# ELIXIR and Toxicology: a community in development

Marvin Martens, Rob Stierum, Emma Schymanski, Chris Evelo, Reza Aalizadeh, Hristo Aladjov, Kasia Arturi, Karine Audouze, Pavel Babica, Karel Berka, et al.

► To cite this version:

Marvin Martens, Rob Stierum, Emma Schymanski, Chris Evelo, Reza Aalizadeh, et al. ELIXIR and Toxicology: a community in development. F1000Research, 2021, 10, pp.1129. 10.12688/f1000research.74502.1. pasteur-03680151

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OPINION ARTICLE

ELIXIR and Toxicology: a community in development [version
1; peer review: 1 approved, 1 approved with reservations]

Marvin Martens<fnref n="1" />, Rob Stierum<fnref n="2" />, Emma L. Schymanski<fnref n="3" />, Chris T. Evelo<fnref n="1" />,<fnref n="4" />,
Reza Aalizadeh<fnref n="5" />, Hristo Aladjov<fnref n="6" />, Kasia Arturi<fnref n="7" />, Karine Audouze<fnref n="8" />, Pavel Babica<fnref n="9" />,
Karel Berka<fnref n="10" />, Jos Bessems<fnref n="11" />, Ludek Blaha<fnref n="9" />, Evan E. Bolton<fnref n="12" />,
Montserrat Cases<fnref n="13" />, Dimitrios E. Damalas<fnref n="5" />, Kirtan Dave<fnref n="14" />, Marco Dilger<fnref n="15" />,
Thomas Exner<fnref n="16" />, Daan P. Geerke<fnref n="17" />, Roland Grafström<fnref n="18" />,<fnref n="19" />, Alasdair Gray²⁰,
John M. Hancock²¹, Henner Hollert²², Nina Jeliazkova²³, Danyel Jennen²⁴,
Fabien Jourdan²⁵,²⁶, Pascal Kahlem²⁷, Jana Klanova<fnref n="9" />, Jos Kleinjans²⁴,
Todor Kondic<fnref n="3" />, Boï Kone²⁸, Iseult Lynch²⁹, Uko Maran³⁰,
Sergio Martinez Cuesta³¹, Hervé Ménager³²,³³, Steffen Neumann³⁴,
Penny Nymark<fnref n="18" />, Herbert Oberacher³⁵, Noelia Ramirez³⁶, Sylvie Remy<fnref n="11" />,
Philippe Rocca-Serra³⁷, Reza M. Salek³⁸, Brett Sallach³⁹,
Susanna-Assunta Sansone³⁷, Ferran Sanz⁴⁰, Haralambos Sarimveis⁴¹,
Sirarat Sarntivijai²¹, Tobias Schulze⁴², Jaroslav Slobodnik⁴³, Ola Spjuth⁴⁴,
Jonathan Tedds²¹, Nikolaos Thomaidis<fnref n="5" />, Ralf J.M. Weber⁴⁵,
Gerard J.P. van Westen⁴⁶, Craig E. Wheelock⁴⁷,⁴⁸, Antony J. Williams⁴⁹,
Hilda Witters<fnref n="11" />, Barbara Zdrazil⁵⁰, Anže Županič⁵¹, Egon L. Willighagen<fnref n="1" />

<footnote n="1">¹Department of Bioinformatics - BiGCaT, Maastricht University, Maastricht, 6229 ER, The Netherlands</footnote>

<footnote n="2">²Risk Analysis for Products In Development (RAPID), Netherlands Organisation for applied scientific research TNO, Utrecht, 3584 CB, The Netherlands</footnote>

<footnote n="3">³Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Belvaux, 4367, Luxembourg</footnote>

<footnote n="4">⁴Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, 6229 EN, The Netherlands</footnote>

<footnote n="5">⁵Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Athens, 15771, Greece</footnote>

<footnote n="6">⁶Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, 1113, Bulgaria</footnote>

<footnote n="7">⁷Department Environmental Chemistry, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, 8600, Switzerland</footnote>

<footnote n="8">⁸Université de Paris, T3S, Inserm UMR-S1124, Paris, F-75006, France</footnote>

<footnote n="9">⁹RECETOX, Faculty of Science, Masaryk University, Brno, Czech Republic</footnote>

<footnote n="10">¹⁰Department of Physical Chemistry, Palacky University Olomouc, Olomouc, 77146, Czech Republic</footnote>

<footnote n="11">¹¹Health Unit, Flemish Institute for Technological Research (VITO), Mol, 2400, Belgium</footnote>

<footnote n="12">¹²National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA</footnote>

<footnote n="13">¹³Chemotargets SL, Barcelona, 08028, Spain</footnote>

<footnote n="14">¹⁴School of Science, GSFC University, Gujarat, 391750, India</footnote>

<footnote n="15">¹⁵Forschungs- und Beratungsinstitut Gefahrstoffe (FoBiG) GmbH, Freiburg im Breisgau, 79106, Germany</footnote>

<footnote n="16">¹⁶Seven Past Nine, Cerknica, 1380, Slovenia</footnote>

<footnote n="17">¹⁷AIMMS Division of Molecular Toxicology, Vrije Universiteit, Amsterdam, 1081 HZ, The Netherlands</footnote>

<footnote n="18">¹⁸Institute of Environmental Medicine, Karolinska Institute, Stockholm, 17177, Sweden</footnote>

<footnote n="19">¹⁹Department of Toxicology, Misvik Biology, Turku, 20520, Finland</footnote>
²⁰Department of Computer Science, Heriot-Watt University, Edinburgh, UK

²¹ELIXIR Hub, Wellcome Genome Campus, Cambridge, CB10 1SD, UK

²²Department Evolutionary Ecology & Environmental Toxicology (E3T), Goethe-University, Frankfurt, D-60438, Germany

²³Ideaconsult Ltd., Sofia, Bulgaria

²⁴Department of Toxicogenomics, Maastricht University, Maastricht, 6200 MD, The Netherlands

²⁵Toxalim (Research Centre in Food Toxicology), Université de Toulouse, INRAE, ENVT, INP-Purpan, UPS, Toulouse, France

²⁶MetaboHUB, National Infrastructure of Metabolomics and Fluxomics, Toulouse, France

²⁷Scientific Network Management SL, Barcelona, 08015, Spain

²⁸Faculty of Pharmacy, Malaria Research and Training Center, Bamako, BP:1805, Mali

²⁹School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK

³⁰Department of Chemistry, University of Tartu, Tartu, 50411, Estonia

³¹Data Sciences and Quantitative Biology, Discovery Sciences, AstraZeneca, Cambridge, UK

³²Bioinformatics and Biostatistics Hub, Institut Pasteur, Université de Paris, Paris, F-75015, France

³³Institut Français de Bioinformatique, Evry, F-91000, France

³⁴Research group Bioinformatics and Scientific Data, Leibniz Institute of Plant Biochemistry, Halle, 06120, Germany

³⁵Institute of Legal Medicine and Core Facility Metabolomics, Medical University of Innsbruck, Innsbruck, A-6020, Austria

³⁶Institut d'Investigacio Sanitaria Pere Virgili-Universitat Rovira i Virgili, Tarragona, 43007, Spain

³⁷Data Readiness Group, Department of Engineering Science, University of Oxford, Oxford, UK

