important for this class, as reflected by the inclusion of the “solubility” and “oxidation
states” parameters (Figure 2). The role of solubility on fate and effects of metal, metal salts, and
metalloid nanoparticles is well documented in literature22. In their review, Casals et al. (2012)
highlighted the importance of solubility when considering the fate and effects of nanoparticles.
In biological or environmental systems, nanoparticles will likely be driven to higher or even
complete dissolution. As such nanoparticles may possess associated toxicity and environmental
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risks because they will act as a source of potentially toxic cations (e.g. silver nanoparticles have a
bactericidal effect that has been correlated with the number of released Ag+ ions).
It is important to note that measuring solubility is still complex and that uncertainties remain on
how to define and measure this property(e.g., identifying dispersions vs. solubility, identifying
and measuring degradation vs. dissolution vs. solubility, etc.)
2.5 Semiconductor quantum Dots
2.6 Organics
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Quantum dots are semiconductor nanoparticles with composition and size-dependant electronic
properties23. In addition to the importance of properties outlined in the preceding classes
(sections 2.1 to 2.4), liberation of the ions through solubility/degradation (in contrast to
dispersions) and core-shell composition are also very important. The comprehensive review by
Hardman (2006) 24 and study by Liu et. al. (2012) investigating releases of quantum dots from
nanocomposite lighting demonstrates the importance of the identified physicochemical
parameters for this class (the white boxes in Figure 2), including the key role of solubility and
core-shell composition as key parameters in understanding the fate (such as releases) and effects
of quantum dots.
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The Programs acknowledge that many organic chemical substances may be on the nanoscale, but
are not engineered on this size scale to exploit any nano-specific property. These typically
include organic dyes, polymers, and organic pigments. However, there are situations where an
organic substance, such as nanocrystalline cellulose (NCC), takes advantage of a nanoscale
property26. NCC has unique properties which include high specific strength and modulus,
optical properties, high surface area, etc.27. It is these types of substances that the Programs are
interested in and that are considered part of this class. Further discussion is required to
understand what constitutes nanoscale properties of organic substances in this class.
2.7 Other
This category includes emerging nanomaterials and/or nanomaterials with which the Programs
have had very limited experience or for which there is insufficient science to classify adequately
based on similarities in chemical composition. To date, these have included metal alloys (e.g.,
tungsten carbide28), nanoclays29, and tubular structures of metals/metal salts/metalloids30. It is
believed that for tubular structures of different metals/metal salts/metalloids, the requirements to
consider two nanomaterials similar are likely similar to those as carbon nanotubes.
During the stakeholder consultation at the March 20th, 2012 it was suggested that
bionanomaterials, which refers to substances which combine biotechnology and nanotechnology
to produce advanced functional materials31, are an emerging area that the Programs need to be
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aware of due to their potential impact to commerce. Bionanomaterials in this context does not
refer to nanomaterials interacting with an organism. The Programs have not received any
notifications for nanoparticles coupled with biological systems. From literature, an example of a
bionanomaterial can be seen in the work by Sultan et. al. 32, who have used biotechnology to
engineer synthetic DNA strands sensitive to a target and combined them with nano-scale
scaffolds.
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It is up to the discretion of the Programs to make classes and use read-across and/or analogue
information where appropriate for the nanomaterials which fall into the other category. Followup Canada - US discussions for this category will be required to ensure consistency between both
countries.
3.1 Next Steps
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3.0 Moving Forward
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The Programs intend to use the classification scheme described herein as a starting point to
increase the utilization of read-across and analogue data in the assessment of new substances
under CEPA and TSCA. The Programs will decide whether the proposed use of read-across and
analogue data by notifiers is appropriate and valid. It is expected that as scientific knowledge
increases, additional layers or tiers will be added to the proposed classification scheme, likely
targeting more specific endpoints, e.g., tiers based on toxicological modes of action. This will be
done in collaboration with stakeholders as has been done under the RCC Nanotechnology
Initiative.
