Development of nanotoxicology: Implications for drug delivery and medical

devices

Sourav Bhattacharjee* and David J. Brayden

UCD School of Veterinary Medicine and UCD Conway Institute, University College

Dublin, Dublin, Ireland

*Correspondence: Tel: +353 1 716 6233; Email: sourav.bhattacharjee@ucd.ie

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Abstract

Toxicology assessments of nanomaterials are currently challenged by sub-

optimal in vitro models, lack of in vitro-in vivo correlations, deficits in both material

purity and physicochemical characterization, and variability within in vitro

nanotoxicological protocols. As a result of these issues, reliable nanomaterial toxicity

and mechanistic understanding of nanomaterials interactions in physiological systems

are required for health and toxicity risk assessments. Much in vitro toxicological data

is inconclusive in designating whether nanomaterials for drug delivery and medical

device implants are truly safe. A critique is presented to analyse the interface between

toxicology and nanopharmaceuticals. Deficiencies of existing practices in toxicology

are reviewed and useful emerging techniques (e.g. lab-on-a-chip technique, tissue

engineering, atomic force microscopy, high-content analysis, and multivariate

analysis), as well as better defined in vitro models are highlighted. Cross-fertilisation

between disciplines will aid development of biocompatible delivery and implant

platforms. Finally, improvements are suggested for development of advanced

protocols in nanotoxicology, with implications for translation.

Key words

Nanotoxicology, biomaterials, high content analysis, lab-on-a-chip, predictive

toxicology

Glossary

Nanotoxicology: in vitro and in vivo study of toxicity of nanomaterials, typically

<100 nm in at least one dimension.

Nanomedicine: the medicinal applications of nanomaterials obtained with

nanotechnology in diagnostics, medical devices, and delivery of therapeutics.

QSAR: (Quantitative Structure-Activity Relationship) is a statistical modelling tool

used in chemical and biological sciences to develop in silico models.

ROS: Reactive oxygen species: superoxides, hydroxyls, and peroxides, produced in

cells as a consequence of biochemical reactions

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Microfluidics: the design of devices, which contain processes with fluid flow

ranging from µl to nl volumes with application in chemistry, biology and

‘nanobiotechnological’ research.

Tissue spheroids: 3D conglomerates of living cells that mimic the evolution,

viability and biochemical processes comparable to original source tissues.

HCA: High Content Analysis is an automated technique used in discovery and in

delivery research, which produces quantifiable data from live cells on a range of

cellular and biochemical indicators of toxicity.

Abbreviations

AAS, atomic absorption spectroscopy; AFM, atomic force microscopy; AUC,

analytical ultracentrifugation; BET, Brunauer-Emmett-Teller; CdTe, cadmium

tellurite; CNT, carbon nanotube; DIC, disseminated intravascular coagulation; DLS,

dynamic light scattering; DMA, differential mobility analyzer; DSC, dynamic

scanning calorimetry; ECM, extra-cellular matrix; FFF, field flow fractionation;

FRET, Förster resonance energy transfer; FTIR, fourier transformation infrared

spectroscopy; GelMA, gelatin methacrylate; GFP, green fluorescent protein; GPC,

gas phase chromatography; HCA, high-content analysis; HNDF, human neonatal

dermal fibroblast cells; HPLC, high performance liquid chromatography; HTS, high-

throughput screening; HUVEC, human umbilical vein endothelial cells; ICP-MS,

inductively couples plasma mass spectrometry; iPSC, induced pluripotent stem cells;

I.V., intravenous; LDH, lactate dehydrogenase; LOC, lab-on-a-chip; MANOVA,

multivariate analysis of variance, MS, mass spectroscopy; MWCNT, multi-walled

carbon nanotube; MVA, multivariate analysis; NMR, nuclear magnetic resonance;

NP, nanoparticle; PAMAM, poly(amidoamine); PCA, principal component analysis,

PDMS, polydimethylsiloxane; QD, quantum dot; QSAR, quantitative structure-

activity relationship; RES, reticulo-edothelial system; RFP, red fluorescent protein;

ROS, reactive oxygen species; SEM, scanning electron microscopy, SOP, standard

operating protocol; SPM, scanning probe microscopy; TEM, transmission electron

microscopy; TEER, trans-epithelial electrical resistance; TGA, thermogravimetric

analysis; TIPS, thermally induced phase separation; TIRF, total internal reflection

fluorescence; TMRM, tetramethyl rhodamine methyl ester; MFA, multifactor

analysis; UV-Vis, ultraviolet-visible spectroscopy; XPS, X-ray photoelectron

spectroscopy; XRD, X-ray diffraction; ZO, zonula occludens.

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Executive Summary

Nanopharmaceuticals are being introduced mainly for cancer therapy, with other

prototypes being tested in preclinical study of delivery systems for a variety of

conditions.

Uncertainty regarding the safety and compatibility of nanopharmaceuticals hinder

translation.

The search for criteria that define the toxicity of nanomaterials remains elusive.

Nanoparticle features (e.g. surface charge, particle size) and non-nanoparticle-

related factors (e.g. protein corona) influence biological behavior of nanoparticles.

The protein corona adsorbed to nanoparticles is a highly dynamic and

heterogeneous layer and its composition is yet to be fully realized.

The role of oxidative stress as a mechanism of toxicity for nanoparticles needs to

be better understood.

Lab-on-a-chip techniques, tissue engineering, computational toxicology, high-

content analysis (HCA), atomic force microscopy, and multivariate analysis assist

nanotoxicological assessments, and these methods are being established in drug

delivery research.

