Table Of ContentAdvances in Experimental Medicine and Biology 947
Lang Tran
Miguel A. Bañares
Robert Rallo Editors
Modelling
the Toxicity of
Nanoparticles
Advances in Experimental Medicine
and Biology
Volume 947
Editorial Board
Irun R. Cohen, The Weizmann Institute of Science, Rehovot, Israel
N.S. Abel Lajtha, Kline Institute for Psychiatric Research, Orangeburg, NY, USA
John D. Lambris, University of Pennsylvania, Philadelphia, PA, USA
Rodolfo Paoletti, University of Milan, Milan, Italy
More information about this series at http://www.springer.com/series/5584
Lang Tran • Miguel A. Bañares • Robert Rallo
Editors
Modelling the Toxicity
of Nanoparticles
Editors
Lang Tran Robert Rallo
Institute of Occupational Medicine Universitat Rovira i Virgili
Edinburgh Departament d’Enginyeria Informatica i
United Kingdom Matematiques
Tarragona
Miguel A. Bañares Spain
Institute of Catalysis & Petrochemistry, CSIC
Madrid
Spain
Frontispiece: Uschi M. Graham and Günter Oberdörster, 2016
ISSN 0065-2598 ISSN 2214-8019 (electronic)
Advances in Experimental Medicine and Biology
ISBN 978-3-319-47752-7 ISBN 978-3-319-47754-1 (eBook)
DOI 10.1007/978-3-319-47754-1
Library of Congress Control Number: 2016963324
© Springer International Publishing AG 2017
This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of
the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation,
broadcasting, reproduction on microfilms or in any other physical way, and transmission or information
storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology
now known or hereafter developed.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication
does not imply, even in the absence of a specific statement, that such names are exempt from the relevant
protective laws and regulations and therefore free for general use.
The publisher, the authors and the editors are safe to assume that the advice and information in this book
are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the
editors give a warranty, express or implied, with respect to the material contained herein or for any errors
or omissions that may have been made.
Printed on acid-free paper
This Springer imprint is published by Springer Nature
The registered company is Springer International Publishing AG
The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
v
Introduction
Nanotechnology is recognised as one of the most important new technologies of the
twenty-first century. The global investment in nanotechnology from public sources
for 2008 exceeded $7 billion. The market size for nanotechnology is expected to
grow to over $64.2 billion by 2019 with over commercial 50,000 products contain-
ing engineered nanomaterials (ENMs).
Nanotechnology promises new materials for industrial applications by having
new or enhanced physico-chemical properties that are different in comparison to
their micron-sized counterparts. However, as in all industrial applications, the
potential exposure of humans and the environment to these materials is inevitable.
As these materials go through their life-cycle – from development, to manufacture,
to consumer usage, to final disposal – different human groups (workers, bystanders,
consumers), animal species (e.g. worm, fish or humans through secondary expo-
sure) and environmental compartments (air, soil, sediment, ground and surface
water) will be exposed to them. A growing body of evidence has shown a range of
toxic effects from ENM suggesting that even their low mass exposure will result in
a risk to human health or the environment. Furthermore, the toxicity of ENM can be
attributed to some of their physico-chemical properties such as surface area, charge
or reactivity. There is thus a clear need for a better understanding of the relationship
between ENM structure and properties and the adverse responses they evoke in liv-
ing organisms. Clearly, understanding this relationship will greatly help in design-
ing future ENM by using the ‘safe by design’ approach.
The European Union (EU) has set ambitious plans for the future of nanotech-
nology. Accordingly, the regulatory agencies are urgently seeking ways of assess-
ing the potential health risks caused by exposure to ENM. Available data are so far
insufficient to meet this need. This is because research to determine impacts of
ENM on diverse biological systems, although essential for assessing their hazard,
is time-consuming and expensive, and has ethical implications when animals are
used. In silico methods for predicting biological effects of ENM play an important,
complementary role to that of experimental research. Due to the complexity of
interactions of ENM with living organisms, and the increasing use of high-
throughput screening methods to generate large in vitro datasets, statistical
vii
viii Introduction
modelling (e.g. quantitative structure-activity relationships, QSAR and machine
learning methods (e.g. neural networks) are becoming methods of choice. They
have been applied successfully to the development of pharmaceuticals and crop
protection agents over the past several decades.
QSAR methods are increasingly being used by regulatory agencies for chemical
risk assessment. They have also been applied more recently to modelling the prop-
erties of materials, including ENM. Although QSAR techniques have only started
to be used to predict biological effects of ENM, they have shown encouraging initial
results. However, ENMs present significantly different obstacles to modelling com-
pared to drugs and industrial chemicals, and specific models based on the structures
and properties of ENMs are therefore needed. Issues pertinent to the development
of computational methods for modelling ENM properties and their biological
effects are central to this book, together with development in research that are
required if the regulation of nanomaterials is to be assisted by computational tools
within the next decade. Preliminary work demonstrates that these models show con-
siderable promise for modelling ENM toxic effects. They are also useful for predict-
ing toxic effects of new ENM based on their material properties and for classifying
ENM according to common properties or common biological endpoints. Ultimately,
the predictive power of these models will lead to considerable reduction in the use
of animal experimentation.