In addition, the Programs intend to increase their understanding on hybrid nanomaterials (also
called second and third generation nanomaterials) and bionanomaterials (section 2.7) which are
increasingly seen in the marketplace. It is expected that the science will sufficiently evolve
within the next 3-5 years to inform on the parameters necessary to develop a class for these
substances and the possible use of read-across/analogue information. However, in the interim,
since the Programs have already started seeing hybrid nanomaterials and are currently utilizing
case-by-case approaches to assess these substances, additional discussions are needed between
the two groups to develop strategies to address this class of nanomaterials.
Finally, the Programs acknowledge that there remains uncertainty with the scientific foundation
of this proposed classification scheme and information needed to validate this approach.
However, it is expected that this will foster research on these classes to help validate and further
refine the physicochemical parameters and the boundaries around the classes.
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The research community is invited to help better the regulatory decision making of
nanomaterials by generating data on this classification scheme so it can be better refined.
3.2 Towards common terminology and definitions
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Under the RCC Nanotechnology Work Plan deliverables, the Programs were asked to consider
approaches for common terminology and definitions for nanomaterials. After discussions
between the Programs and with stakeholders at the March 20th RCC Nanotechnology Initiative
Workshop7, it was concluded that the RCC needs to collaborate with the International
Organization for Standardization (ISO) Technical Committee 229 which in part has a focus on
developing international standards associated with terminology and nomenclature35. ISO has
already developed and published several documents on terminology for nanomaterials36, and the
Programs have agreed that any terminology and nomenclature activities not be done in isolation
within Canada and the US.
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Both Programs have actively participated in this ISO committee since its inception and as a
result of the RCC will look at additional mechanisms to ensure that our needs for terminology
and definitions are provided to ISO. For nomenclature, the Programs are actively working within
ISO as part of the ISO and International Union of Pure and Applied Chemistry (IUPAC) joint
project on developing nomenclature for classes of nanomaterials37. The Programs will consider
how best to implement the outputs of these activities in their respective regulatory frameworks.
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3.3 Towards nanomaterials of concern/no-concern
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As part of the Work Element 2 deliverables, the Programs were also asked to see whether and, if
so, how they could move towards the development of classes of nanomaterials of concern/noconcern as has been done for many traditional chemicals.
By developing a classification scheme under the RCC, the Programs have taken a first step
towards identifying which nanomaterials they consider to be sufficiently different than their nonnano counterparts (these are considered to be of concern) and through omission which
nanomaterials are considered as traditional chemicals for regulatory purposes (these are
considered to be of no-concern). Currently, this list is used only for sorting which
nanomaterials need additional nano-specific consideration and which can be considered as
traditional chemicals. Indeed, there are exceptions to this and these will continue to be
considered on a case-by-case basis. To further inform this list, it needs to take into account
hazard classification – similar to how these lists are generated for traditional chemicals.
However, the Programs believe it is still early to incorporate these approaches because of the
lack of appropriate scientific information. This classification scheme will continue to evolve as
relevant scientific information is generated.
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The Programs plan on fostering research and regulatory capacity in Canada and the US to help
move us towards understanding what nano-properties are relevant for hazard and how those
properties are affect organisms. In addition, the Programs intend on continuing dialogue post
RCC (beyond 2014) and plan harmonization activities to move us towards refining our approach
on this list of nanomaterials of concern/no-concern.
3.4 Conclusion
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The Canadian and US New Substances Programs, using input from stakeholder consultations, are
proposing a classification scheme for nanomaterials based on similarities in chemical
composition to support the use of analogue/read across information in regulatory risk
assessments. Although intuitive, this is the first time regulatory programs are considering using a
classification scheme for nanomaterials in regulatory decision making to increase the utilization
of read-across and analogue data. Using a class approach will help the Programs to better utilize
information from similar nanomaterials and will provide increased transparency, consistency and
alignment between the US and Canada to stakeholders.