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Contents

1. Introduction

2. Issues with current nanotoxicological in vitro methods

2.1 Discrepancies in operating protocols and in NP-characterization

2.2 Inadequate surface analysis of NPs and cells

2.3 Interactions between proteins and NPs

2.3.1 Role of protein corona around NPs in nanotoxicology

2.3.2 In vivo effects of protein-NP interactions: physiological relevance

2.4 Understanding oxidative stress in cytotoxic mechanisms

2.5 Unfulfilled translation of nanotechnologies to date

3. Upcoming technologies and testing platforms

3.1 Computational nanotoxicology

3.2 Transition towards 3D testing platforms

3.2.1. Nanotox-on-a-chip

3.2.2 Scope for tissue engineering

3.2.3 3D printing

3.3 High-content analysis (HCA)

3.4 Multivariate analysis (MVA)

3.5 Atomic force microscopy (AFM)

4. Future Perspectives

5. References

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1. Introduction

Nanotoxicology is a topic of importance in the current era of nanomedicine and

drug delivery. Interest in nanotechnology has grown rapidly in academia and

industry, as well as with policy makers, funding agencies and the media; the

worldwide market is expected to surpass the $ trillion landmark by 2015 [1]. There is

much effort is in development of “nano-bio” materials that have useful properties and

are safe and effective in drug delivery systems and medical devices. Nanotoxicology

is a subset area of nanomedicine and is used to assess acute and chronic

biocompatibility of nanomaterials; it is in a growth phase, as reflected by large

funding for consortia dispersed from the EU FP7- and other programmes. Due to the

size factor, nanoparticles (NPs) have unique features that influence toxicity, and this

differentiates nanotoxicology from conventional particle toxicology [2].

Nanotoxicology has however, failed to yield significant breakthroughs in

extrapolation of in vitro data to in vivo, despite the volume of literature on

nanomaterial safety published in the last decade [3]. The surge of articles in

nanotoxicology does not necessarily reflect in depth assessment of nanomaterials.

While the number of novel nanomaterials with potential use in diagnostics, tissue- and

cell-based scaffold implants, and delivery of therapeutics is rapidly expanding [4],

most research on their cytotoxicity has applied traditional cytotoxic cell death assays

in cell lines to predict outcomes in vivo, with decidedly mixed results. In addition, a

major challenge for in vitro assay development is to model is sub-lethal toxicity that

may be caused by nanomaterials at low concentrations during chronic exposure in

vivo.

2. Issues with current nanotoxicological in vitro methods

The factors that influence nanomaterial cytotoxicity can be classified as follows: (1)

Factors related to the nanomaterials: e.g. surface charge, particle size, porosity,

surface functionalization, crystallinity, shape and composition; (2) Factors related to

experiment: e.g. presence of opsonins, interactions with culture media components,

surface adsorption to cells or to system supports, cell selection, the role of cellular

receptors, and the bioassays used. While these factors are multifactorial, there is a

tendency to express cytotoxicity primarily in respective of single parameters. For

example, a positive surface charge on NPs is recognized to promote cellular

interaction and can promote increased cytotoxicity compared to neutral or negatively-

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charged NPs [5-7]. However, surface charge does not represent the entire cytotoxic

potential of NPs and further depends on surface functionalization [8] and the spatial

configuration with reference to the surrounding steric bulk [9]. In addition, the charge

density on the surface needs to be taken into account [10, 11]. Undue focus on surface

charge per se lead to errors in conclusions, and the broader physico-chemical

intricacies of surface charge need to be better investigated [12].

Apart from surface charge, particle size is also a critical factor in nanotoxicology

[13, 14]. An aqueous dispersion of NPs is typically a colloid, not accurately reflected

by electron micrograph images. Interpretation is especially complex when NPs are

incubated in culture medium, comprising a gamut of multiple salts, ions,

immunoglobulins, lipids and proteins. They compete for adsorption sites on the

particle, which causes size to fluctuate over time. Adsorption impacts surface charge

and can change overall surface chemistry [15, 16]. Singling out individual factors

therefore will provide limited data, in the event that multiple parameters likely

combine to contribute to overall nanotoxicity.

2.1 Discrepancies in operating protocols for NP characterization

The main obstacle towards gaining insights regarding in vitro nanotoxicology is

questionable methodology [17]. The field lacks many validated SOPs (standard

operating procedures) and of those that are, they are not widely implemented. While

there is debate over which discipline nanotoxicology is closest to – pharmacology and

toxicology, chemistry, or the physical sciences, tackling its challenges requires multi-

disciplinary collaborations. Current nanotoxicology research suffers from lack of

adequate physicochemical characterization of NPs [18, 19], and there are no

universally-agreed assays with designated acceptance criteria [20]. Furthermore,

although there are attempts to provide guidelines on characterization of nanomaterials

in biological media [21, 22], there is no consensus. Scattered knowledge dissemination

in the literature may contribute in part to the lack of standardization.

Nanotoxicological research is published in a wide variety of journals including those

in pure toxicology, pharmaceutics, and polymer and lipid chemistry. There is a

tendency to focus on journals within one’s own expertise rather than on less familiar

journals.

In order to assess cytotoxicity of NPs in cellular environments, useful data can be

achieved from techniques in physical chemistry and colloid sciences. Such

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laboratories are well equipped with instruments essential to characterize

nanomaterials. These include dynamic light scattering (DLS) to measure

hydrodynamic size of NPs, zeta potential measurement to assess the stabilities of

suspensions, and the Brunauer-Emmett-Teller (BET) technique to measure surface

area and porosity. They also contribute X-ray diffraction (XRD) to investigate the

crystal structure, transmission/scanning electron microscopy (TEM/SEM), and atomic

force microscopy (AFM) to image the NPs, as well as spectroscopic nuclear magnetic

resonance (NMR), infrared (IR), ultraviolet (UV-VIS) and chromatographic liquid

chromatography/mass spectroscopy (LC/MS) to understand compositions. Common

techniques employed to characterize NPs are listed (Table 1).

