Volume 384S1, September 2023 ISSN 0378-4274 384S1 S1-S348 (2023) Abstracts of the 57th congress of the European Societies of Toxicology (EUROTOX 2023) TOXICOLOGY – MULTIDISCIPLINARY SCIENCE LEADING TO SAFER AND SUSTAINABLE LIFE Ljubljana, Slovenia, September 10–13, 2023
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Abstracts of the 57th Congress of the European Societies of Toxicology (EUROTOX 2023) TOXICOLOGY – MULTIDISCIPLINARY SCIENCE LEADING TO SAFER AND SUSTAINABLE LIFE Ljubljana, Slovenia, 10 –13 September 2023 Publication of this supplement is supported by EUROTOX. An International Journal for the Rapid Publication of Short Reports on all Aspects of Toxicology Especially Mechanisms of Toxicity Editor-in-Chief Angela Mally Associate Editors Timothy W. Grant, Scott Garrett and Emanuela Testai Amsterdam—Boston—London—New York—Oxford—Paris—Philadelphia—San Diego—St. Louis
Editor-in-Chief A. Mally, Julius-Maximilians-University Würzburg, Department of Toxicology, Versbacher Straße 9, 97078 Würzburg, Fax. +49 931 31 811940 Co-Editors T. W. Gant, Imperial College London Faculty of Medicine, SW7 2AZ, London, United Kingdom S. Garrett, University of North Dakota School of Medicine and Health Sciences, 501 N. Columbia Road Stop 9037, ND 58202, Grand Forks, North Dakota, United States of America E. Testai, National Institute of Health Laboratory of Comparative Toxicology and Ecotoxicology, Roma, Italy Emeritus Editors W. Dekant, Julius-Maximilians-University Würzburg, Department of Toxicology, Versbacher Straße 9, 97078 Würzburg, Germany J. P. Kehrer, University of Alberta Faculty of Pharmacy and Pharmaceutical Sciences, 8613 – 114th St., Edmonton, T6G 2N8, Alberta, Canada Editorial Board J. T. Ahokas, Victoria, Australia B. Akingbemi, Alabama, United States of America L. Aleksunes, New Jersey, United States of America M. van den Berg, Utrecht, Netherlands W. M Caudle, Georgia, United States of America V. Cuomo, Roma, Italy M. Lucia Zaidan Dagli, Sao Paulo, Brazil B. Delclos, Arkansas, United States of America M. P. Dent, Bedford, United Kingdom P. Diel, Koln, Germany D. R. Dietrich, Konstanz, Germany J. A. Doorn, Iowa, United States of America Z. Dvorak, Olomouc, Czechia A. O. S. El-Kadi, Alberta, Canada N. Filipov, Georgia, United States of America A.-M. Florea, Berlin, Germany R. Ge, Wenzhou, China K. O. Goyak, Texas, United States of America J. A. Harrill, North Carolina, United States of America P. Hewitt, Darmstadt, Germany H. Jaeschke, Kansas, United States of America N. Kramer, Wageningen, Netherlands C. Yanfei Li, California, United States of America B. Liu, Florida, United States of America D. Marko, Vienna, Austria N. Mei, Arkansas, United States of America B. van Ravenzwaay, Ludwigshafen, Germany S. Sahu, Maryland, United States of America Q. Shi, Arkansas, United States of America S. Somji, North Dakota, United States of America H. Stopper, Wurzburg, Germany E. G. Vilanova, Elche, Spain M. Adrian Williams, Maryland, United States of America F. Worek, Munich, Germany Processed at Thomson Digital, Gangtok (India) IV
Abstracts of the 57th Congress of the European Societies of Toxicology (EUROTOX 2023) TOXICOLOGY – MULTIDISCIPLINARY SCIENCE LEADING TO SAFER AND SUSTAINABLE LIFE Ljubljana, Slovenia, 10 –13 September 2023 Preface Keynote Lectures KL01 | Keynote Lecture (Gregor Majdič) KL02 | EUROTOX Lecture Award KL03 | EUROTOX - SOT Debate KL04 | SOT Merit Award Lecture KL05 | HESI CITE Lecture KL06 | Keynote Lecture (Tom Turk) Continuing Education Courses (CECs) CEC01 | A hands-on introduction to applied artificial intelligence in toxicology CEC02 | Characterizing, validating, and reporting physiologically-based kinetic models – hands on training on the new PBK model OECD guidance CEC03 | Building a NAM-based IATA for chemical risk assessment CEC04 | Risk perception and risk communication of chemical substances CEC05 | Particle and fiber toxicology CEC06 | Recent perspectives for the safe use of pesticides in agriculture Sessions S01 | Human biomonitoring – a view to the future based on current achievements S02 | Implementation of new approach methods into regulatory risk assessment using case studies S03 | Current and future perspectives on the extended one-generation reproductive toxicity study (EOGRTS) S04 | Safety aspects of cannabidiol (CBD) applications S05 | Consideration of the endogenous exposome in risk assessment S06 | Chemical emergencies – public health management and the role of poison centers S07 | Involvement of mitochondria in adverse drug reactions S08 | Skills for the early career toxicologist S09 | Current use of NAMS/alternatives in DART testing S10 | Pathology and adverse outcome pathways S11 | Contact allergen potency: the missing piece in the huge puzzle of alternative methods S12 | Finding synergies for 3Rs – toxicokinetics, physiologically- based kinetic (PBK) models and read-across S12A | Regulating inhaled copper particles: Time for an updated Occupational Exposure Limit? S13 | Acceptance and use of in vitro methods: a perspective from various chemical sectors S14 | NAM mechanistic information for the risk assessment of chemical mixtures S15 | Next generation risk