In the frame of the FP7 program, the EC funded a total of six research projects
and the COST Action TD1204 Modena, specifically devoted to various aspects of
nanotoxicity modelling. All the projects worked in close coordination to develop
new methodologies and tools suitable for transforming raw nanosafety data into
new insight on the mechanisms governing nano-bio interactions. The most relevant
outcomes of some of these modelling projects are presented either as chapters on
modelling or as integrated case studies in the safety/hazard assessment of ENMs.
This book reflects on the co-operation between international scientists; the con-
tributors cover a truly multidisciplinary spectrum of scientific disciplines including
material sciences, metrology, exposure sciences, mammalian toxicology and eco-
toxicology. In addition, transversal approaches entangle these disciplines providing
the breadth and depth necessary to foster understanding the molecular rationale of
toxicity of nanoparticles; these include computer science (databases, data mining)
mathematics (data analysis ad modelling) and systems biology so that toxicity can
be understood and tackled at any possible level, ranging from molecular to living
organism.
Edinburgh, UK Lang Tran
Madrid, Spain Miguel A. Bañares
Tarragona, Spain Robert Rallo
Contents
Part I Characterisation
1 Engineered Nanomaterials: Their Physicochemical
Characteristics and How to Measure Them . . . . . . . . . . . . . . . . . . . . . . . 3
Rambabu Atluri and Keld Alstrup Jensen
Part II Exposure
2 Assessment of Human Exposure to ENMs . . . . . . . . . . . . . . . . . . . . . . . 27
Araceli Sánchez Jiménez and Martie van Tongeren
3 The Life Cycle of Engineered Nanoparticles . . . . . . . . . . . . . . . . . . . . . 41
David González-Gálvez, Gemma Janer, Gemma Vilar,
Alejandro Vílchez, and Socorro Vázquez-Campos
4 From Dose to Response: In Vivo Nanoparticle Processing
and Potential Toxicity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
Uschi M. Graham, Gary Jacobs, Robert A. Yokel, Burtron H. Davis,
Alan K. Dozier, M. Eileen Birch, Michael T. Tseng,
Günter Oberdörster, Alison Elder, and Lisa DeLouise
Part III Modelling
5 Literature Review of (Q)SAR Modelling
of Nanomaterial Toxicity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
Ceyda Oksel, Cai Y. Ma, Jing J. Liu, Terry Wilkins,
and Xue Z. Wang
6 Systems Biology to Support Nanomaterial Grouping . . . . . . . . . . . . . 143
Christian Riebeling, Harald Jungnickel, Andreas Luch,
and Andrea Haase
ix
x Contents
7 Multiscale Modelling of Bionano Interface . . . . . . . . . . . . . . . . . . . . . 173
Hender Lopez, Erik G. Brandt, Alexander Mirzoev, Dmitry Zhurkin,
Alexander Lyubartsev, and Vladimir Lobaskin
8 Biological Surface Adsorption Index of Nanomaterials:
Modelling Surface Interactions of Nanomaterials
with Biomolecules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207
Ran Chen and Jim E. Riviere
Part IV Case Studies
9 An Integrated Data-Driven Strategy for Safe- by- Design
Nanoparticles: The FP7 MODERN Project . . . . . . . . . . . . . . . . . . . . . 257
Martin Brehm, Alexander Kafka, Markus Bamler,
Ralph Kühne, Gerrit Schüürmann, Lauri Sikk, Jaanus Burk,
Peeter Burk, Tarmo Tamm, Kaido Tämm, Suman Pokhrel,
Lutz Mädler, Anne Kahru, Villem Aruoja, Mariliis Sihtmäe,
Janeck Scott-Fordsmand, Peter B. Sorensen, Laura Escorihuela,
Carlos P. Roca, Alberto Fernández, Francesc Giralt,
and Robert Rallo
10 Compilation of Data and Modelling of Nanoparticle
Interactions and Toxicity in the NanoPUZZLES Project . . . . . . . . . . 303
Andrea-Nicole Richarz, Aggelos Avramopoulos,
Emilio Benfenati, Agnieszka Gajewicz,
Nazanin Golbamaki Bakhtyari, Georgios Leonis,
Richard L Marchese Robinson, Manthos G Papadopoulos,
Mark TD Cronin, and Tomasz Puzyn
11 Case Study III: The Construction of a Nanotoxicity
Database – The MOD-ENP- TOX Experience . . . . . . . . . . . . . . . . . . . 325
Hanne Vriens, Dominik Mertens, Renaud Regret,
Pinpin Lin, Jean- Pierre Locquet, and Peter Hoet
Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 345