Table 1: Usual characterization techniques for NPs

Parameter Properties Techniques

Morphology

Size TEM, SEM, AFM, XRDShape/Structure TEM, SEM, AFM, DLS, FFF, AUC, HPLCSize distribution EM, SEM, AFM, DLS, AUC, FFF, HPLCMolecular weight AUC, GPC

Stability DLS, AUC, FFF, SEM, TEM

Surface features

Surface area BETSurface charge SPM, TitrationsSurface coating SPM, XPS, MS, FTIR, NMR

Surface coverage AFM, AUC, TGATopology SEM, SPM, MS

Chemistry

Composition XPS, MS, AAS, ICP-MS, FTIR, NMRPurity ICP-MS, AAS, AUC, HPLC, DSC

Crystallinity XRD, DSCStability MS, HPLC, FTIR

Drug deliveryDrug loading MS, HPLC, UV-VIS, Fluorescence

In vitro release UV-VIS, MS, HPLC, FluorescenceDeformability AFM, DMA

Abbreviations: AAS, atomic absorption spectroscopy; AFM, atomic force microscopy; AUC, analytical ultracentrifugation; BET, Brunauer-Emmett-Teller; DLS, dynamic light scattering; DMA, differential mobility analyzer; DSC, dynamic scanning calorimetry; EM, electron microscopy; FFF, field flow fractionation; FTIR, fourier transformation infrared spectroscopy; GPC, gas phase chromatography; HPLC, high performance liquid chromatography; ICP-MS, inductively coupled plasma mass spectrometry; MS, mass spectroscopy; NMR, nuclear magnetic resonance; SEM, scanning electron microscopy, SPM, scanning probe microscopy; TEM, transmission electron microscopy; TGA, thermogravimetric analysis; TIRF, total internal reflection fluorescence; UV-Vis, ultraviolet-visible spectroscopy; XPS, X-ray photoelectron spectroscopy; XRD, X-ray diffraction

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232233234235236237238239240241242243

There are three major areas to further address in characterization of NPs:

(1) NP-interference – NPs are reactive and interact with components of in vitro

systems (e.g. salts, proteins, immunoglobulins). They have high surface area/mass

ratios, which facilitate molecule adsorption. For example, carbon nanotubes

(CNTs) can adsorb to the formazan in the [3-(4,5-dimethylthiazol-2-yl)-2,5-

diphenyltetrazolium bromide] (MTT) assay and produce false positive cytotoxicity

[25]. Other examples of interference during assays occur with fluorescent NPs (e.g.

quantum dots, fluorescent latex beads), which can interfere with

spectrofluorometric assays [26]. Furthermore, NPs can adsorb salts and proteins in

culture medium [27], creating medium component concentrations that are too low

to support cell viability, thus indirectly causing cytotoxicity.

(2) Concentration considerations – compared to realistic exposure concentrations,

there is a tendency to use very high levels of NPs both in vitro and in vivo. Very

high concentrations of NP are of little toxicological relevance in making a risk

assessment. Furthermore, they can paralyze cellular physiology by establishing a

~500 nm layer of NPs on the plasma membrane, which deprives cells of nutrients

and oxygen [28, 29].

(3) Effect of solvents – many laboratories uses commercially-available NPs “as

received” from suppliers. Quantum dots (QDs) and latex beads arrive suspended in

a “vehicle mixture” containing surfactants, stabilizers and organic solvents (e.g.

tetrahydrofuran, THF), which may have inherent toxicity. For example, the

oxidative stress in cells observed from C60 fullerenes originated from the peroxides

produced from ageing THF, which were present to provide fullerene stability [30].

Effects of solvents therefore need to be taken into consideration in order to avoid

erroneous conclusions on cytotoxicity.

2.2 Inadequate surface analysis of NPs and cells

Surface chemistry is important in nanotoxicology not only because most of the

nanobio-interactions are surface-dependent, but also due to the growing use of

functionalized NPs. The surfaces of NPs can be coupled with functional groups via

conjugation or through attachment of surface coatings to facilitate passage through

biological barriers (e.g. human intestinal mucus, sub-cutaneous tissue). Therefore,

characterization of NPs is incomplete without detailed knowledge about surface

properties [31]. Surface charge has a significant effect on cellular internalization as

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well as on toxicity of NPs. Importantly, the entire surface chemistry (i.e. the combined

effects of curvature, surface area/volume ratio, the percentage of molecules expressed

on the surface, functionalization, and hydrophilicity) contributes to how NPs interact

with biological systems.

The consequences for the plasma membrane after exposure to NPs are also of

interest. With the help of AFM, the surfaces of rat macrophage NR8383 cells exposed

to 100 nm positively- and negatively-charged latex beads were visualized [32]. The

positively-charged NPs created holes in the cell membrane and increased the overall

roughness of the cell surface, which were associates with cytotoxicity. In contrast,

non-toxic negatively charged NPs caused few changes in cell surface topography.

These results showed how NPs affect the surface properties of the cells and also

suggested an additional mechanism of toxicity for the cationic NP: disruption of the

surface congruity of cell membranes.

Unfortunately, it is a challenge to fully characterize the surfaces of either NP or

cells. One major reason is the typically harsh conditions (e.g. ultra-high vacuum, high

pressure, dessication) that are employed in the current surface analysis tools (e.g. XPS

(X-ray photoelectron spectroscopy), LEED (low energy electron diffraction),

TEM/SEM, SIMS (secondary ion mass spectrometry), and Auger electron

spectroscopy. Another contributing factor arises from sub nm structures, (e.g. ion

channels), which participate in such cell-NP interactions, but current surface analytical

tools do not have the resolution to map them, although this is being addressed. The

presence of water in biological as well as NP environments is also a restricting factor

towards the applicability of such tools.

2.3 Interactions between proteins and NPs

2.3.1 Role of protein corona around NPs in nanotoxicology

The concept of a protein corona forming on NPs in serum-rich culture medium has

gained general acceptance [33-37]. The protein corona is a highly dynamic and

heterogeneous adsorbed layer; its composition further depends on the chemistry of the

NP and determines the mechanism of interaction [38], agglomeration states, and as to

whether NPs can stimulate specific receptor-mediated internalization [39].