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Appendix I: Examples of classification schemes in literature
Classification of nanomaterials by their containing matrix
The US Army is developing a classification scheme to take into account the behaviour of the
nanomaterial in products. They have suggested the following classes: freely dispersed particles,
particles in viscous media, particles in diffuse coatings, durable coatings and composites, and
nanostructured products. This classification scheme is meant to provide data to regulators on
army-specific products along with providing improved criteria to determine potential EHS risks
associated with nanomaterials. The reader is invited to contact Jeffery Steevens
([email protected]) for more information on this project.
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The US National Institute of Occupation Safety and Handling (NIOSH) has suggested grouping
of nanomaterials by physical state to improve safe handling and reduce worker exposure38. The
suggested classes are: (a) bound of fixed nanostructures (polymer matrix); (b) liquid suspension,
liquid dispersion; (c) dry dispersible nanomaterials and agglomerates; and (d) nanoerosols and
gas phase synthesis (on substrate).
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Similar to the NIOSH approach, Hallock and colleagues39 have suggested classifying
nanomaterials by product matrix: pure nanomaterials, items contaminated with nanomaterials,
liquid suspensions, and solid matrices to ensure safe disposal. In the work by Foss Hansen and
colleagues40, the team suggests a classification approach based on the location of the
nanomaterial on the product, i.e., as part of a bulk substance (e.g., nanoelectronics), on the
surface (e.g., films), or as particles (e.g., liquid suspensions) thereby allowing one to distinguish
which nanoparticles are expected to cause exposure, which may cause exposure, and are not
expected to cause exposure to the consumer.
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Appendix II: References:
1
Available online at : http://www.actionplan.gc.ca/page/rcc-ccr/cross-sectoral
Available online at : http://www.trade.gov/rcc/documents/Nanotechnology.pdf
3
Nel, A.; Xia, T.; Mädler, L.; Li, N.Science, 2006, 311, 622-627.
4
Olson, M.; Gurian, P. J. Nanopar. Res., 2012, 14, 786.
5
Available online at :
http://www.oecd.org/env/ehs/nanosafety/sponsorshipprogrammeforthetestingofmanufacturednanomaterial
s.htm
6
Stone, V.; Nowack, B.; Baun, A.; Brink, N.; Kammer, F.; Dusinska, M.; Handy, R.; Hankin, S.;
Hassellov, M.; Joner, E.; Fernandes, T. Sci. Total Env., 2010, 408, 1745-1754.
7
Regulatory Cooperation Council Nanotechnology Initiative Multi-Stakeholder Workshop Report March
20, 2013. A copy can be obtained by contacting [email protected]
8
Nel, A.; Xia, T.; Meng, H.; Wang, X.; Lin, S.; Ji, Z.; Zhang, H. Acc. Chem. Res., 2013, 46, 607-621.
9
Baughman, R.; Zakhidov, A.; de Heer, W. Science, 2002, 297, 787-792.
10
Poland, C.A.; Duffin R.; Kinloch I.; Maynard A.; Wallace WA.; Seaton A.; Stone, V.; Brown, S.;
MacNee, W.; and Donaldson, K. Nature Nanotechnol., 2008, 3, 423-428.
11
Fenoglio, I.; Aldieri, E.; Gazzano, E.; Cesano, F.; Colonna, M.; Scarano, D.; Mazzucco, G.; Attanasio,
A.; Yakoub, Y.; Lison, D.; and Fubini, B. Chem. Res. Toxicol., 2012, 25, 74-82.
12
Pasquini, L.; Hashmi, S.; Sommer, T.; Elimelech, M.; Zimmerman, J. ES&T, 2012, 46, 6297-6305.
13
Liu, Y.; Zhao, Y.; Sun, B.; Chen, C. Acc. Chem. Res., 2013, 46, 702-713.
14
Skandani, A.; Zeineldin, R.; Al-Haik. Langmuir, 2012, 28, 7872-7879.
15
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