assessment of food chemicals, environmental contaminants and pharmaceuticals using open-source modelling platforms: perspectives from regulatory agencies, academia and industry S16 | Organ-on-a-chip and the developing role in early drug development S17 | Critical organs and exposure windows for developmental immunotoxicity assessment S18 | Uncertainty in chemical risk assessment – identifying, evaluating, reducing S19 | Micro-and nano-plastics in our environment: presence and potential impact S20 | Are diseases and conditions related to hormone imbalance really increasing? S21 | Environmental chemical mixtures and cancer hallmarks – new developments and open questions S22 | Role of immunity and contribution of immunotoxicity in the identification of non-genotoxic carcinogens S23 | Towards quantitative adverse outcome pathway networks S24 | Toxicogenomics: breaking barriers for regulatory implementation S25 | Re-emerging concerns associated with Phytotoxins S26 | Translational Advanced Platforms S27 | Ontologies as translational tools in toxicology S28 | HOT TOPIC (Warfare agents: F. Carvalho, M. Wilks) S29 | Current issues concerning air pollution V
Short Orals Sessions OS01 | Short Orals Session 1 OS02 | Short Orals Session 2 OS03 | Short Orals Session 3 OS04 | Short Orals Session 4 Poster Presentations P01 | Adverse Outcome Pathways P02 | Biomarkers of adverse effects P03 | Genotoxicology, mutagenesis and carcinogenicity P04 | Chemical emergencies P05 | Clinical and forensic toxicology P06 | Computational toxicology P07 | Dermal and ocular toxicology P08 | Developmental and reproductive toxicology P09 | Endocrine disrupting chemicals P10 | Environmental epidemiology and toxicology P11 | Exposome P12 | Gastrointestinal tract toxicology & microbiome P13 | Immunotoxicity P14 | Inhalation and respiratory toxicology P15 | Integrated approaches for testing and assessment (IATA) P16 | In vitro methodologies & screening P17 | Micro and nano particle toxicology P18 | Mitochondrial toxicity P19 | Mixture toxicity P20 | Naturally occurring poisons (Toxins) P21 | Neurotoxicity P22 | New approach methodologies (NAMs) P23 | Occupational toxicology P24 | Regulatory toxicology P25 | Risk assessment & communication P26 | Target organ toxicity Late Breaking Abstracts Author Index Keyword Index Note: The names of the main authors are underlined. When a main author is not also presenting author, the name of the presenting author is marked with an asterix *. Abstracts that have been withdrawn for presentation at EUROTOX 2023 Congress are not included in this publication. VI
Abstracts of the 57th Congress of the European Societies of Toxicology (EUROTOX 2023) TOXICOLOGY – MULTIDISCIPLINARY SCIENCE LEADING TO SAFER AND SUSTAINABLE LIFE Ljubljana, Slovenia, 10 –13 September 2023 Scientific Programme Committee Thomas Weiser, Chair Heather Wallace, EUROTOX Executive Committee Member 2023 Scientific Programme Committee • Lucija Perharič EUROTOX 2023 Congress President • Jernej Kužner EUROTOX 2023 LOC Delegate Chairs of the EUROTOX Specialty Sections • Valentina Galbiati, Immunotoxicology & Chemical Allergy (ITCASS) • Angela Mally, Molecular Toxicology • Doris Marko, Carcinogenesis • Georges Kass, ERASS Risk Assessment • Mathieu Vinken, In Vitro and In Silico Toxicology Specialty Section (In2Tox SS) • Eva Bonefeld-Jørgensen, EUROTOX 2024 Congress Delegate Local Organising Committee Lucija Perharič (Chair), National Institute of Public Health, SI Katarina Černe, University of Ljubljana, SI Gorazd Drevenšek, University of Primorska, SI Anita Jemec Kokalj, University of Ljubljana, SI Jernej Kužner, KRKA, SI Maja Martinčič, National Institute of Public Health, SI Smilja Milošev Tusevljak, Sandoz, SI Lucija Peterlin Mašič, University of Ljubljana, SI Marija Sollner Dolenc, University of Ljubljana, SI Mirjam Stančič, University of Ljubljana Marjan Vračko, National Institute of Chemistry, SI Bojana Žegura, National Institute of Biology, SI VII
Abstracts of the 57th Congress of the European Societies of Toxicology (EUROTOX 2023) TOXICOLOGY – MULTIDISCIPLINARY SCIENCE LEADING TO SAFER AND SUSTAINABLE LIFE Ljubljana, Slovenia, 10 –13 September 2023 Reviewers The abstracts of poster presentations and short oral communications were peer-reviewed by the following reviewers: • Valentina Galbiati, Chair of the EUROTOX Immunotoxicology and Chemical Allergy Specialty Section (ITCASS) • Angela Mally, Chair of the EUROTOX Molecular Toxicology Specialty Section • Barbara Birk, Member of the EUROTOX In Vitro and In Silico Toxicology Specialty Section (In2Tox SS) • Gladys Ouedraogo, Member of the EUROTOX In Vitro and In Silico Toxicology Specialty Section (In2Tox SS) • Joana Miranda, Chair of the EUROTOX Communication Subcommittee • Greta Waissi, Member of the EUROTOX Communication Subcommittee • Johanna Zilliacus, Member of the EUROTOX Education Subcommittee • Jyrki Liesivuori, EUROTOX Individual Members Delegate • Nursen Basaran, Member of the EUROTOX Nomination Subcommittee • Emanuela Corsini, Member of the EUROTOX Nomination Subcommittee • Werner Brueller, Member of the EUROTOX Registration Subcommittee • Gianni Dal Negro, Member of the EUROTOX