The role of protein corona in cellular interactions of NPs however, needs to be

analyzed further [40]. DMEM and RPMI-1640 are mixtures of different amino acids,

lipids, salts (calcium chloride, potassium chloride, phosphates), carbohydrates, and

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vitamins (folic acid, nicotinamide, riboflavin). In medium, such molecules also adsorb

onto NP surfaces. Molecules with smaller masses (e.g. lipids) move faster and thereby

are adsorbed on the NP-surface quicker than the large proteins in fetal bovine serum

(FBS). However, with the arrival of proteins at surfaces, the lower mass molecules are

gradually displaced in a dynamic process [41]. Lower molecular weight molecules

however, contribute more than proteins in building up the corona at early time points,

during which cell interaction and uptake of NP may be at their highest level. The role

of non-protein molecules in cell culture medium may therefore contribute significantly

to initial interactions between cells and NPs, as well as to cytotoxicity. To our

knowledge, there is very little published on their potentially important role. The

occurrence of protein adsorption on biomaterials in biologically relevant media

including like blood has been reported before, but there is a tendency for some

researchers to ignore literature [42-45]. The topics of particle curvature, defects and

energy isotherms on NP-surfaces, as well as analytical issues remain challenging for

the corona, although the basic principles for adsorption are well established. The

composition of protein corona on NP-surfaces is dynamic and depends on a multitude

of factors including protein size and concentration. Unfortunately, the composition of

protein corona on NP-surfaces is yet not well studied due to lack of adequate tools.

To date, few animal studies investigating the role of surface charge in

biodistribution and bioavailability of charged NPs have noted any significant effect of

their surface charge, either following oral [46, 47] or parenteral administration [48, 49]

There is a lack of any consensus on the effect of surface charge on biodistribution of

NPs after oral delivery. This is in contrast to in vitro data [50]. One explanation for the

apparent discrepancy between in vitro and ex-/in vivo intestinal epithelial data may be

the role of mucous overlying the intestinal epithelium, which impedes NP-uptake by

enterocytes, depending on the model [51]. The role of the surface charge in surface

adsorption of proteins can also be an explanation for this lack of in vitro-ex-/in vivo

correlation [52]. The protein molecules harbor both cationic and an anionic binding

sites, which adhere to NPs thereby altering the surface properties and masking effects

observed in vitro [53]. Therefore, the in vivo understanding of the protein corona

around NPs has not yet been worked out adequately.

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2.3.2 In vivo effects of protein-NP interactions: physiological relevance

Following I.V. injection, NPs appear to interact with proteins in plasma in both

surface charge- and size-dependent ways. For example, Greish et al. [54] tested non-

porous silica NPs (50, 200 nm; amine- and acid-terminated), PAMAM

[poly(amidoamine)] dendrimer generations (G3.5-G7; sizes (3.2-8 nm), as well as

surface functionalized analogues (amine, hydroxyl and acid-terminated) in CD-1 mice

following I.V. injection. Of the silica NPs, only the largest 200 nm silica NPs caused

in vivo cytotoxicity, irrespective of their surface charge. In contrast, amine-terminated

dendrimers induced lethality at a dose of >10 mg/kg, confirming the cytotoxicity of

cationic but not the anionic dendrimers. The cationic dendrimers caused disruption of

the clotting cascade, intestinal hemorrhage, as well as disseminated intravascular

coagulation. In a similar study, cationic PAMAM dendrimers induced platelet

dysfunction while inhibiting thrombin formation [55]; a mechanism mediated by

interaction with P-selectin, RANTES and PF4 (platelet factor) recognition sites on

platelets. Insights into the role of NP-protein interactions in in vivo toxicology in such

examples will provide better understanding of nanotoxicity in the circulation and will

assist the translational value of NPs after parenteral exposure.

2.4 Understanding oxidative stress in cytotoxic mechanisms

Oxidative stress is a common mechanism of cytotoxicity of NPs [56-59], since NP

are highly reactive and interact with a variety of proteins and lipids. If internalized,

NPs may trigger enzymatic pathways capable of producing reactive oxygen species

(ROS) including superoxides, hydroxyls and peroxides. There are doubts however,

over whether oxidative stress is a primary or secondary toxicological mechanism.

Charged NPs disrupt the mitochondrial membrane permeability [60, 61], making them

leaky. The mitochondrial membrane is the site for the electronic transport chain

(ETC), which quenches oxygen free radicals [62]. Therefore, a disturbance to the

mitochondrial membrane by charged NPs will hamper the ETC, causing leach of

oxygen radicals into cytoplasm. Hence, oxidative stress can manifest as a secondary

feature of disrupted mitochondrial physiology caused by charged NPs. In addition,

mitochondria is a source of intracellular calcium [63], and disruption will also cause

calcium release into the cytoplasm leading to overload [64, 65]. Calcium overload can

in turn trigger apoptotic pathways via production of secondary cellular messengers

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including NF-κB [66]. Other cellular cytotoxic pathways exist within cells in response

to NPs, and perhaps systems biology mapping can add value [67, 68].

2.5 Unfulfilled translation of nanotechnologies to date

In spite of the large amount of nanotoxicology data available, building safe and

sustainable drug delivery platforms based on NP constructs remains largely unfulfilled

[69-76]. 10,000 papers on nanotoxicology were published from 2011-2014 [26], but

few constructs translated into clinical approvals. Three major reasons are highlighted:

(1) The deficiency in correlation between in vitro and in vivo – current in vitro models

in nanotoxicology continue to be inadequate for in vivo correlation, yet in vitro

studies have dominated the nanotoxicology literature, due largely to the difficulties

associated with in vivo experimentation, including inadequate animal models,

stringent licensing procedures, and significant Facility investment.

(2) Sequestration of NPs into organs – more than 90% of the bioavailable dose of NPs

fails to reach target organs due to sequestration by the liver or spleen [77]. Coating

NPs with PEG (polyethylene glycol) of different chain lengths is a valid way to

alter surface hydrophilicity in order to change distribution by avoiding uptake by

the RES (reticulo-endothelial system) [78].

(3) Inability of engineered NPs to cross biological barriers – many NPs fail to cross

biological barriers (e.g. blood-brain-barrier, small intestine). NPs with high surface

charge density show better flux through mucus [79], but such muco-penetrating

NPs then need further design to promote epithelial cell internalization, unless

release of payload close to the epithelium is enough for efficacy. In many studies

Caco-2 cell monolayers grown on inserts are used to measure passage of NPs [80],

but there are discrepancies between protocols, with no account taken for lack of

mucous. Most of the mucous-covered epithelial constructs have reproducibility

issues and do not elaborate the same mucous composition as in vivo.