³⁸International Agency for Research on Cancer, World Health Organisation, Lyon, 69372, France

³⁹Department of Environment and Geography, University of York, UK, York, YO10 5NG, UK

⁴⁰Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), Barcelona, 08003, Spain

⁴¹National Technical University of Athens, Athens, 15780, Greece

⁴²Helmholtz Centre for Environmental Research - UFZ, Leipzig, 04318, Germany

⁴³Environmental Institute, Koš, 97241, Slovakia

⁴⁴Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Uppsala, SE-75124, Sweden

⁴⁵School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK

⁴⁶Division of Drug Discovery and Safety, Leiden Academic Center for Drug Research, Leiden, 2333 CC, The Netherlands

⁴⁷Department of Medical Biochemistry and Biophysics, Karolinska Institute, Stockholm, 17177, Sweden

⁴⁸Department of Respiratory Medicine and Allergy, Karolinska University Hospital, Stockholm SE-141-86, Sweden

⁴⁹Center for Computational Toxicology and Exposure, United States Environmental Protection Agency, Research Triangle Park, NC 27711, USA

⁵⁰Department of Pharmaceutical Sciences, University of Vienna, Vienna, 1090, Austria

⁵¹Department Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, 1000, Slovenia

**V1** First published: 08 Nov 2021, 10(ELIXIR):1129
https://doi.org/10.12688/f1000research.74502.1

Latest published: 08 Nov 2021, 10(ELIXIR):1129
https://doi.org/10.12688/f1000research.74502.1

## Abstract

Toxicology has been an active research field for many decades, with academic, industrial and government involvement. Modern omics and computational approaches are changing the field, from merely disease-specific observational models into target-specific predictive models. Traditionally, toxicology has strong links with other fields such as biology, chemistry, pharmacology and medicine. With the rise of synthetic and new engineered materials, alongside ongoing prioritisation needs in chemical risk assessment for existing chemicals, early predictive evaluations are becoming of utmost importance to both scientific and regulatory purposes. ELIXIR is an intergovernmental organisation that brings together life science resources from across Europe. To coordinate the linkage of various

## Open Peer Review

Approval Status ? ✓

1

2

version 1

08 Nov 2021

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1. **Christopher Southan** University of Edinburgh, Edinburgh, UK
Medicines Discovery Catapult, Macclesfield, UK

2. **Marta Eide** University of Bergen, Bergen,
life science efforts around modern predictive toxicology, the establishment of a new ELIXIR Community is seen as instrumental. In the past few years, joint efforts, building on incidental overlap, have been piloted in the context of ELIXIR. For example, the EU-ToxRisk, diXa, HeCaToS, transQST, and the nanotoxicology community have worked with the ELIXIR TeSS, Bioschemas, and Compute Platforms and activities. In 2018, a core group of interested parties wrote a proposal, outlining a sketch of what this new ELIXIR Toxicology Community would look like. A recent workshop (held September 30th to October 1st, 2020) extended this into an ELIXIR Toxicology roadmap and a shortlist of limited investment-high gain collaborations to give body to this new community. This Whitepaper outlines the results of these efforts and defines our vision of the ELIXIR Toxicology Community and how it complements other ELIXIR activities.

## Keywords

Toxicology, ELIXIR, interoperability, FAIR

Norway

Centre for Digital Life Norway, Bergen,

Norway

Any reports and responses or comments on the article can be found at the end of the article.

elixir

This article is included in the ELIXIR gateway.

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This article is included in the Nanotoxicology collection.

**Corresponding authors:** Marvin Martens (marvin.martens@maastrichtuniversity.nl), Egon L. Willighagen (egon.willighagen@maastrichtuniversity.nl)

**Author roles:** Martens M: Conceptualization, Writing - Original Draft Preparation, Writing - Review & Editing; Stierum R: Conceptualization, Writing - Original Draft Preparation, Writing - Review & Editing; Schymanski EL: Conceptualization, Writing - Original Draft Preparation, Writing - Review & Editing;velo CT: Conceptualization, Writing - Original Draft Preparation, Writing - Review & Editing; Alizadeh R: Writing - Review & Editing; Aladjov H: Writing - Review & Editing; Arturi K: Writing - Review & Editing; Audouze K: Writing - Review & Editing; Babica P: Writing - Review & Editing; Berka K: Writing - Review & Editing; Bessems J: Writing - Original Draft Preparation, Writing - Review & Editing; Blaha L: Writing - Review & Editing; Bolton EE: Writing - Review & Editing; Cases M: Writing - Review & Editing; Damalas DE: Writing - Review & Editing; Dave K: Writing - Review & Editing; Dilger M: Writing - Review & Editing; Exner T: Writing - Original Draft Preparation, Writing - Review & Editing; Geerke DP: Writing - Original Draft Preparation, Writing - Review & Editing; Grafström R: Writing - Original Draft Preparation, Writing - Review & Editing; Gray A: Writing - Review & Editing; Hancock JM: Writing - Review & Editing; Hollert H: Writing - Review & Editing; Jeliazkova N: Writing - Original Draft Preparation, Writing - Review & Editing; Jennen D: Writing - Original Draft Preparation, Writing - Review & Editing; Jourdan F: Writing - Review & Editing; Kahlem P: Writing - Review & Editing; Klanova J: Writing - Review & Editing; Kleinjans J: Writing - Original Draft Preparation, Writing - Review & Editing; Kondic T: Writing - Review & Editing; Kone B: Writing - Review & Editing; Lynch I: Writing - Original Draft Preparation, Writing - Review & Editing; Maran U: Writing - Review & Editing; Martinez Cuesta S: Writing - Review & Editing; Ménager H: Writing - Original Draft Preparation, Writing - Review & Editing; Neumann S: Writing - Review & Editing; Nymark P: Writing - Original Draft Preparation, Writing - Review & Editing; Oberacher H: Writing - Review & Editing; Ramirez N: Writing - Review & Editing; Remy S: Writing - Review & Editing; Rocca-Serra P: Writing - Review & Editing; Salek RM: Writing - Review & Editing; Sallach B: Writing - Review & Editing; Sansone SA: Writing - Review & Editing; Sanz F: Writing - Review & Editing; Sarimveis H: Writing - Original Draft Preparation, Writing - Review & Editing; Sarntivijai S: Writing - Review & Editing; Schulze T: Writing - Review & Editing; Slobodnik J: Writing - Review & Editing; Spjuth O: Writing - Original Draft Preparation, Writing - Review & Editing; Tedds J: Writing - Review & Editing; Thomaidis N: Writing - Review & Editing; Weber RJM: Writing - Review & Editing; van Westen GJP: Writing - Review & Editing; Wheelock CE: Writing - Review & Editing; Williams AJ: Writing - Review & Editing; Witters H: Writing - Review & Editing; Zdrazil B:
**Writing – Review & Editing; Županič A:** Writing – Review & Editing; **Willighagen EL:** Conceptualization, Writing – Original Draft Preparation, Writing – Review & Editing