Registration Subcommittee • Sarah Gould, Member of the EUROTOX Registration Subcommittee • Lucija Perharič, Chair of the Local Organising Committee • Katarina Černe, Local Organising Committee • Gorazd Drevenšek, Local Organising Committee • Anita Jemec Kokalj, Local Organising Committee • Jernej Kužner, Local Organising Committee • Maja Martinčič, Local Organising Committee • Smilja Milošev Tusevljak, Local Organising Committee • Lucija Peterlin Mašič, Local Organising Committee • Marija Sollner Dolenc, Local Organising Committee • Marjan Vračko, Local Organising Committee • Bojana Žegura, Local Organising Committee Organising Societies • Thomas Weiser, Chair of the Scientific Programme Committee • Félix Carvalho, EUROTOX President • Manon Beekhuijzen, EUROTOX Executive Committee Member • Theo de Kok, EUROTOX Executive Committee Member • Marc Pallardy, EUROTOX Executive Committee Member • Mathieu Vinken, EUROTOX Executive Committee Member, Chair of the EUROTOX In Vitro and In Silico Toxicology Specialty Section (In2Tox SS) • Heather Wallace, EUROTOX Executive Committee Member Chair of the EUROTOX Nomination Committee • Martin Wilks, EUROTOX Executive Committee Member • Doris Marko, Chair of the EUROTOX Carcinogenesis Specialty Section • Jan Vondracek, Secretary General of the EUROTOX Carcinogenesis Specialty Section • Georges Kass, Chair of the EUROTOX Risk Assessment Specialty Section • Corrado Galli, Secretary General of the EUROTOX Risk Assessment Specialty Section VIII
Volume 384S1, September 2023 ISSN 0378-4274 384S1 S1-S348 (2023) Abstracts of the 57th congress of the European Societies of Toxicology (EUROTOX 2023) TOXICOLOGY – MULTIDISCIPLINARY SCIENCE LEADING TO SAFER AND SUSTAINABLE LIFE Ljubljana, Slovenia, September 10–13, 2023 journal homepage: www.elsevier.com/locate/toxlet Toxicology Letters Contents lists available at ScienceDirect Toxicology Letters 384S1 (2023) S1 0378-4274/ © 2023 Published by Elsevier B.V. Preface Dear Friends and Colleagues It is with immense pleasure that we welcome each one of you, as we convene for the 57th Congress of the European Toxicologists and European Societies of Toxicology, in the captivating city of Ljubljana, Slovenia, from 10 to 13 September 2023, under the resolute banner of “Toxicology - Multidisciplinary Science Leading to Safer and Sustainable Life.” Allow us to express our profound gratitude for the exceptional quality of the scientific submissions received for this congress, and for the diligent efforts of our distinguished scientific programme committee (SPC). The outstanding commitment of session chairs, speakers and SPC has crafted a vibrant and thought-provoking programme that delves into areas of paramount importance and contemporary relevance, including the groundbreaking applications of artificial intelligence in toxicology, the validation and implementation of new approach methodologies, and the intricate networks of quantitative adverse outcome pathways to name just a few. Our discussions will also encompass crucial topics such as risk perception, risk assessment, and risk communication, next-generation carcinogenicity assessments, the harrowing challenges posed by drug abuse, the pivotal significance of human bio- monitoring, and the compelling aspects of developmental immunotoxicity. Furthermore, we shall delve into the intricacies surrounding the toxicity of chemical mixtures and the exposome, and confront the pressing realities of warfare agents in today’s world. The Congress boasts a meticulously curated agenda, comprising 6 Continuing Education Courses (one with even two tracks), 30 Scientific Sessions, and 2 Keynote Lectures. The programme further highlights a diverse array of prize and award lectures, including the EUROTOX Lecture Award, the SOT Merit Award lecture, the HESI Lecture, and the riveting EUROTOX/SOT Debate, a testament to our unwavering pursuit of knowledge and excellence. Moreover, we eagerly anticipate 4 dynamic short oral communication sessions, and the continuous display of over 630 enlightening posters that shall immerse us in cutting-edge research. Furthermore, our gathering shall be enriched by 8 thought-provoking industry hosted events, complemented by a compelling trade exhibition, fostering an environment conducive to forging valuable collaborations and nurturing fruitful interactions. We would like to express our appreciation and admiration for all those who have tirelessly worked towards the success of EUROTOX, and specifically of the EUROTOX 2023 Congress. Special thanks are due to the immense efforts of the Local Organizing Committee team, as well as the dedication, expertise, and passion demonstrated by each member of our committees (Executive, Nomination, Education, Communication, Registration, Corporate), our Specialty Sections (Carcinogenesis, Immunotoxicology, ERASS, In2TOX, and Molecular Toxicology), our PCO – K.I.T. Group, our experienced, dedicated and efficient Secretariat Office, and last but not least, our individual members and European Societies of Toxicology. As we convene at this distinguished congress, we wholeheartedly believe that the interactions and dialogues that ensue will serve as a wellspring of enlightenment and inspiration, leading to remarkable advancements in the realm of toxicology and contributing significantly to foster the science and education of toxicology, and influence regulatory and policy frameworks to promote the safety of humans, animals and the environment, and protect global health. We humbly extend our sincere wishes for a truly exceptional and enriching experience throughout this congress. With utmost respect and warm regards, Thomas Weiser Lucija Perharič EUROTOX President-Elect EUROTOX 2023 and EUROTOX 2023 Chair of the Congress President Scientific Programme Committee (SPC) https://doi.org/10.1016/S0378-4274(23)00260-6