3. Upcoming technologies and testing platforms

3.1 Computational nanotoxicology

Quantitative structure-activity relationship (QSAR) models have been proposed as a

promising tool to model and predict NP cytotoxicity [81, 82]. In silico models may

predict cytotoxicities of NPs to a satisfactory degree [83]. One of the key features is

interaction between NPs and cell membrane-bound receptor pathways. These

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receptors, including clathrin and caveolin pathways [84, 85], are the basis of

internalization of a wide range of NPs.

With knowledge on the energetics and mechanisms of endocytic pathways

emerging, reliable computational models can be developed [86]. However, we must

first acquire improved characterization of NPs as the quality of the data input will

determine the quality of results that can be extracted from these models. QSAR

models may provide insight into receptor-NP interactions and, for example, can

predict behavior of multi-layered phospholipid layers after being exposed to charged

NPs [87]. With increasing numbers of NPs being incorporated into consumer products,

it is extremely difficult to test them all in vivo [88]. Taking such points into

consideration, QSAR can be an effective model towards predictive nanotoxicology in

future, although it will still need in vivo datasets to compare with.

Another aspect of computer design-aided systems is the potential for protocols in artificial

intelligence (AI) domains. Some of this research is related to designing computer-human

brain interfaces [89, 90]. Similarly, other human model systems (e.g. skin) [91] are being

developed digitally, and such models may predict nanomaterial toxicity in a more defined

way. Through these informatics-based designs, interesting models of human physiological

barriers [e.g. blood-brain-barrier (BBB)] can be developed, which can assist development of

NP-based delivery technologies [92].

3.2 Transition towards 3D testing platforms

3.2.1 Nanotox-on-a-chip

Microfluidics-based approaches are finding new applications in biology. Improvements in

surface fabrication and lithography techniques (e.g. wet and dry etching, sputtering, anodic

and fusion bonding) [93] can produce surfaces (e.g. silicon, glass and polymers) with

embedded channels and reservoirs of µm dimensions. These surfaces can be used to produce

chips synthesized from materials including polydimethylsiloxane (PDMS) [94]; µm

dimensional structures are then transferred onto chip materials. With advanced

instrumentation and introduction of modern automation including robotics, sophisticated

microfluidics-based devices are being developed with precise control over process- and fluid

flow. Lab-on-a-chip (LOC) technology has potential in drug delivery [95, 96], and especially

within the fields of bio-MEMS (biomedical microelectromechanical systems) [97, 98] and

µTAS (micro total analysis systems) [99, 100]. One of the advantages of fluid flow in

microchannels is the laminar flow and absence of turbulence [101], thereby preventing

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mixing between fluids. As a result, the chances of bacterial infection are reduced compared to

conventional in vitro techniques [102]. Additionally, bio-MEMS platforms require few

reagents, produce low level waste, and have a high degree of integration, sensitivity, and

portability. The surface fabrication costs are becoming manageable and this will contribute to

growth [103].

In last few years, bio-MEMS have been used extensively in biomedical engineering

and drug discovery. One of the important developments in this field is the designing of

‘organ-on-a-chip’ devices [104]. These 3D microfluidics-based devices are tissue

culture systems, which simulate the functions and physiologies of different organs.

They offer more flexibility compared to 2D conventional counterparts, in addition to a

low contamination risk. Organ-on-a-chip devices are being used extensively for in

vitro studies investigating chemotaxis, stem cell differentiation, axon guidance and

embryonic development [105-108]. They offer the advantages of multiplexing with

capability of high-throughput screening (HTS) and hence, are being used in the

development of biosensors, point-of-care diagnostics, and “omics” studies. Apart from

that, they are being used with induced pluripotent stem cells (iPSC) [109] to develop

new techniques in cell therapy and the study of cell-cell, or cell-ECM (extra-cellular

matrix) interactions. Some organ-on-a-chip devices (e.g. lung-on-a-chip [110], liver-

on-a-chip [111], gut-on-a-chip [112]) are already being used in nanotoxicology and

this is relevant for NP delivery systems. There are efforts to develop a “human-on-a-

chip” µdevice which will integrate all the major systems in human body [113].

A human lung-on-a-chip model was reported in 2010 [110]. Although some sporadic

attempts of designing human lung-on-a-chip have been done before [114], this model may

potentially be used for testing pulmonary toxicity of NPs. The chip was produced in PDMS

containing µm-dimensional structures and contained a three layer arrangement (PDMS-

membrane-PDMS) (Fig. 1). The membrane sandwiched between the two PDMS layers was

porous and, after the chip assembly, epithelial and endothelial cellular monolayers were

grown on opposite sides of the membrane. Intact structural aspects of the monolayers were

confirmed by TEER (trans-epithelial electrical resistance) and staining by a ZO-1 (zonula

occludens) antibody to the tight junction protein. Two parallel hollow channels were at the

sides of the cell-containing chambers in order to exert cyclic stretching by application of

periodic vacuum to mimic the effect of diaphragmatic movement on the alveoli during

respiration in man.

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In related work, a novel human gut-on-a-chip was reported in 2012 [112]. Caco-2

cells were grown on a porous PDMS membrane (coated with rat collagen type I and

Matrigel as ECM) sandwiched between two PDMS layers from top and bottom. Two

hollow side chambers were also kept in order to apply periodic longitudinal stretching

in order to mimic the peristaltic movements. The viability of the Caco-2 monolayers

was confirmed by measuring the activity of aminopeptidase enzyme which is

expressed in the brush borders of differentiated cells. A strain of Lactobacillus

rhamnosus GG (LGG) was then added as a co-culture to model gut microflora and

monolayers were maintained for five days at a flow rate of 30 µl/h. Undoubtedly,

these devices also have scope for use with cells/tissues from real patients, and they

have high levels of integration with tight control over experimental conditions, and a

lower waste compared to traditional in vitro set ups [115].

Fig 1. “Biologically inspired design of a human breathing lung-on-a-chip microdevice. (A) The microfabricated lung mimic device uses compartmentalized PDMS microchannels to form an alveolar-capillary barrier on a thin, porous, flexible PDMS membrane coated with ECM.