**Competing interests:** No competing interests were disclosed.

**Grant information:** This work received funding from the European Union's Horizon 2020 research infrastructure programme via the OpenRiskNet project under grant agreement No. 731075. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 681002 (EU-ToxRisk). This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 814572. SN acknowledges BMBF funding under grant number 031L0107. This work was supported by OBERON (https://oberon-4eu.com), a project funded by the European Union's Horizon 2020 research and innovation program under the grant agreement No. 825712. This work was supported by the European Union, 's Horizon 2020 research and innovation program HBM4EU, grant agreement No. 733032 (https://www.hbm4eu.eu). Supported by the European Union's Horizon 2020 programme under the Marie Skłodowska-Curie grant agreement No. 859891. Where authors are identified as personnel of the International Agency for Research on Cancer/World Health Organization, the authors alone are responsible for the views expressed in this article, and they do not necessarily represent the decisions, policy, or views of the International Agency for Research on Cancer/World Health Organization. This work was supported by the European Union, 's Horizon 2020 research and innovation program HARMLESS, grant agreement No. 953183. This work was supported by the European Union, 's Horizon 2020 research and innovation program Gov4Nano, grant agreement No. 814401. This work was supported by the Swedish Fund for Research Without Animal Experiments under grant number N2020-0005. This work was supported by the European Union, 's Horizon 2020 research and innovation program NTS-EXPOSURE, Grant agreement ID: 896141. This work was supported by the European Union, 's LIFE program LIFE-APEX, Grant agreement ID: LIFE17 ENV/SK/000355. This study was funded by the German Environment Agency within the PHION project (grant number 3718 674150). The Data Readiness Group is supported, in this ELIXIR Community, by the H2020 Precision Toxicology project (H2020-EU 965406). The Data Readiness Group is supported, in this ELIXIR Community, by the Wellcome ISA-InterMine project (208381/A/17/Z). The Data Readiness Group is supported, in this ELIXIR Community, by the Wellcome FAIRsharing project (212930/Z/18/Z). This work received funding from the European Union's Horizon 2020 research and innovation programme RiskGONE Project under grant agreement No. 814425. NR's research is funded by a Miguel Servet contract (CO19/00060) from Instituto de Salud Carlos III, cofinanced by the European Union. UM (Uni. of Tartu) is grateful for support to Ministry of Education and Research, Republic of Estonia through Estonian Research Council (grant number IUT34-14) and to European Union European Regional Development Fund through Foundation Archimedes (grant number TK143, Centre of Excellence in Molecular Cell Engineering). Development and Implementation of a Sustainable Modelling Platform for NanoInformatics. Linking LRI Ambit chemoinformatic system with the IUCLID substance database to support read-across of substance endpoint data and category formation. This work was supported by the French Ministry of Research and National Research Agency as part of the French MetaboHUB, the national metabolomics and fluxomics infrastructure (Grant ANR-INBS-0010). This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement GOLIATH No. 825489. Where authors are identified as personnel of the International Agency for Research on Cancer/World Health Organization, the authors alone are responsible for the views expressed in this article, and they do not necessarily represent the decisions, policy, or views of the International Agency for Research on Cancer/World Health Organization. The views expressed in this manuscript are solely those of the authors and do not represent the policies of the U.S. Environmental Protection Agency. Mention of trade names of commercial products should not be interpreted as an endorsement by the U.S. Environmental Protection Agency.

*The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.*

**Copyright:** © 2021 Martens M et al. This is an open access article distributed under the terms of the [Creative Commons Attribution License](https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**How to cite this article:** Martens M, Stierum R, Schymanski EL et al. **ELIXIR and Toxicology: a community in development** [version 1; peer review: **1 approved**, **1 approved with reservations**] F1000Research 2021, **10**(ELIXIR):1129 https://doi.org/10.12688/f1000research.74502.1

**First published:** 08 Nov 2021, **10**(ELIXIR):1129 https://doi.org/10.12688/f1000research.74502.1
## Introduction of the ELIXIR Toxicology Community

Toxicology as a field tries to understand the negative consequences that may arise from the interactions of chemicals with living organisms. In this ELIXIR (European life-sciences Infrastructure for biological Information)¹ Community, the focus will be primarily the protection of human health. There are a number of both chemical and biological “interoperability” issues key to the toxicology field that translate into data interoperability issues. These include the connection between the action and activity of a particular chemical compound to its effective amount available at a biological target (the link between toxicodynamics and toxicokinetics). Typically this is also a link between biological data analysis (including large-scale multi-omics) and kinetic modelling. Other examples include interactions between a compound and its target (a protein, nucleic sequence or membrane structure for instance). This is primarily based on the interplay between chemistry (the chemical structure and, for example, its related properties in terms of functional groups, charge, shape and related binding affinity) and biochemistry (like biomolecular 3D structures). Also, mixture toxicity needs to be considered as combinations of chemicals with synergistic or antagonistic behaviour, or a combination thereof. While chemicals with similar modes of action may act in terms of concentration addition, those with different modes may rather act according to independent action.²,³ Substances with low toxicity may interact in concentration addition rather than as excess toxicity drivers of one compound. Often there is a need to translate the knowledge about one compound into knowledge about other compounds, where approaches like quantitative structure-activity relationships (QSARs) help to elucidate this knowledge and predict required property and toxicity, and in more general when “read-across approaches” come into play that are based on chemical data only, biological data only, or are hybrid.⁴,⁵ These again need detailed information about the relationships between related chemical compounds, specific properties and toxicological endpoints and, when considering chemical-biological interactions, details regarding both the chemical structures and adequate descriptions of the biological targets. Since toxicological endpoints can be represented in a myriad of ways, the toxicological effect data are often scattered over multiple repositories and databases hosting different types of data; i.e. chemical structures, toxicity data (in vivo and in vitro), biological target details, and omics data. This itself is not a problem, but the separation and segregation make the data difficult to find and to connect. Currently, many of these deposition databases (where datasets can be archived) do not provide adequate descriptions regarding typical toxicological study designs and parameters, quality control, data acceptance criteria, or even clear identification of the compounds tested. This all adds to the need for an adequate FAIRification process, to make toxicology data more Findable, Accessible, Interoperable and Reusable (FAIR - see Go-FAIR).⁶,⁷

The field of toxicology would certainly benefit from clear, standardized guidelines for data capture, approaches to integrate and connect across multiple databases, clear data licensing for these data repositories, and tools that support accessing the data (as being developed by the ELIXIR Converge data brokerage work). Existing study capture tools can be extended with templates defined for toxicology, which end up in a central place (e.g. Biosamples⁸) with links to omics and other data distributed over technology-specific deposition databases and BioStudies.⁹ Relevant portals (e.g. FAIR-sharing.org¹⁰,¹¹) should then be able to identify these studies, also linking to existing but scattered toxicology databases.

Risk assessment, consisting of hazard identification, characterisation and risk evaluation in relation to exposure, involves expert opinions based on discussions and data interpretation. Streamlining this process is important also because of the huge number of chemicals known and produced in chemistry, biotechnology or food production, with over 350,000 chemicals documented on the global market.¹² However, expert evaluation is and will remain crucial and calls for extensive data provenance both for the actual data (how was it measured, where was it published, whom to give credit for it), and for the risk assessments themselves. Interestingly this process stumbles on problems and solutions that have much in common with other fields, where part of the data need to be hidden and other parts can be publicly accessed, as observed in pilot approaches in genetics, or patient data repositories.