0378-4274/ © 2023 Published by Elsevier B.V. Toxicology Letters 384S1 (2023) S2–S3 KL02 | EUROTOX Lecture Award No abstract has been submitted. KL03 | EUROTOX – SOT Debate The exposome will drastically change the practice of toxicology Robert Barouki1, Robert Wright2 1 Université de Paris, France 2 Icahn School of Medicine at Mount Sinai, NY, US Each year, the EUROTOX congress includes a debate in which leading toxicologists from EUROTOX and SOT advocate opposing sides of an issue that has significant toxicological importance. The debate continues a tradition that originated in the early 1990s. This year, the debaters will address the proposition “Will the exposome drastically change the practice of toxicology?” The debaters will explain the concept of the exposome and discuss its opportunities and challenges for toxicity assessments. Specific questions to be addressed include: Is the exposome concept adequately mature to be applied in the assessment of human toxicities? Is our understanding of what factors contribute to the exposome sufficiently known? Is there a systematic way to measure or model the influence of environmental exposures? Are analytical and diagnostic techniques sufficiently advanced to reliably measure the exposome? Do we have the necessary mechanistic understanding to allow linking exposures with health outcomes? Are we ready to include “all life exposures” in our toxicology practice? Are we able to integrate the social exposome with our toxicology practice? In addition to inclusion as a Featured Session at this meeting, this debate took place already (with the debaters having taken the reverse positions) during the 2023 SOT Annual Meeting in Nashville, USA, March 19-23, 2023. https://doi.org/10.1016/S0378-4274(23)00263-1 KL01 | Keynote Lecture Intoxicating love Gregor Majdic University of Ljubljana, Ljubljana, Slovenia Love is our companion from the cradle to death. Mother love is the powerful emotion triggered at birth and ensures the care and thus the survival of the offspring. Motherly love is later replaced by love between partners, which can last a lifetime or be stopped and restarted again and again with new partners in the course of life. But what is love? Is it something incomprehensible? Is it a game of molecules/ neurotransmitters in our brain? Is it an intoxication? Neuroscience is interested, among other things, in what happens in our brain when we are in love. Although we are still far from fully understanding what goes on in our brains when we are in love, we are slowly deciphering the changes in our brains when we fall in love and when we stay in a lasting relationship. Monogamy is common in birds, where mothers and fathers care for offspring in more than 90% of all bird species. However, it is much less common in mammals, and only about 5% of mammals live in lasting monogamous relationship. We have learned a lot about what goes on in the brains of monogamous animals from voles, small furry animals, some species of which engage promiscuous mating patterns and some species mate for life. Studies of these animals have shown that two neurotransmitters, oxytocin and vasopressin, play a predominant role in the formation of lasting partnerships between male and female voles. During the first mating in monogamous prairie voles, oxytocin and vasopressin regulate dopamine activity in the reward system, which triggers a desire in partners to stay together for life. Several studies in humans have shown that oxytocin in particular, but also vasopressin to some extent, plays a role in human bonding and trust. In the human brain, serotonin levels also change when we are in love, although it is not yet clear exactly what role serotonin plays in love. Imaging studies have shown changes in activity in different parts of the brain, but again, we do not yet fully understand how all the changes in brain activity are related to feelings of love. We are slowly learning what happens in our brains when we fall in love, but we are still far from fully understanding our brains. However, even if we learn all we can about the cellular and molecular processes in our brains during love, love will remain a mysterious feeling, probably something unique to our conscious species. https://doi.org/10.1016/S0378-4274(23)00261-8 Keynote Lectures Volume 384S1, September 2023 ISSN 0378-4274 384S1 S1-S348 (2023) Abstracts of the 57th congress of the European Societies of Toxicology (EUROTOX 2023) TOXICOLOGY – MULTIDISCIPLINARY SCIENCE LEADING TO SAFER AND SUSTAINABLE LIFE Ljubljana, Slovenia, September 10–13, 2023 journal homepage: www.elsevier.com/locate/toxlet Toxicology Letters Contents lists available at ScienceDirect