The device recreates physiological breathing movements by applying vacuum to the side chambers and causing mechanical stretching of the PDMS membrane forming the alveolar-

capillary barrier. (B) During inhalation in the living lung, contraction of the diaphragm causes a reduction in intrapleural pressure (Pip), leading to distension of the alveoli and

physical stretching of the alveolar-capillary interface. (C) Three PDMS layers are aligned and irreversibly bonded to form two sets of three parallel microchannels separated by a 10-μm-

thick PDMS membrane containing an array of through-holes with an effective diameter of 10 μm. Scale bar, 200 μm. (D) After permanent bonding, PDMS etchant is flowed through the

side channels. Selective etching of the membrane layers in these channels produces two large side chambers to which vacuum is applied to cause mechanical stretching. Scale bar, 200 μm. (E) Images of an actual lung-on-a-chip microfluidic device viewed from above.” (from [110])

Reproduced from Ref. 110 with permission from the American Association for the Advancement of Science (AAAS).

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In spite of the potential of organ-on-a-chip models, significant strides still need to

be made before they are suitable for nanotoxicity testing [116-118]. Commonly used

chip materials such as PDMS can cause cytotoxicity and interfere with biological

assays. Several models are based on oversimplified principles, which do not reproduce

the structural complexities of tissue. However, improving current in vitro conditions

does not automatically mean higher extrapolative values to in vivo. Most of these

organ-on-a-chip models are built on selected cell lines and none have been validated

for their tissue phenotypes, genetic expressions, or metabolism. It is therefore a

challenge to expect that cells grown on a chip in a closed µfluidic environment will

mimic in vivo or even conventional in vitro systems. To address this, there is renewed

interest in use of “tissue-on-a-chip” models built on perfused ex vivo tissue slices from

toxicologically relevant organs (e.g. liver) [119, 120].

3.2.2 Scope for tissue engineering

From being a simple branch of cell biology and testing biomaterials, tissue engineering

has experienced unprecedented growth in the last two decades. Innovations including “in

vitro meat” [121], and generation of bio-artificial organs [122-124]) are paving the way.

Usually, the rationale for developing tissues in vitro is to harvest cells onto natural or

synthetic scaffolds [125, 126]. These scaffolds provide mechanical support for cells to

develop 3D aspects within the tissue systems and also for multiple cell types to differentiate.

Therefore, such cells have higher differentiation and increased robustness compared to

traditional 2D systems [127]. To embed cells within scaffolds and to ensure supply of

nutrients and oxygen, it is essential that the scaffolds are porous and exhibit surface

roughness. The scaffolds are usually made from synthetic biodegradable materials (e.g.

polylactic acid, polyglycolic acid, polycaprolactone) [128], or from natural materials (e.g.

collagen, chitosan, polysaccharides, glycosaminoglycans) [129]. They can be prepared by

electrospinning, thermally-induced phase separation (TIPS), emulsification/freeze drying, or

gas foaming [130]. Recently computer aided design was used to produce scaffolds with

uniform pores and controllable pore distribution [131]. Other progress is in the use of carbon

CNTs [132] as scaffold materials. They can provide a mesh with nm-range roughness, which

can be optimal for seeded cells to grip and coalesce upon, before growing into a tissue mass.

Additionally, the conductivity of CNTs can be used further to stimulate cell growth and

vasculature development [133]. The hanging drop technique is now being used to produce

microtissues which can then be used for toxicity testing [134]. The significant growth in

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surface lithography techniques and materials science is enabling development of novel

biomaterials, which can be used to harvest cells in order to promote differentiation of

spheroids [135, 136]. Control of oxygen tension, supply of nutrients, pH, humidity,

temperature, along with succinct and defined specificities and negligible variations between

such µtissue spheroids can be achieved [137]. Additionally, with the use of different growth

factors, microtissue spheroids with altered vascularity can be generated [138]. As a result, the

nanotoxicity data derived from such microtissue spheroids may turn out to be more consistent

and extrapolative to in vivo conditions compared to 2D systems. Application of ~100 µm

spheroids produced from human hepatocarcinoma-derived HepG2 cells in

polyacrylamide hydrogel inverted colloidal crystal (ICC) scaffolds in the estimation of

NP toxicity was recently carried out [139]. Spheroids were exposed for 12 h to CdTe

(cadmium tellurite)-QDs, as well as gold NPs, and lactate dehydrogenase (LDH) and

MTT assays were used as read-outs. The authors compared the NPs in the scaffolds

with a 2D system (Fig. 2). Significant differences were found between the 2D and 3D

systems, whereby NP-toxicities were over-estimated in the former; toxicity data

obtained from NPs in 3D systems are of higher quality compared to the 2D [140].

Fig 2. “Comparison of 2D and 3D culture of HepG2 cells after 12 h of CdTe NP exposure. A–D) Optical images of normal A) 2D and C) 3D spheroid cultures. After CdTe NP introduction,

the 2D culture showed a dramatically different morphology (B), while it was hard to distinguish any change in the 3D culture under an optical microscope (D).” (from [139]).

Reproduced with permission, Copyright: Wiley-VCH.

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In a second example, toxicity of polypyrrolidone-coated silver (Ag) NPs was tested

in murine macrophage RAW 264.7 cells in 2D cell culture and in 3D spheroid culture

systems. Again, the toxicity of AgNPs was comparatively lower in spheroids

compared to 2D, and it decreased faster over time. Computer-based design has also

been used to predict the diffusion of NPs through micro-tissue spheroids [141]. Even

with the limited amount of literature available from nanotoxicological investigations

performed in 3D cell cultures to date, the differences between toxicity between 2D and

3D systems are clearly apparent [142]. A likely explanation is that differentiated cells

grown within 3D systems are different from those within 2D systems, both

morphologically and physiologically. This also raises concerns about the huge amount

of in vitro data in nanotoxicology that have been published in the last two decades, as

most of these data were based on 2D models.