Toxicology, while established as discipline, is also rapidly developing in areas, where, for example, new molecular methods to describe the adverse outcome of exposure to a toxic substance are not yet fully established. This offers opportunities for integration in systems biology approaches building on molecular pathway descriptions that benefit from modern network biology approaches. Compound profiling, where, for example, using omics methods to characterize the effect of compounds on cells, are generally useful for categorizing compounds, or for the development of predictive pathway models. For such studies, the availability of high-quality annotations for compounds is of paramount importance to enable the use of omics profiles in toxicology.

Toxicology is also an applied field. There are important applications of toxicity tests in the regulatory field and large amounts of data are collected for that purpose, often for different (governmental) agencies. Making this data more Findable and Reusable is often seen as an important way to reduce both animal testing and the cost of registration of new compounds. If some data is not available to the public due to ownership by companies or other constraints, indexes should be developed to enable the use of this data in an aggregated form (such as the SPIN index of the Swedish Chemicals agency (KEMI) and other Nordic chemical agencies). Typically, regulatory use requires very precise and rigid
descriptions of protocols, including reporting methods. On the other hand, better insights into the toxicological
mechanisms, including interactions between chemicals, benefit from more innovative research methods (e.g. single-
cell omics, induced stem cell applications, imaging methods) and from creative development of new analysis methods.
While it is beneficial to combine results from both types of approaches (termed New Approach Methods (NAM) in the
regulatory field), the corresponding interoperability issues are often quite different.

User community

Europe is steadily increasing demands on the risk assessment of chemicals, drugs, cosmetics ingredients and nanomaterials to lead to safer products, resulting in a strong toxicology research community with sub-communities in, for example, the drug development, environmental, nanomaterial and rare-disease areas. Recent changes in European law for animal testing and new demands for testing of lower-volume chemicals and nanomaterials have triggered large-scale research into alternative testing approaches. These activities not only produce new biological and mechanistic insights, but also large amounts of new data, which have to be managed and shared for re-usage to avoid unnecessary duplication of experiments and, in this way, reduce animal testing. The goal is that the combination of data from integrated *in vitro* and *in silico* approaches will support (ultimately personalized) risk/benefit health analysis, safer drug innovation with fewer needs to withdraw after registration, a fact-based perception of chemical safety, safe-by-design nanomaterials and sustainable and safe economies.

The European Union supports toxicological and risk assessment projects with various funding programs. Recently, large collections of data have been released, resulting from research clusters, such as SEURAT-1,¹³ the EU NanoSafety Cluster (NSC) with NANoREG, EU-ToxRisk,¹⁴ the NORMAN Network, and the EU Innovative Medicines Initiative (IMI) funded projects related to drug toxicology, including eTOX,¹⁵ eTRANSAFE,¹⁶ and Eurion.¹⁷ Data from these and other projects are becoming available, sometimes as Open Data (e.g. NANoREG) and sometimes as FAIR data. An example of the latter is European REACH data, which has recently been made FAIR by the Cefic-LRI-funded project AMBIT-LRI.¹⁸ Furthermore, the FAIRplus project is collaborating with eTOX on making their data more FAIR, and the new Precision Toxicology will develop a data commons following the FAIR principles.

However, there are a few opportunities for data handling that need to be taken.<sup>19,20</sup> Recent studies show how powerful the combination of toxicology information and omics data is,<sup>21,22</sup> but to be able to obtain the statistical significance to draw these conclusions, data from the US and Japan had to be combined. In contrast to large data sets like DrugMatrix,<sup>23</sup> ToxCast/Tox21,<sup>24</sup> and TG-GATEs<sup>25</sup> from these countries, data from European projects is often not sufficiently integrated. Luckily, there are signs that the community is going in the right direction, e.g. the aforementioned data integration by diXa,<sup>26</sup> NANoREG and REACH.<sup>27</sup> With respect to the European Chemical Industry, various authors have been involved in other Cefic-LRI activities related to data management (AIMT-3, AIMT-4).

In addition, the eTOX project²⁸ has established data integration approaches e.g. to enable the development of QSARs relating chemical structures to *in vivo* toxicopathological outcomes. As such, the project also delivered databases and approaches to ontology development, text mining approaches, and approaches for prediction of drug metabolism and pharmacokinetic features. Moreover, in 2017 the Organisation for Economic Co-operation and Development (OECD) performed an online survey underscoring the fact that data integration for safety is of global concern for ultimate risk assessment. The purpose of the resulting knowledge base is the integration of eCHEMportal (The Global Portal to Information on Chemical Substances²⁹), IUCLID (International Uniform ChemicaL Information Database³⁰), and OECD's QSAR Toolbox³¹ supporting the development of Adverse Outcome Pathways and associated infrastructures (AOP-Wiki).³² Despite these positive developments, the 'data integration struggle' from various perspectives (omics, computational chemistry and more 'conventional' toxicological data within REACH and pharmaceutical industry setting) remains a challenge.

Roadmap

The above initiatives are mainly driven by user communities themselves: chemical industry, funding agencies, pharmaceutical companies, governmental agencies and organisations such as Member State organisations, the OECD and non-governmental organisations (NGOs). ELIXIR can contribute strongly to the existing infrastructure projects from a cheminformatics and bioinformatics perspective, providing tools and guidelines, linking and harmonizing the ongoing activities, serving the toxicology users.

For future risk assessment paradigms solely based on human-derived models, and in this way of higher relevance for human adverse effects,³³ various data types will need to be integrated into and cross the conventional boundaries of risk assessment. This involves external exposure assessment (e.g. via workplace or environmental modelling and measurements³⁴,³⁵), internal exposure characterisation (ADME-TK (absorption, distribution, metabolism, and excretion - toxicokinetics) e.g. via modelling and biomarker-based detection), toxicodynamics on a molecular level,
and cell and systems biology. In this way, more data-driven mechanism-based evaluations and supporting data can integrate into regulatory risk assessment. There will not only be more but also more diverse data as e.g. internal exposure data may be inferred from biomonitoring data and/or physiologically-based toxicokinetic modelling to estimate target dose available at the active sites involved in the molecular initiating events of Adverse Outcome Pathways (AOPs).

Another relevant topic is the concept of the exposome,³⁶⁻³⁸ which aims at characterising lifetime exposure (not only to chemicals in the narrowest sense, but also dietary components, lifestyle factors, environmental exposures, etc) in relation to health outcome. Often, vulnerable periods of life (infancy, childhood, and old age) are investigated, and the evaluation also integrates epidemiology. This is one clear demonstration of the trend that the previously distinct areas of toxicology, drug and product design and personalized/precision medicine³⁹ but also environment and health and epidemiology are moving closer together. Data sharing will be increasingly necessary across these disciplines. High throughput data analysis in exposomics, for instance, shares many parallels with metabolomics and other higher level omics analyses, with an added layer of chemical complexity on top.³⁸

The toxicology community is large and well established. The current list of proponents of an ELIXIR Toxicology Community only reflects a subset of a much larger community with a lot of commitments to, and activities around open collaboration. It has clear omics, knowledge management and data infrastructure needs to accommodate the increasing wish to predict toxicology without animal testing (e.g. in SEURAT-1, EU-ToxRisk, eTOX OBERON⁴⁰). Foreseeing this need for better infrastructures, the community has previously contacted ELIXIR for collaboration. Various domain-specific projects exist that service the toxicology community with computational and database knowledge (OpenRiskNet, NanoCommons) that can translate ELIXIR knowledge to the respective communities. These infrastructure projects are the successors of research projects focusing on data management, including diXa,²⁶ ToxBank⁴¹ and eNanoMapper.⁴²