S3 Toxicology Letters 384S1 (2023) S2–S3 KL06 | Keynote Lecture KL06-01 Toxins of dinoflagellates and diatoms T. Turk University of Ljublana, Department of Biology, Biotechnical Faculty, Ljublana, Slovenia Toxins which are produced by certain species of marine dinoflagellates and diatoms represent a considerable danger to public health. These toxins are associated to harmful algal blooms (HAB), which can occur in various parts of the world. Once restricted within certain endemic areas, nowadays they seem to be spreading due to the climate changes and eutrophication of many coastal areas around the world. Harmful algal blooms produce a variety of toxins that are mainly distributed through food chains and are toxic to marine mammals, birds and fish. Many of these toxins are also a serious threat to the public health and have negative economic impact. Most often, humans get intoxicated by ingestion of vector organisms like shellfish which by means of filtration accumulate toxins in their tissues. According to the predominant and specific symptoms four main types of poisoning caused by dinoflagellates (NSP, PSP; DSP and ciguatera) and one type caused by diatoms (ASP) are known. In humans neurotoxic, mostly sensory symptoms are the most prominent in NSP and ciguatera poisoning, paralysis of motoric muscles in PSP and diarrhea in DSP, while ASP is characterized by permanent loss of short-term memory. Main toxins involved in these intoxications are brevetoxins in NSP, ciguatoxins in ciguatera poisoning, saxitoxin in PSP and okadaic acid in DSP. Diatom born ASP is caused by domoic acid. The mechanism of toxicity caused by the mentioned toxins will be presented in the keynote lecture. https://doi.org/10.1016/S0378-4274(23)00266-7 KL04 | SOT Merit Award Lecture Mechanisms Matter: Deriving Causal Concepts to Informing Risk Assessment L. Lehman-McKeeman Bristol Myers Squibb, Princeton, USA Mechanisms explain how things work. Toxicology research, with its focus on identifying hazards and defining potential risks, is highly informed by mechanistic studies. Mechanistic research requires integrating molecular, biochemical, and cellular effects along with considerations of metabolism and fate of a toxicant. This lecture will highlight research that determined numerous mechanisms of toxicity for environmental chemicals and potential new drugs. Additionally, how evidence for causal relationships identifies key events required to apply a mechanistic paradigm or inform human risk assessment will be summarized. While focusing on successful outcomes of mechanistic research, the role of research that addressed “why not” instead of “why” also will be discussed as a critical component of proving or confirming causality, and the contribution of just plain serendipity to novel or unexpected findings will be shared. Finally, consideration for translational research to aid in elucidating mechanisms of toxicity will be discussed. Examples to be highlighted include [1] sex- and/or species-specific mechanisms of toxicity that are determined by novel metabolic pathways, novel gene expression, or unintended pharmacology; [2] mechanisms of drug toxicity that are directly related to intended pharmacologic activity that is conserved across species; and [3] how effects in humans inform mechanisms of toxicity observed in animal studies. https://doi.org/10.1016/S0378-4274(23)00264-3 KL05 | HESI CITE Lecture Translational knowledge in minipigs: a way forward to reduce the use of nonhuman primates in non-clinical safety studies S. van Cruchten University of Antwerp, Antwerp, Belgium The current shortage in industry supply of non-human primates (NHPs) and the pressure to reduce overall NHP use in non-clinical safety studies has forced pharmaceutical companies to consider alternative species and approaches in the development of their drug candidates, especially for new therapeutic modalities. Alternative species are not always considered due to a general bias that NHPs are the most predictive for the human response, but also due to practical reasons such as limited compound supply and familiarity with the model. However, when animal studies are required and the compound is active in an alternative species, this species should be used instead of the NHP. The (mini)pig is generally underrepresented and often even not considered as non-rodent species in nonclinical safety studies, not just for new therapeutic modalities, but also for small molecule drugs. This lecture will highlight the translational value of the minipig for safety testing of new therapeutic modalities. The main focus will be on therapeutic oligonucleotides and paediatric patients, but the potential value of the minipig for other types of drug modalities and other patient populations will also be addressed. Finally, knowledge gaps that require an interdisciplinary approach will be discussed. https://doi.org/10.1016/S0378-4274(23)00265-5