3.3.3 3D printing

3D printing produces digital structures that were considered previously to be impossible to

create [143], and it has great potential in tissue engineering. Sophisticated structures of

varying geometries can be producing by the layer-by-layer deposition of materials, which

offer opportunities for nanotoxicology [144]. With the capability in developing

structures/scaffolds with high precision, 3D printing technology may help eliminate

deficiencies in methodologies in nanotoxicology. There are two main techniques to

manufacture biomaterials using such methods: (1) Bonding-based inkjet printing, whereby a

particle-based material is deposited in layers along with binder molecules. After post-

processing, this technique produces biomaterials with designs that can be used as scaffolds in

tissue engineering; (2) Bioink-jet printing where instead of particles, biologically relevant

materials can be used. This is an exciting way of printing organs with defined vascularity

[145]. However, it is worth pointing out a few current drawbacks. The structures produced by

3D printing require post-processing, which can compromise biocompatibilities and cell

viability. Most 3D printing products are also porous in structure, which can hamper their use

as sustainable biological models [146]. A lot of tissue engineering techniques, especially in

bone tissue engineering [147], are already being used with the help of 3D printing. A TED-

talk was used as a recent forum to demonstrate how to print a human kidney using cells as

bio-ink [148]. Others also showed how cell-laden tissue constructs with grown

vascularization were developed with the help of 3D printing (Fig. 3) [149].

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Fig 3. “a,b) Schematic views of the top-down and side views of a heterogeneous engineered tissue construct, in which blue, red, and green filaments correspond to printed 10T1/2 fibroblast-laden

GelMA, fugitive, and GFP HNDF DEFINE -laden GelMA, inks, respectively. The gray shaded region corresponds to pure GelMA matrix that encapsulates the 3D printed tissue construct. Note: The red filaments are evacuated to create open microchannels, which are endothelialized with RFP DEFINE

HUVECs. c) Bright field microscopy image of the 3D printed tissue construct, which is overlayed with the green fluorescent channel. d) Image showing the spanning and out-of-plane nature of the 3D

printed construct. e) Image acquired during fugitive ink evacuation. f) Composite image (top view) of the 3D printed tissue construct acquired using three fluorescent channels: 10T1/2 fibroblasts (blue), HNDFs (green), HUVECs (red). g) Cell-viability assay results of printed 10T ½ fibroblast-laden and

HNDF-laden GelMA features compared to a control sample (200–300 μm thick) of identical composition. The asterisks indicate differences with p < 0.05 obtained from student's t-test” (from

[149]). Reproduced with permission, Copyright: Wiley-VCH.

To print the vasculature, tri-block copolymer Pluronic F127 [poly(ethylene oxide)-

poly(propylene oxide)-poly(ethylene oxide)] was used. Gelatin methacrylate (GelMA) was

used as an ink for the ECM. Different cells [fibroblastic 10T1/2 cells, green fluorescent

protein (GFP)-labelled human neonatal dermal fibroblast cells/HNDF and red fluorescent

protein (RFP)-labelled human umbilical vein endothelial cells/HUVEC] were used. The

main motivation behind 3D platforms is associated with their capabilities in

reproducing the intrinsic physiological complexities at an in vitro tissue/organ level.

This addresses some current inadequacies of 2D in vitro platforms in nanotoxicology

[150]. A shift in focus to better 3D models represents the physiological complexities

and intricacies at an organ-level to a much greater degree and with more control. The

in vitro data derived from these 3D models will be of comparatively better quality,

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which in turn will lead to better validation, improved optimization and better

extrapolation to in vivo.

3.3 High-content analysis (HCA)

The concept of HCA is relatively new in nanotoxicology research for drug delivery

and stems from drug discovery [151-153]. HCA is an integrated automated platform

comprising fluorescence microscopy and advanced imaging software for live cells. It

confers improved sensitivities and specificities compared to conventional cytotoxicity

assays. Another important characteristic of HCA analysis is that in contrast to cell

death assays, it successfully detects sub-lethal cellular changes simultaneously in

relation to concentration and exposure time. In one of the first HCA studies in drug

delivery, the cytotoxicity of melittin (a peptide from bee venom under investigation as

an intestinal permeation enhancer) was tested in Caco-2 cells using a four-dye mixture

of Hoechst 33342 (to detect cell number, nuclear intensity and nuclear area), Fluo-4

AM (to detect intracellular calcium), tetramethyl rhodamine methyl ester (TMRM) (to

detect mitochondrial membrane potential) and TOTO®-3 iodide (to detect plasma

membrane permeability) [154]. The data revealed a structure-activity relationship for

single amino acid replacements in melittin and proved that permeation enhancement

and cytotoxicity mechanism were associated. HCA offers scope for multiplexing and

HTS, as it counts the changes in individual cells and then provides a mean value

whereas traditional toxicity assays provide a single mean point for the entire

population of cells, irrespective of varying degrees of developmental and

differentiation of all the cells present. This can be of importance in nanotoxicology as

it is known that toxic effects of NPs differ depending on the differentiation stages.

Therefore, it is possible that the toxicity of NPs occurs only in a subset of the cellular

population, which can be missed by traditional in vitro techniques. Additionally, HCA

offers the possibility for rapid screening of nanoparticulates, which can be very useful

in the current context of the high numbers of emerging novel biomaterials. A recent

study used HCA to compare toxic CdTe-QDs and innocuous gold (Au) NPs [155].

Murine neuroblastoma NG108-15 (exposed to QDs) and HepG2 (exposed to AuNPs)

were used as cell models. Cell viability, calcium leakage, neurite growth, and

apoptosis were measured by HCA (Fig. 4). The results showed escalation of apoptosis

in NG108-15 cells induced by QDs, with varying responses in differentiated and

undifferentiated cells, whereas the AuNPs induced intracellular calcium release in

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HepG2 cells and altered sub-lethal parameters to a lesser extent. A similar study where

HCA has been used to assess toxicities of NPs was also published recently with

investigation on toxicity of iron oxide NPs [156].

Fig 4. “Representative fluorescence and bright field images of a healthy (green outline), an apoptotic (red outline), and a necrotic (yellow outline) cell. Cells were stained simultaneously with Hoechst 33342 (blue channel, first column) and propidium iodide (red channel, middle column). Outline and classification of cells were generated by the IN Cell Investigator image

analysis software using the supervised classification capability.” NG108-15 murine neuroblastoma cells were exposed to thioglycolic acid/gelatin coated QDs (from [155]).