To benefit the research community, small and medium-sized enterprises (SMEs) and larger industry, and to enable further future support to regulatory applications and upcoming calls (e.g. Green Deal⁴³,⁴⁴), we need to reach an inclusive ecosystem of data, evaluation and modelling tools. The current separate consortia from different toxicity-related and neighbouring disciplines already work towards data and knowledge that is FAIR.⁶ After all, these aspects are essential to efficiently assess the risk of new compounds and materials, as well as combined risks of current stressors (e.g. under the exposome concept). To further accelerate these activities, more toxicology-related data and knowledge need to be linked, such as on physiologically based toxicokinetic (PBTK) modelling, biological pathways describing affected metabolism and cell biology processes, metabolism, metabolic models and metabolism predictions, drug-response, omics (biological identity), chemical structures and associated metadata (use, hazard, transformations), QSARs, AOPs, REACH dossiers, etc. Simultaneously, an extension towards the human (preclinical toxicology) discipline should be initiated, in which exposure data are combined with internal exposure and early biomarkers of effect data (e.g. from the European Human Biomonitoring Initiative (HBM4EU)⁴⁵ and environmental data from NORMAN⁴⁶,⁴⁷) towards pathways of toxicity. Interoperability with the standardization efforts of clinical research by CDISC is important.

However, to reach such interoperable toxicology, resources need to be better integrated. Despite the work of many projects, their FAIR features can still be improved and applying newly developed FAIR metrics will help steer this.⁴⁸ Even though there is overlap in content with existing ELIXIR Communities (Table 1, key demands specifically fostering the integration for interoperable toxicology and risk assessment include the following roadmap¹⁹,²⁰):

* chemical structure interoperability challenges (e.g. links to ELIXIR Metabolomics Community⁴⁹)

* metadata, open standards (e.g. links to ELIXIR Interoperability Platform, and TeSS⁵⁰)

* continued ontology development (e.g. links to ELIXIR Interoperability Platform and Ontology Lookup Service)

* interoperable computation (e.g. links to the Galaxy⁵¹ and bio.tools⁵² communities)

* interactions with other ELIXIR Core Data Resources (e.g. Ensembl and Europe PMC)

* interactions with other communities, including nanomedicine and health

* deployment of existing tools and modelling approaches on the ELIXIR Compute infrastructure (also allowing future growth towards risk estimations needing Monte Carlo approaches)

* integration of ELIXIR AAI
<table><caption>**Table 1.** Overlap of the proposed ELIXIR Toxicology Community with ELIXIR platforms and communities.</caption><thead><tr><th></th><th>Overlap</th></tr></thead><tbody><tr><td><strong>Platforms</strong></td><td></td></tr><tr><td>Tools</td><td>Semantic annotation of services (e.g. <u>bio.tools</u><sup>52</sup>). Alignment with <u>BioContainers</u><sup>62</sup> to make toxicology reproducible and redeployable (e.g. <u>OpenRiskNet</u>)</td></tr><tr><td>Data</td><td>BioStudies was co-developed by the CHEMBL-EBI team, and builds on <u>ArrayExpress</u><sup>63</sup>, an ELIXIR Core Data Resource. Better adoption of the core resources. Sharing toxicology workflows on <u>WorkflowHub</u></td></tr><tr><td>Compute</td><td>ELIXIR Authentication and Authorisation Infrastructure (AAI) is used by OpenRiskNet. Better and more sustainable compute infrastructure reuse of core elements (ELIXIR AAI, modelling toolsets)</td></tr><tr><td>Interoperability</td><td>FAIR and Research Data Management (RDM) standards have already been adopted by various projects. Registries of toxicology tools need integration with FAIRsharing; There is a huge identifier mapping service need (also for ontology mapping and chemical (sub) structures), Common Workflow Language (CWL)<sup>69</sup> as interoperability for workflow, and standardized data exchange formats like the Investigation-Study-Assay (ISA) standard.<sup>64</sup></td></tr><tr><td>Training</td><td>Bioschemas annotated tutorials. Several projects have training tasks that could be added to TeSS, already partially automated.</td></tr><tr><td><strong>Communities</strong></td><td></td></tr><tr><td>3D-bioinfo & Intrinsically Disordered Proteins (IDP)</td><td>Structural information about molecular actions of toxic compounds, molecular initiating events in AOPs</td></tr><tr><td>Galaxy</td><td>Application Programming Interface (API) standards and ontological annotation of APIs</td></tr><tr><td>Marine Metagenomics</td><td>Ecotoxicology data reflects effects on populations of species</td></tr><tr><td>Plant Sciences</td><td>Ecotoxicology data reflects effects of toxicants on plants</td></tr><tr><td>Metabolomics</td><td>Toxicants Chemical identifiers, data standards, data repository, common resources</td></tr><tr><td>Proteomics</td><td>Data standards and repository for proteomics data</td></tr><tr><td>Microbial Biotechnology</td><td>Chemical transformations in biological systems of toxicants</td></tr><tr><td>Federated Human Data & Human Copy Number Variation Community</td><td>Federated search, phenotype and genotype data</td></tr><tr><td>Rare Diseases</td><td>Shared biological pathways and interaction effects between rare diseases and exposure of toxicants</td></tr></tbody></table>

* InChI implementation for small molecule data

* Spectral database functionality (open implementations)

The concrete steps forward proposed in this roadmap include:

1. Leverage from open solutions (models, ontologies, educational material, standards etc) developed by past and ongoing toxicology and ELIXIR projects

2. Connect more closely with the core ELIXIR resources (FAIR data, database interoperability, etc), strengthen and connect the inclusive communities that have evolved over the past few years (<u>OpenTox</u>, eNanoMapper, diXa, OpenRiskNet, NORMAN) and older communities like the Federation of European Toxicologists & European Societies of Toxicology (<u>EUROTOX</u>), the Society of Environmental Toxicology and Chemistry (<u>SETAC</u>) and <u>European Environmental Mutagenesis and Genomics Society</u> (EEMGS, formerly known as EEMS)

3. Develop open community standards to support common interest (ontologies, APIs, data formats, deposition databases and publication recommendations)
<table><caption>**Table 2.** Examples of existing and anticipated collaboration.</caption><thead><tr><td></td><td>Existing collaboration/Reuse</td><td>Anticipated collaboration</td></tr></thead><tbody><tr><td>Tools</td><td>Semantic annotation of services (e.g. bio.tools)</td><td>Alignment with BioContainers of toxicology workflow efforts (e.g. OpenRiskNet)</td></tr><tr><td>Data</td><td>diXa was co-developed by the CHEMBL-EBI team, and builds on ArrayExpress an ELIXIR Core Data Resources</td><td>Better adoption of these Resources</td></tr><tr><td>Compute</td><td></td><td>Better and more sustainable compute infrastructure reuse of core elements (ELIXIR AAI, modelling toolsets)</td></tr><tr><td>Interoperability</td><td>FAIR and RDM standards have already been adopted by various projects</td><td>Registries of toxicology tools need integration with FAIRsharing; There is a huge identifier mapping service need (also for ontology mapping and chemical (sub) structures)</td></tr><tr><td>Training</td><td>Bioschemas annotated tutorials</td><td>Several projects have training tasks that could be added to TeSS, already partially automated</td></tr></tbody></table>