Toxicology Letters 384S1 (2023) S4–S18 Successfully and effeciently generating AI models, cannot be done without much data and using a programming language. In this workshop, we will provide the basics for using the Statistical Programming Language R to get you introduced to machine learning. Together with the RStudio IDE, the R language is a fully fledged platfom for doing data science. In this part of the course we will use RStudio together with R to learn how to preprocess data to make it suitable for machine learning. We will explore the different types of machine learning available to us and build an unsupervised and a supervised classification model. In order to illustrate how machine learning can be used to classify toxicity of compound, we will use examples from the toxicological field.In the first part of this workshop, we will explore the data, which will serve two goals: to get you introduced into the R syntax and to show you the potential and importance of spending time with your data to get to know it. Every well performed Exploratory Data Analysis will reveal flaws, inconsistencies, interesting patterns, and insight into the data. We will create some visualizations on the data to get you started on visualizing with the R-package {ggplot2}. In the second part of the workshop, we will introduce you a modelling framework called {tidymodels}, and which ties neatly into the tools introduced in the first part. Tidymodels is an extension of the {tidyverse} suite of R packages and extend this framework to machine learning. We will explore the different functionalities to build an extensible workflow for implementing different types of machine-learning algorithms, using the same {recipe}.In the final part of the workshop, we will look at how to generate a neural network in R, using {tensorflow}. The neural network is an extension of the machine learning toolbox and can be considered the current working horse of big data. There are many different topologies to choose from when building neural network. We will only show you some architectures but will provide information on where to go next when you want to learn more. Participants of this workshop are required to bring their own laptop. Please make sure you have sufficient rights to install software, or at least have access to a browser and working WIFI-connection. We will provide an online environment to use for computations and course work, during the course. All materials will be shared online in a public Github repository for self-study and future reference. https://doi.org/10.1016/S0378-4274(23)00268-0 CEC01-02 (B) A hands-on introduction to applied artificial intelligence in toxicology: Advanced Deep Learning for Toxicology P. Banerjee Charité Universitätsmedizin Berlin, Institute of Physiology, Berlin, Germany CEC01 | A hands-on introduction to applied artificial intelligence in toxicology CEC01-01 A hands-on introduction to applied artificial intelligence in toxicology T. Hartung Johns Hopkins University, Baltimore, USA AI, aka machine learning, has become one of the most disruptive technologies due to the synergy of growth in computational power, growth in available “big” data, and optimization of machine learning. This effects all areas of modern life, including toxicology. Information retrieval and data extraction are obvious examples. Digital pathology with image analysis and sharing impacts on toxicology. Big data in toxicology originate from increasingly curated legacy studies, the scientific literature becoming open and machine-readable, the grey literature of the internet (e.g., more than 900,000 safety data sheets), sensor technologies, high-throughput testing (such as ToxCast and Tox-21), and ~omics technologies. AI uniquely lends itself to evidence integration. The output of this is probabilities, which opens opportunities for AI-enabled probabilistic risk assessment. The lecture introduces some basic concepts of AI and uses examples from the EU ONTOX project as well as our read-across-based structure-activity relationships (RASAR) approach to illustrate advances, challenges, and opportunities. https://doi.org/10.1016/S0378-4274(23)00267-9 CEC01-02 (A) Machine learning with R M. A. Teunis, A. M. De Haan, M. Corradi University of Applied Sciences, Innovate Testing – Data Science Group, Utrecht, Netherlands The amount of data that is being collected within the Life Sciences is increasing by the minute. To make sense of such vast amounts of data we need to step away from using classical analysis tools and embrance Artificial Intellingence (AI). AI has long hold promises for contributing to solving scientific challenges. Recently, the release of large foundation natural language processing models has shown the potential of AI to uphold those promises. Continuing Education Courses (CECs) Volume 384S1, September 2023 ISSN 0378-4274 384S1 S1-S348 (2023) Abstracts of the 57th congress of the European Societies of Toxicology (EUROTOX 2023) TOXICOLOGY – MULTIDISCIPLINARY SCIENCE LEADING TO SAFER AND SUSTAINABLE LIFE Ljubljana, Slovenia, September 10–13, 2023 journal homepage: www.elsevier.com/locate/toxlet Toxicology Letters Contents lists available at ScienceDirect 0378-4274/ © 2023 Published by Elsevier B.V.