Reproduced with permission from Elsevier.

3.4 Multivariate analysis (MVA)

One of the new methodologies to analyze nanotoxicology data is multivariate analysis

(MVA), which is based on the principles of multivariate statistics and analyzes outcomes

taking multiple variables into account [157]. Owing to its capacity to deal with multiple

factors at a time, MVA offers improvements in understanding cell-NP interactions. It has

several variations: principal component analysis (PCA), multifactor analysis (MFA), and

multivariate analysis of variance (MANOVA). The choice of model will depend on

dependent or independent factors. The target of MVA is to build up a model statistical tool

through determining the regression trends that can be used to analyze a broad range of

datasets [158]. It can be used in specific nanomaterial toxicity assays, where individual

parameters including surface charge, composition, and particle size are correlated to toxicity

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parameters (e.g. production of intracellular ROS, reduction of cellular glutathione, disruption

of mitochondrial membrane integrity). It is still unknown to what extent these factors

contribute individually to the amalgamated toxic effects and therefore MVA approaches can

shed new light on this. Use of MVA to represent the NP-toxicity data is gaining traction. Two

recent studies used MVA to investigate cytotoxicities of carbon NPs (multi-walled

CNTs (MWCNTs) and C60 fullerenes on gram negative organisms (P. fluorescens and

M. vanbaalenii) [159, 160]. The authors used synchrotron radiation-based Fourier-

transform infrared (IR) spectroscopic techniques in order to assess cellular metabolic

activities, in association with cellular imaging. Control cells were scanned using

advanced IR spectroscopy to determine the fingerprint range for the biomolecules

within the cells. Next, with systematic scanning of cellular samples exposed to

different MWCNTs and C60 fullerenes, 64 different data sets were generated and

analyzed. Through scanning of specific regions of the spectra and further comparison

with control data, a larger picture of intracellular events including production of ROS

were identified. Furthermore, these data were depicted in 3D hyperspace after

uploading the computational model with the data and determining the vector. The 3D

depiction showed outcomes of clustered datasets, and advanced a novel way of

representing and analyzing data.

3.5 AFM

In the last two decades, AFM has evolved to be an extremely powerful and sensitive tool

to image surface topologies at even sub-nm scales. AFM offers advantages (e.g. real-time

mapping, capability to measure in aqueous environments, minimal sample preparation, and

absence of any requirements of harsh conditions as high vacuum or pressure, integration

possibilities with fluorescence and microscopy techniques like confocal, TIRF, FRET), which

makes it a suitable tool for biological specimens [161]. AFM sensitivity has seen growth in

mapping cell surface topography, an important aspect of nanotoxicology. The simplest

application of AFM is in NP-visualization. With advanced techniques and tiny diameter of

the tips, very high resolution is now possible, which enables visualization of NPs (<50 nm),

and examination of surface complexities and functionalization [162]. Adequate surface

analysis is essential before starting toxicity assays, so AFM can provide a broad range of

comprehensive surface analysis of both NPs and plasma membranes. It can also image

complex biomolecules (proteins, DNA) [163, 164], and can investigate their interactions with

NPs. It is also used to image membrane proteins, including elucidation of their repetitive sub-

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units and other structural properties [165], as well as mapping ion channels and receptor

patterns [166]. Furthermore, AFM was used to investigate cell mechanics by imaging

changes in cytoskeleton following exposure to toxicants including NPs [167]. With

functionalized tips, AFM is now able to provide hyper-resolution of sub-nm scale “bionano”-

interactions and also provides information on intermolecular interactions and adhesion forces.

This can be helpful especially in developing NPs for peptide delivery across the intestine,

where the most promising prototype should be able to penetrate mucus and reach the

epithelium. AFM can measure the adhesion forces between NPs with mucin and can rank

NPs on their propensity to permeate mucus. It has potential in nanotoxicology through its

interrogation of the complex interactions between NPs and cell membranes, provides

information about how NPs interact with receptors, and elucidates the processes of cellular

internalization.

4. Future Perspectives

Nanotoxicology has tremendous potential to facilitate NP-drug delivery research.

However, poorly disseminated SOPs, lack of rationale for selection of concentrations in vitro

and dose levels in vivo, poorly predictive in vitro models, insufficient NP characterization, as

well as system-based interferences hamper progress. These are all areas that need to be

addressed. Furthermore, NP designs for drug delivery are being continuously introduced. For

example, nanocrystals of the original drug can form NPs with very high drug loadings [168],

and is especially suitable for oral drugs with low solubility. Oral nanocrystals of many

important small molecules (e.g. clarithromycin [169], amphotericin [170], danazol [171] and

naproxen [172]) have been reported. As a second example, structural knowledge of viral

capsids is enabling use of viral NPs in delivery of DNA and RNA [173], peptides [174]) and

for imaging and diagnostics [175, 176]. Due to their extremely high surface charge densities,

viral particles may also diffuse through mucus, which is relevant for non-parenteral delivery

platforms. It is clear that multi-disciplinary NP-drug delivery collaborations between

nanotoxicologists, physical chemists, pharmaceutical formulators and pharmacologists will

lead to higher chances of translating such concepts.

5. Conclusion

Emerging concepts, including 3D printing, bio-MEMS, HCA, AFM, tissue engineering

and MVA can contribute significantly to nanotoxicology assay development and can assist to

derive better in vitro-in vivo correlation. In spite of investing so much effort in

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nanotoxicology, progress in understanding the intricacies of cytotoxicity of NPs still remains

insufficient for accurate predictions for man and this is especially relevant for drug delivery

application. There is an urgent need to establish standardized protocols in order to bring

comparability within nanotoxicology research. An inter-disciplinary research environment

needs to be established to produce more reliable safety profiles of engineered nanomedicine.

In doing so, nanotoxicology will facilitate the safety aspects to enable effective robust NP

platforms.

Acknowledgements

Research for this review has received funding from the European Union Seventh

Framework Programme (FP7 / 2007-2013) under grant agreement n° 281035 (TRANS-INT)

and also from the Science Foundation Ireland Centre for Medical Devices (CURAM) (13-

RC-2073).

Declaration

The authors declare no competing interests.

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