Specifically, we will continue to grow the list of involved toxicology research groups, projects, and ELIXIR Node activities. This Community has already held a joint meeting to select the key priorities and use cases (see Tables 2 and 3), resulting in this positioning paper. The ELIXIR Toxicology Community will continue to expand and search for contributors with relevant expertise as the community and activities mature. By bootstrapping from Open Science approaches developed in aforementioned projects (e.g. Open PHACTS⁵³), the new Community will focus on mutual benefit, an open and inclusive community, solving practical community problems. The goal is not to design domain-specific approaches, but a pragmatic approach that provides FAIR and open tools from the start, allowing all toxicology and neighbouring communities to benefit from these harmonized solutions. The inclusive community will involve the existing sub-communities in pharmaceuticals, e.g. from eTOX, transQST,⁵⁴ and eTRANSAFE,¹⁶ cosmetic ingredients, e.g. from SEURAT-1, high and low-volume chemicals, e.g. from HBM4EU and soon from Horizon Europe Partnership for the Assessment of Risk from Chemicals (PARC),⁴⁷ or from different Cefic-LRI (Lang-Range Research Initiative) projects, and nanomaterials, via the NanoSafety Cluster, building on shared needs and community solutions and strongly aligned to other ELIXIR communities. Open licensing and interfaces (ontologies, standards, formats) will encourage new solutions and collaborations, which will be accessible to any organisation and every project within and outside Europe. This will allow close interoperability with toxicology communities outside Europe that also use open approaches, while at the same time allowing compatibility with closed approaches too. This dual model has been demonstrated successfully in recent projects. A prioritized roadmap is essential; the label “ELIXIR Community” would enable us to set priorities at a level above the individual projects. Existing components that will give this Community an initial boost, include, software (e.g. AMBIT with OpenTox API⁵⁵), databases (e.g. diXa, eNanoMapper, AMBIT-LRI, NORMAN-SLE, MassBank), ontologies (e.g. the eNanoMapper ontology,⁵⁶ AOP ontology⁵⁷), interoperability concepts (e.g. annotation of OpenAPIs, in collaboration with bio.tools, semantic structural searches with IDSM), teaching/education material (Bioschemas annotation of outreach activities, in collaboration with TeSS), and virtual infrastructures (e.g. OpenRiskNet Virtual Research Environment and the NORMAN Digital Sample Freezing Platform). However, each of these approaches would benefit from integration in the ELIXIR Platforms (see examples in Table 1) and with Core and National Resources. Various existing ELIXIR Communities need similar solutions, e.g. for chemical structure handling, toxicology needs proteomics and metabolomics, toxicology involves human data, and ecotoxicology has significant impact on crops and health.

The following projects have been adopting and integrating FAIR toxicology concepts, but need integration with ELIXIR Platforms and Communities: eTOX, NanoCommons (NanoSafety Cluster), EU-ToxRisk, OpenRiskNet, OpenTox Foundation, Open PHACTS Foundation, and the diXa platform. Many other projects have a specific scientific focus but also need integration and some will work on the FAIR concepts. A non-exhaustive list is ACEnano, SmartNanoTox, HeCaToS, NewGeneris, EnviroGenoMarkers, EXPOsOMICS, HELIX, ASAT,⁵⁸ PATROLS, and HEALS, as well as new projects e.g. new Horizon 2020 projects RISK-HUNT3R and HARMLESS and the new Horizon Europe project PARC. Companies and organisations will profit from this Community either as users or as providers of services on top of the infrastructure, including ECHA (FI), Edelweiss Connect (CH), IdeaConsult Ltd. (BG), Misvik Biology (FI), TNO (NL), Seven Past Nine (SI), and the Swedish Academic Consortium for Chemical Safety (SwACCS, SE). Industries showed a strong interest in toxicology, demonstrated by their activities: Cosmetics Europe was participant in the
<table><caption>**Table 3.** The Toxicology Community roadmap is roughly defined by three themes (steps). Each step comes with a 10-year aim, further detailed with possible work that could be done in ELIXIR activities.</caption><thead><tr><td>Roadmap step</td><td>10-year aim</td><td>Possible implementation study aim & general criteria</td></tr></thead><tbody><tr><td>Disseminate existing open solutions (data, database software, models, ontologies, standards, or otherwise) developed among receptive toxicology projects, allowing the advantages of these solutions to become visible to the whole toxicology community</td><td>1. Integrating data types across toxicological exposure, biological, Adverse Outcome Pathways, chemical prioritization, hazard assessment, and risk assessment. Data spanning the toxicological domains, properties, exposure, kinetics and dynamics, that support hazard and risk assessment. Approaches include QSAR, QSARDB,⁶⁵ in vitro kinetics, kinetic modelling (toolboxes and parameter estimation), AOPs and Key Event measuring method data results, supporting read-across.<br>2. Interoperable Software and Predictive Models<br>3. Ontology and Standards</td><td>(a) Better adoption of the ELIXIR core and national node resources.<br>(b) Share teaching material about data exchange between resources on TeSS.<br>(c) Disseminate the need of linking database content, e.g. with identifier mapping and solutions to match entries between databases<br>(a) Explore technical connections between existing platforms (e.g. OpenRiskNet) and the Compute Platform and make them more interoperable, working with ELIXIR Interoperability Platform.<br>(b) Wider adoption of the EDAM ontology⁶⁶ and OpenAPI<br>(c) Explore Common Workflow Language (CWL), port a risk assessment case study as CWL workflow<br>(a) Adoption of standards like InChi/InChiKey<br>(b) Bioschemas adoption by web databases, and listing in Bioschemas Live Deploys<br>(c) Semantic annotation of assays, cell lines, and Standard Operating Procedures<br>(d) Encourage ontology reuse with dissemination of entering ontology terms as free text with autocorrect, autocomplete and autolookup (e.g. Clinical Data Interchange Standards)</td></tr></tbody></table>
<table><caption>**Table 3. Continued**</caption><thead><tr><td>Roadmap step</td><td>10-year aim</td><td>Possible implementation study aim & general criteria</td></tr></thead><tbody><tr><td>Connect and stimulate cross-project collaborations by making all toxicology research output FAIR.</td><td>1. FAIRify existing community resources and solutions for findability and easier reuse<br>2. Increase FAIRness of relevant data</td><td>(a) Register all Toxicology resources in FAIRsharing<sup>11,10</sup> and/or the Registry of Research Data Repositories<sup>67</sup> to build an awareness and overview of ongoing activities and infrastructures<br>(b) Link up with non-toxicology communities, such as GO FAIR and CDISC<br>(c) Use LabLinks to link Toxicology resources to EuropePMC<br>(a) Register/connect chemicals between PubChem, CompTox, ChEMBL, ChEBI, MolMeDB, JPCheM, IUCLID, HBM4EU, etc and increase integration of toxicologically-relevant information in open resources<br>(b) Develop citation standard for these solutions<br>(c) Integrate kinetics databases and databases needed for kinetic modelling<br>(d) develop and deploy tool boxes that make data registration in repositories easy (e.g. analogous to OneDep in PDB)<br>(a) Identify how/where toxicologists are asking questions and what their practices are<br>(b) Define tags to be used cross-platform for toxicology and disseminate these among three Q/A platforms</td></tr><tr><td></td><td>3. Inventorize Question-and-Answer (Q/A) platforms and sub-communities (e.g. tags) on those platforms where people can learn about solutions<br>4. Develop journal editorial standards for minimal reporting standards for describing the chemical entities in deposition databases and compact identifiers in the main text</td><td>(a) Reach out to editors. Make an "easy to refer to" guideline available. Find enough journals to join/ support this and point to these guidelines.<br>(b) Define a simple format for reporting names and InChI (Keys) and/or SMILES. Consider the possible ontologies for study descriptions for other things often used in toxicology research and toxicity testing (like Salmonella Typhimurium strains, cell systems, LD50 tests)<br>(c) Advocate using compact identifiers (structured as database:dbID, e.g. uniprot: P1234) that are easy to use and human readable and that can be resolved by adding links to identifiers.org or n2t.net.</td></tr></tbody></table>
<table><caption>**Table 3. Continued**</caption><thead><tr><td>Roadmap step</td><td>10-year aim</td><td>Possible implementation study aim & general criteria</td></tr></thead><tbody><tr><td>Design and ideally develop missing open community standards to support common interest (Open educational resources, ontologies, APIs, data formats, etc) in advancing toxicology research.</td><td>1. Engage with existing (ELIXIR) solutions, like Bioschemas and BioTools, ELIXIR AAI, Galaxy including these from connected organisations like RDA, Global Alliance for Genomics and Health (GA4GH), European Open Science Cloud (EOSC), and identify and communicate missing features.<br> 2. Sharing of standard operating procedures (SOPs)<br> 3. Continued evaluation by adoption of existing ontologies for annotation of toxicology research output<br> 4. Communicate and where possible disseminate FAIR data entry and/or study capture with matching software and/or templates to bench toxicologists</td><td>(a) Continue semantic annotation of service APIs (e.g. at bio.tools) and discuss limitations with service and solution providing communities<br> (b) Semantic annotation of training materials, databases, etc with Bioschemas JSON-LD and discuss found limitations<br> (c) ELIXIR AAI rollout in Toxicology platforms (already on OpenRiskNet platform as an example to build from) and report on experiences<br> (a) Explore existing solutions to share SOPs (e.g. protocols.io) and discuss limitations<br> (a) Work with other communities on meta ontologies and mechanisms for (re) creating those from underlying ones and adding dedicated parts. With automated updates and feedback to integrate changes in the base ontologies, e.g. Experimental Factor Ontology and the food & nutrition (Ontology of Nutritional Studies<sup>68</sup>).<br> (a) Engage with ELIXIR Training and explore solutions to repurpose existing solutions for data capturing better known in the ELIXIR Toxicology Community (e.g. BioSamples, NanoSafety Cluster templates)<br> (b) Make sure we can capture study designs based on templates can be used for toxicology studies<br> (c) Adopt DataCite practices</td></tr></tbody></table>
SEURAT-1 cluster; chemical industries (Nanotechnology Industries Association) are participant of the NSC; chemical branch organisation (Cefic) funds LRI projects around toxicology; pharmaceutical industries funds toxicology research via IMI projects like eTOX, eTRANSAFE, and Open PHACTS. The Research Data Alliance (RDA) organized a workshop recently about integration of toxicogenomics resources,⁵⁹ and collaboration with international organizations has already been established with, for example, the CompTox Chemicals Dashboard team of the US EPA⁶⁰ and PubChem from the US National Institutes of Health.⁶¹