S5 Toxicology Letters 384S1 (2023) S4–S18 Modeling Methods: To train our models, we use millions of chemical properties integrated through a harmonization process into a single, performant dataset. Our models integrate probabilistic layers that learn to represent parameters in probability distributions, including conditional variational autoencoders, isometric layers, and preliminary results from graph traversal methods where nodes are chemicals, reactions, hazards, chemical-protein, chemical-gene, and other relationships. Conclusion: This approach has the potential to greatly improve the efficiency and cost-effectiveness of chemical hazard assessment, facilitating the safe and sustainable use of chemicals in society. The generated models and aggregated data are available for rapid distribution and reuse, and a tutorial is provided to demonstrate how these tools can be used in downstream applications and research. This contribution is submitted on behalf of the ONTOX project. https://doi.org/10.1016/S0378-4274(23)00270-9 CEC01-03 (B) An Introduction to Machine Learning in Python D.-A. Clevert Pfizer, Machine Learning Research, Berlin, Germany We invite toxicologists to join a comprehensive hands-on training on machine learning (ML) in Python. This training is designed to provide a practical and in-depth introduction to ML techniques and tools, specifically tailored for applications in the field of computational toxicology. The aim of this workshop is to equip participants with the necessary skills to effectively develop and apply ML models to toxicological data, thus enhancing predictive capabilities and improving decision-making processes in risk assessment. Throughout the workshop, participants will engage in an interactive coding session, using real-world toxicological datasets and Python’s popular libraries such as scikit-learn or PyTDC. The training will cover fundamental concepts of ML, including data preprocessing, feature engineering (molecular descriptors), model building (un/supervised methods), model selection and model evaluation. By the end of the workshop, participants will have a thorough understanding of ML algorithms and their applications in computational toxicology, enabling them to create own predictive models, assess their performance, and optimize them for use in their research or professional projects. https://doi.org/10.1016/S0378-4274(23)00271-0 CEC01-04 Toxicogenomics data and analysis workflows G. Callegaro, S. Kunnen, G. Burger, B. van de Water Leiden University, LACDR, Leiden, Netherlands The assessment of an increasing number of chemicals in a way that better protects human health, requires a paradigm shift in the safety assessment of chemicals. It should involve an interdisciplinary approach that integrates the different types of knowledge and data in a mechanism-based framework. Toxicogenomics represents the ideal platform to provide detailed insights into the mechanism of action of chemicals. Toxicogenomics is a well-established approach that has been embraced by both the scientific community and various industries, used within the agricultural, chemical, and pharmaceutical sectors, to better understand mechanisms of toxicity and human relevance. In particular in academia and in pre-clinical safety studies in the industry toxicogenomics has been applied both in vitro and in vivo. Technological innovations have moved Computational toxicity prediction models based on machine learning (ML) algorithms are mathematical models which allow learning from the data without explicit programming from a human expert. Prediction of toxicity levels of chemical compounds is a great challenge [1]. Deep learning or deep neural networks (DNNs) are a machine learning approach that has been gaining attention in the field of predictive science and has successfully been applied to analyze and interpret a large amount of data in the field of toxicology [2]. The practical handson session includes- concrete examples, exploring the machine learning landscape, particularly neural nets, using Scikit-Learn to track an example machine-learning project end-to-end, including training and scaling deep neural networks for predictive models in toxicology [3]. The hands-on training goal is to gain an intuitive understanding of the concepts and application of practical code examples with less emphasis on acquiring excessive machine learning theory or algorithms details. References [1] Banerjee Priyanka, Eckert Andreas, Schrey Anaa and Preissner Robert, ProTox-II – a webserver for the prediction of toxicity of chemicals, Nucleic Acids Research, Apr 2018 [2] Mayr Adreas, Klanbauer Gunter, Unterthiner Thomas, and Hochreiter Thomas, DeepTox: Toxicity Prediction using Deep Learning, Frontiers in Environmental Science, volume 3- 2015 [3] Géron Aurélien, 2019, Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, O’Reilly, 2nd Edition, O’Reilly Media, Inc. https://doi.org/10.1016/S0378-4274(23)00269-2 CEC01-03 (A) Probabilistic Hazard Models Trained On Harmonized Chemical Relationship Data T. Luechtefeld2,1 1 Johns Hopkins University, Environmental Health Engineering, Baltimore, USA; 2 ToxTrack, Bethesda, USA We present methods for creating probabilistic predictions of chemical hazard based on chemical structure, chemical – chemical, chemical – disease, and other biomedical chemical – entity relationships. Methods include similarity embeddings used for read-across and probabilistic deep learning methods. Our method utilizes a large and diverse dataset of chemical structures and property data harmonized from many public data stores and distributed on biobricks.ai, an open source data registry. Our approach improves the accuracy and precision of chemical hazard predictions, providing a valuable tool for regulatory agencies and industry stakeholders. We demonstrate the effectiveness of our method through extensive testing and comparison to existing methods, showing a significant improvement in prediction accuracy and applicability domain coverage, and demonstrate the capacity for probabilistic models to measure uncertainty. This approach has the potential to greatly improve the efficiency and cost-effectiveness of chemical hazard assessment, facilitating the safe and sustainable use of chemicals in society. Data Sourcing: Training data for the presented probabilistic hazard classifiers is derived from many public stores, including chembl, pubchem, tox21, toxvaldb, ICE, and others. These stores were extracted from public sources, transformed into a standard chemical – property – value triplet store, and loaded into biobricks.ai, a data registry which provides programmatic access to normalized tabular data. Once loaded on biobricks.ai these data assets were treated as “data dependencies” and integrated in a new data asset which harmonized and combined all data stores into a large repository of chemical property and chemical relationship data. The resulting data assets are the ChemHarmony biobrick and the Aspis4J relational graph database.
