Biomedical Engineering Reference
In-Depth Information
smallest change in the position of atoms near edges, corners, surface steps, and defects. The mecha-
nisms of the interatomic interactions between NPs and biological molecules are not well understood.
Comprehension of the mechanisms of such interactions will aid safe production and utilization of the
nanomaterials. Computational studies are helpful to understand the precise nature of interparticle
interactions, the structure of the interface, and the packing of arrays and superstructures that are dif-
ficult to probe experimentally [194]. However, similar to experimentalists who face several issues,
computational nanoscientists also have various challenges; for example, simulations involving many
NPs are computationally too intensive and not feasible using advanced
ab initio
or density functional
theory (DFT) approaches; convergence problems often occur in dealing with large molecules.
Experimental studies have concluded that the toxicity of carbon-based nanomaterials depends
on a wide range of properties such as structures (single walled or multi walled), length and aspect
ratios (in case of CNTs), surface area, surface charge, degree of aggregation, extent of oxidation,
attached functional group(s), method of manufacturing, morphology, concentration, and dose [195].
Theoretical and computational nanoscientists should carefully consider all such physical param-
eters, which are intrinsically linked with toxicity of materials, before making predictions about
risks of nanostructures.
19.10.2 q
uaNtItatIve
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tructure
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ctIvIty
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elatIoNshIps
for
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aNoMaterIals
In fact, the toxicity properties of nanomaterials have been investigated by various groups of research-
ers, but considerable uncertainties in NPs' mechanism of toxicity still exist. Indeed, many studies
proved much higher toxicity displayed by some of the NPs in comparison to bulk-size particles. For
example, it is well known that metal oxide NPs possess higher toxicity than bulk-size counterparts
of the same chemical composition [196].
The large number of NPs and the variety of their characteristics including sizes and coatings
suggest that the only rational approach that avoids testing of every single NP is to find relationship
between NP properties (i.e., physicochemical characteristics) and their toxicity. The current risk
assessment paradigms, particularly in regulatory submissions for drugs and chemicals, generally
depend on standardized methodologies. REACH legislation introduced in Europe allows computa-
tional tools in replacing experimental tests in some cases. Some computational tools, for example,
QSAR [197], are essential for increasing throughput, reducing the burden of animal testing, provid-
ing details of the toxicity mechanisms, and generating novel hypotheses for risk assessment [198].
In the case of QSAR, the approach is useful not only in making predictions, but also in refining
the existing risk assessment paradigms. As one of the examples, it is known that QSAR approaches
applied to assessing risk may facilitate placement of chemicals with incomplete data sets in the
appropriate risk categories. In addition, computational modeling includes physiologically-based
pharmacokinetic (PBPK) models, as well as modeling dose response [198]. As a result, if a QSAR
model is then developed, ideally, dose-response toxicity of untested NP can be predicted on the
basis of its physicochemistry [197]. Actually, many investigations confirm that there is a strong need
to extend the traditional QSAR paradigm to NPs. In connection to this, some recent studies have
shown that QSAR can be effectively used for predicting the toxicity of NPs, other physicochemical
properties, and therefore, one can assess the environmental risk of these materials [197].
The following three points need to be considered to extend QSAR approach to NPs:
1. QSAR methodology has been mainly developed for small organic compounds with diverse
structural types, while NPs are large and structurally limited in diversity.
2. The experimental data accumulated for NPs are not yet sufficient to fully assess the toxic-
ity; the empirical data are scarce and/or contradictory.
3. Regular QSAR descriptors, which are applicable for organic compounds, are generally not
applicable for NPs. Although this problem is being rapidly addressed,some novel nanode-
scriptors are suggested.