## Competing interests

None.

## Grant information

This work received funding from the European Union's Horizon 2020 research infrastructure programme via the OpenRiskNet project under grant agreement No. 731075. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 681002 (EUToxRisk). This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 814572. SN acknowledges BMBF funding under grant number 031L0107. This work was supported by OBERON (https://oberon-4eu.com), a project funded by the European Union's Horizon 2020 research and innovation program under the grant agreement No. 825712. This work was supported by the European Union, its Horizon 2020 research and innovation program HBM4EU, grant agreement No. 733032 (https://www.hbm4eu.eu). Supported by the European Union's Horizon 2020 programme under the Marie Skłodowska-Curie grant agreement No. 859891. Where authors are identified as personnel of the International Agency for Research on Cancer/World Health Organization, the authors alone are responsible for the views expressed in this article, and they do not necessarily represent the decisions, policy, or views of the International Agency for Research on Cancer/World Health Organization. This work was supported by the European Union, its Horizon 2020 research and innovation program HARMLESS, grant agreement No. 953183. This work was supported by the European Union, its Horizon 2020 research and innovation program Gov4Nano, grant agreement No. 814401. This work was supported by the Swedish Fund for Research Without Animal Experiments under grant number N2020-0005. This work was supported by the European Union, its Horizon 2020 research and innovation program NTS-EXPOSURE, Grant agreement ID: 896141. This work was supported by the European Union, its LIFE program LIFE-APEX, Grant agreement ID: LIFE17 ENV/SK/000355. This study was funded by the German Environment Agency within the PHION project (grant number 3718 674150). The Data Readiness Group is supported, in this ELIXIR Community, by the H2020 Precision Toxicology project (H2020-EU 965406). The Data Readiness Group is supported, in this ELIXIR Community, by the Wellcome ISA-InterMine project (208381/A/17/Z). The Data Readiness Group is supported, in this ELIXIR Community, by the Wellcome FAIRsharing project (212930/Z/18/Z). This work received funding from the European Union's Horizon 2020 research and innovation programme RiskGONE Project under grant agreement No. 814425. NR's research is funded by a Miguel Servet contract (CO19/00060) from Instituto de Salud Carlos III, cofinanced by the European Union. UM (Uni. of Tartu) is grateful for support to Ministry of Education and Research, Republic of Estonia through Estonian Research Council (grant number IUT34-14) and to European Union European Regional Development Fund through Foundation Archimedes (grant number TK143, Centre of Excellence in Molecular Cell Engineering). Development and Implementation of a Sustainable Modelling Platform for NanoInformatics. Linking LRI Ambit chemoinformatic system with the IUCLID substance database to support read-across of substance endpoint data and category formation. This work was supported by the French Ministry of Research and National Research Agency as part of the French MetaboHUB, the national metabolomics and fluxomics infrastructure (Grant ANR-INBS-0010). This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement GOLIATH No. 825489.

## Disclaimer

* Where authors are identified as personnel of the International Agency for Research on Cancer/World Health Organization, the authors alone are responsible for the views expressed in this article, and they do not necessarily represent the decisions, policy, or views of the International Agency for Research on Cancer/World Health Organization.

* The views expressed in this manuscript are solely those of the authors and do not represent the policies of the U.S. Environmental Protection Agency. Mention of trade names of commercial products should not be interpreted as an endorsement by the U.S. Environmental Protection Agency.