S6 Toxicology Letters 384S1 (2023) S4–S18 CEC02 | Characterizing, validating, and reporting physiologically-based kinetic models – hands on training on the new PBK model OECD guidance CEC02-01 An international effort to promote the regulatory use of PBK models based on non-animal data M. Sachana OECD, Environment Health and Safety Division, Environment Directorate, Paris, France Physiologically Based Kinetic (PBK) modelling has emerged as an essential tool in chemical risk assessment, particularly now that the regulatory community is exploring and practising the application of new approach methodologies (NAMs). NAMs have also proved to be valuable for calibrating model parameters of a PBK model and for validating its predictive capability, opening the possibility to put an end to the heavy reliance on in vivo data (i.e. blood/plasma or tissue concentrations) and allowing the estimation of internal dose metrics even for data-poor chemicals that lack toxicokinetic (TK) in vivo data. Building regulatory confidence in PBK models that use in vitro and in silico data for informing Absorption, Distribution, Metabolism and Excretion (ADME) processes, requires a framework that is developed through the engagement of an international community with expertise in the field. This framework was prepared by an expert group of the Organisation for Economic Cooperation and Development (OECD), and provides a systematic approach for characterising, evaluating and reporting PBK models based on NAM-derived data. This effort led to an OECD guidance document (GD), describing a workflow, including a structured template for reporting PBK models and several well-documented case studies, which was published in 2021. Since then, there is an effort to promote the regulatory use of PBK models based on NAMs and the uptake of the GD through webinars and training sessions. This presentation will give a brief introduction to the GD and highlight other resources that were developed, including recent experience through the implementation of the templates in the OECD Integrated Approaches for Testing and Assessment (IATA). https://doi.org/10.1016/S0378-4274(23)00274-6 CEC02-02 PBK modelling platforms and in silico methods for model parameterisation I. Gardner Certara UK Limited, Sheffield, UK In this presentation some aspects of the OECD Guidance on the characterisation, validation and reporting of Physiologically Based Kinetic (PBK) models for regulatory purposes will be discussed. In particular the presentation will focus on the use and limitations of current in silico methods to derive inputs for PBK models in cases where there is limited (or no) in vivo data available for model calibration/performance verification. The use of in silico methods (eg BCS, ECCS) to characterise likely ADME properties of a chemical and to predict permeability, tissue: plasma partition coefficients and intrinsic metabolic clearance and renal clearance will be discussed using relevant examples from the case studies included in the OECD PBK guidance. Some of the commonly used in silico models for PBK model input parameter predictions will be evaluated against the OECD principles for in silico model quality (having a defined output, an unambiguous algorithm, a domain of toxicogenomics from using arrays and full genome RNA sequencing to more cost efficient high throughput transcriptomics using targeted RNA sequencing. Several bioinformatics approaches have been designed to extract differential gene expression and determining the pathways that are affected. These allow the mapping of biological perturbations that are caused by chemical-biological interactions, for example to discriminate between different cellular responses that are representative for specific biological perturbations such as DNA damage, mitochondrial injury, cellular stress response activation as well as specific activation of molecular initiation events, such as direct targeting of nuclear hormone receptors. During this session you will learn how to process transcriptomics data to obtain differentially expressed genes and several bioinformatics approaches to derive mechanistic information from the data. First, you will analyze a targeted RNAsequencing dataset and perform in R: quality controls and filtering, count normalization and differential gene expression analysis with the DEseq2 package. Then you will test different interpretation tools to reduce data dimensionality and obtain a biological interpretation. First you will exploit current knowledge of biological pathways by applying gene set analysis (EnrichR and Gprofiler R packages). Then you will explore data-driven interpretation approaches, such as weighted gene co-expression network analysis (WGCNA) and related established tools (the TXG-MAPr). In conclusion, this session will provide you with an introduction to toxicogenomics data analysis and examples of how to process transcriptomics data in the context of toxicological experiments to gain mechanistic understanding both exploiting existing knowledge as well as with data-driven approaches. https://doi.org/10.1016/S0378-4274(23)00272-2 CEC01-05 Good coding practices, publishing your work and code-collaboration A. M. De Haan, M. Corradi, M. A. T. Teunis Utrecht University of Applied Sciences, Innovative testing in Life Sciences & Chemistry, Utrecht, Netherlands Reproducibility is a critical aspect of scientific research, perhaps even more so in the case of artificial intelligence. Without the ability to reproduce results, the reliability and validity of AI research can (and should) be called into question, hindering progress and development in the field. Thus, reproducibility and data lineage is important for the acceptance and advancement of new approach methodologies. The recent surge in the use of artificial intelligence in toxicology therefore requires us to reconsider our normal workflow. How do we make sure we keep our projects reproducible in this new context? How do we collaborate efficiently with the enormous amounts of data and code heavy projects involved? Studies have shown that a significant percentage of AI research papers are not reproducible due to factors such as incomplete documentation and unshared code. Within research consortia we feel the need to make a move towards transparency and reproducibility and be able to adequately share data and code with each other and with the scientific and regulatory world. The current workshop is aimed at both early career and senior researchers and will cover a hands-on demonstration on how to approach these challenges in your current projects. We will discuss project management, how to share code and version control. https://doi.org/10.1016/S0378-4274(23)00273-4
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