## Acknowledgements

We acknowledge the discussions with others in the toxicology community (see github.com/bigcaT-UM/ELIXIR-Tox) and ELIXIR for their support so far.
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# Open Peer Review

Current Peer Review Status: ? ✓

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## Version 1

### Reviewer Report 08 April 2022

https://doi.org/10.5256/f1000research.78265.r124031

© 2022 Eide M. This is an open access peer review report distributed under the terms of the [Creative Commons Attribution License](https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Marta Eide

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In this opinion article, the authors describe the establishment of a new ELIXIR Toxicology Community in order to enable the transition from traditional disease-specific observational models to target-specific predictive models. The article introduces the rapidly developing field of toxicology and the interoperability issues arising in combining chemical and biochemical analysis, biological data, and kinetic modelling. The authors argue for "*clear, standardized guidelines for data capture, approaches to integrate and connect across multiple datasets, clear data licensing for these data repositories, and tools that support accessing the data*". The ELIXIR Toxicology Community is suggested to 1) connect the different user communities (including industry, governmental agencies, NGOs, and more), 2) strongly contribute to link between, and harmonize the already existing relevant infrastructure projects, resources, and activities, and 3) provide useful tools, guidelines, and training.

Acknowledging the vast number of chemicals that are currently being produced, and the limited knowledge of the consequences of exposure to humans and the environment, this is a timely and important effort. From my impression, an ELIXIR Community is a good tool to drive and coordinate such an international initiative.

I find the article comprehensive and well-written, and their arguments well discussed. However, I have some points that I hope the authors will take into consideration when taking the initiative further:

1. It is early stated that "*in this ELIXIR Community, the focus will be primarily on the protection of human health*". I would argue that this is an unfavorable restriction for three reasons:

* It disregards the 'OneHealth approach' recognized by WHO, FAO, OIE, and UNEP, which is defined as "*an integrated, unifying approach that aims to sustainably balance and optimize the health of people, animals and ecosystem. It recognizes the health of humans, domestic and wild animals, plants, and the wider environment (including ecosystems) are closely linked and inter-dependent*" (One Health High-Level Expert Panel

<footnote n="1">¹ Department of Biological Sciences, University of Bergen, Bergen, Norway</footnote>

<footnote n="2">² Centre for Digital Life Norway, Bergen, Norway</footnote>
Annual Report 2021). EFSA, ECHA, EMA *et al*. are also organizing a conference on the topic in June 2022 (https://www.one2022.eu). Seeing that animals and ecosystems are closely linked to human health, for example through foods, their responses to and effects from toxicant exposures are also highly important to study and include in risk assessments.

* Live animals, as well as animal tissue, cells, and molecules, are often used as models for toxicological studies. As the toxicological defense systems are highly preserved through evolution, they can give a good indication of human outcomes. Thus, it is important to also ensure supporting infrastructure for integrating these as well.

* Ontologies, standards, and data resources (like omics repositories, data analysis tools, etc.) are often already overlapping.

2. Although I welcome different stakeholders being identified as “user communities”, I am concerned by the, from my understanding, lack of industry and governmental/administrative agencies in the author list of this article. I believe that if the aim of improving FAIR data integration for safety to enable ultimate risk assessments is to be met, it is eminent to include non-academic perspectives, experiences, and concerns into the initiative from early on. Experiences from the PARC project could for example be useful in how to approach this.

3. From my experience, the field of toxicology in general has limited experience with FAIR data management and is not familiar with the resources that are in place. I see that toxicologists' communication, dissemination, and training are mentioned in the proposed roadmap, but I am missing a more targeted approach to engaging with the communities. For example, such activities could include organizing toxicology-specific workshops, presenting at toxicology conferences, and targeted information through different channels. As the proposed ELIXIR Community seems to have a good overview of ongoing initiatives and infrastructures and a good anchoring in the scientific community, a mapping of their target audience and users in the field could be suggested as a starting point.

4. As mentioned in the paper, systems biology approaches are also getting implemented in toxicology, i.e. systems toxicology (described in Sturla *et al.*, 2014¹. From my point of view, I am missing mentioning of tools for this, such as the FAIRDOM SEEK platform that integrates ISA-structured metadata and workflows with JWS-based biological systems modelling. However, there might already be other solutions for this that I don't recognize in the paper

**References**

1. Sturla SJ, Boobis AR, FitzGerald RE, Hoeng J, et al.: Systems toxicology: from basic research to risk assessment. *Chem Res Toxicol.* 2014; **27** (3): 314-29 [PubMed Abstract] | [Publisher Full Text](https://pubmed.com/2014-314-29)

**Is the topic of the opinion article discussed accurately in the context of the current literature?**

Yes

**Are all factual statements correct and adequately supported by citations?**
Yes

**Are arguments sufficiently supported by evidence from the published literature?**

Yes

**Are the conclusions drawn balanced and justified on the basis of the presented arguments?**

Yes

**Competing Interests:** No competing interests were disclosed.

**Reviewer Expertise:** Environmental toxicology, endocrine disruption, bioinformatics, systems toxicology, marine toxicology

**I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.**

Reviewer Report 21 March 2022

https://doi.org/10.5256/f1000research.78265.r124032

© 2022 Southan C. This is an open access peer review report distributed under the terms of the [Creative Commons Attribution License](https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Christopher Southan

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This wide-ranging review circumscribes an important data integration task with a major cat-
herding dimension. Whilst also appearing herculean, this esteemed author collective fully
understands what they are letting themselves in for and I wish them the best for this endeavor. It
is, of course, early days, but I will make a few points (whether these might be addressed in a
revision and blending in what other reviewers may come up with I will leave to the authors)

1. Harvesting tox data from the extant and future literature seems to neither be specifically addressed nor proposed via direct interactions with the pharmaceutical companies generating most of it. Standardised data from their large historical internal sets only surfaces sparsely and heterogeneously public databases. Companies such as LahsaVtic, Instem, and ToxPlanet claim to have large databases compiled from the literature. Might ChEMBL come into the frame here if they could strategically increase their toxicology data extraction from the literature, both prospectively and retrospectively? (So far with only 24 assays)

2. My impression is there are simply too many resources mentioned for realistic overarching harmonisation. Could these be cut back to a smaller "active membership" prioritised by the amount of data they have and will continue to generate?

<footnote n="1">¹ Deanery of Biomedical Sciences, University of Edinburgh, Edinburgh, UK</footnote>

<footnote n="2">² Data Sciences, Medicines Discovery Catapult, Macclesfield, UK</footnote>
3. Quote "standardized guidelines for data capture, approaches to integrate and connect across multiple databases". As we know, this is going to be the really tough bit. It needs the major sources to share not only their data schema and metadata indexing but push for a level of convergence. It has to be said that ELIXIR does not have a good record on this. Unless I have missed it, none of the core data resources has made any significant changes in their individual (and often decades-old) data models to really enhance interoperability.

4. PubChem has 113,110 compounds from ~ 30 annotation sources (although most relatively small) indexed under "PubChem Compound TOC: Toxicological Information" and toxicology-related submitting sources cover over 0.5 million substances. In addition, the term "toxicology" matches 3,774 BioAssays covering 86,068 compounds. This makes PubChem a *de facto* toxicology integration hub. The ELIXIR effort should consolidate and expand this, including where an increase in toxicology curation by ChEMBL could feed into BioAssay and thus become interoperative with the 294,000 biological activity data points already in there.

**Is the topic of the opinion article discussed accurately in the context of the current literature?**

Yes

**Are all factual statements correct and adequately supported by citations?**

Yes

**Are arguments sufficiently supported by evidence from the published literature?**

Yes

**Are the conclusions drawn balanced and justified on the basis of the presented arguments?**

Yes

**Competing Interests:** No competing interests were disclosed.

**Reviewer Expertise:** Bioinformatics and cheminformatics (see LinkedIN)

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.
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