EU-ToxRisk Final Symposium
Case studies
EU-ToxRisk publications
EU-ToxRisk Final Symposium
DAY 1
Please note that the video has been divided into chapters to facilitate navigation between presentations.
- Welcome words from the EU-ToxRisk project coordinator – Bob van de Water (Leiden University) PDF ; VIDEO
- Opening remarks on the EU-ToxRisk project, an EC Horizon 2020 initiative – Christian Desaintes (EC DG Research & Innovation) PDF ; VIDEO
Part I : New technologies and approaches for toxicology
- How has EU-ToxRisk impacted on innovative science research outreach – Thomas Steger Hartmann (Bayer) PDF ; VIDEO
- iPSC-derived hepatocyte spheroids for liver disease and toxicity assessment – Catherine Verfaillie (University Leuven) PDF ; VIDEO
- Biology-inspired microphysiological systems: the asset of multi-organ co-cultures – Uwe Marx (TissUse) PDF ; VIDEO
- Interactions with the Tox21 program – Joshua Harrill (U.S. EPA) PDF ; VIDEO
- The case of a high-concern toxicity profile screening – Bob van de Water (Leiden University) PDF ; VIDEO
- Application of NAMs to detect multisite metabolism – Paul Jennings (VU University Amsterdam) PDF
- Application of an AOP approach in a RAx safety assessment: the case of mitochondrial complex I inhibitors – Marcel Leist (University of Konstanz) PDF ; VIDEO
- Which NAM testing scope is good enough for risk identification/characterization? – Sylvia Escher (ITEM Fraunhofer) VIDEO
Part II: Implementation of NAM-based approaches in risk assessment workflows
- How has EU-ToxRisk impacted on NAM implementation in industry? – Andrew White (Unilever) PDF ; VIDEO
- A case study combining read-across and NAM, the example of propyl-paraben in systemic toxicity, from A to Z – Gladys Ouedraogo (L’Oreal)
- Commercialization Platform: perspectives from partners – Barry Hardy (Edelweiss Connect) PDF ; VIDEO
- Podium discussion: an overview on the impact of the EU-ToxRisk strategy from different perspectives – I. Cotgreave, T. S-Hartmann, M. Sachana, G. Kass, C. Desaintes VIDEO
DAY 2
Please note that the video has been divided into chapters to facilitate navigation between presentations.
Part III: Driving regulatory acceptance of NAMs
- How will EU-ToxRisk impact on NAM regulatory acceptance? – Matthias Herzler (BfR) PDF ; VIDEO
- EU-ToxRisk RAx advisory Document – Hennicke Kamp (BASF) PDF ; VIDEO
- Interactions with the OECD IATA Case Study programme – Magdalini Sachana (OECD) PDF ; VIDEO
- EU-ToxRisk and EFSA: A common journey towards NGRA – George Kass (EFSA) PDF ; VIDEO
- NGRA of developmental neurotoxicity liabilities of neonicotinoid insecticides – Susanne H. Bennekou (Danish Technical University) PDF ; VIDEO
- Interactions with other projects/initiatives: the PARC initiative – Mirjam Luijten (RIVM) PDF ; VIDEO
- European Commission perspective on EU-ToxRisk – Maurice Whelan (JRC) PDF ; VIDEO
- Ab initio risk assessment – case studies using the EU-ToxRisk toolbox – Andrew White (Unilever)
Poster session I: the EU-ToxRisk Case Studies
Impact #1: Toxicological testing to better predict human risk PDF
Martijn Mone/Giorgia Pallocca
The EU-ToxRisk case study approach PDF
Sylvia Escher/Susanne H.Bennekou
Prediction of microvesicular liver steatosis – a RAx CS: the regulatory impact PDF
Sylvia Escher
Prediction of microvesicular liver steatosis – a RAx CS: the applied technology PDF
Sylvia Escher
RAx CS to predict developmental and reproductive toxicity: the regulatory impact PDF
Dinant Kroese
RAx CS to predict developmental and reproductive toxicity: the applied technology PDF
Dinant Kroese
Use of integrated approaches to assess neurotoxicity: the regulatory impact PDF
Bob van de Water
Use of integrated approaches to assess neurotoxicity: the applied technology PDF
Bob van de Water
High-concern toxicity profile screening: the regulatory impact PDF
Bob van de Water
High-concern toxicity profile screening: the applied technology PDF
Bob van de Water
NGRA approach for insecticides induced-DNT: the regulatory impact PDF
Susanne H. Bennekou
Approach for insecticides induced-DNT: the applied technology NGRA PDF
Susanne H. Bennekou
Case Study on multi-organ metabolism: the regulatory impact PDF
Paul Jennings
Case Study on multi-organ metabolism: the applied technology
Paul Jennings
Poster session II: from test system development to commercialization
Technology
An overview of the EU-ToxRisk technologies and sustainable derived datasets PDF
Johannes Schimming/Martijn Mone
Computational prediction tools used and developed in the project PDF
Manuel Pastor
PBPK methods used and established in the project PDF
Iain Gardner
High throughput transcriptomics methods established in the project PDF
Bob van de Water
High throughput cell reporter tools used and developed in the project PDF
Catherine Verfaillie
EU-ToxRisk test methods comparison in CSy PDF
Marcel Leist
Advanced test methods developed in the EU-ToxRisk project PDF
Wolfgang Moritz
From in vitro to human. Translational strategies in EU-ToxRisk PDF
Ian Cotgreave
EU-ToxRisk computational methods based on qAOP PDF
Frederic Bois
Databasing and data sustainability: the EU-ToxRisk approach for data reuse PDF
Ugis Sarkans
Read-Across Strategy
Impact #2: Improved toxicological knowledge to advance read-across procedures PDF
Hennicke Kamp/Dinant Kroese/Sylvia Escher
The EU-ToxRisk Read-Across Advisory Document PDF
Hennicke Kamp/Dinant Kroese/Sylvia Escher
Commercialization
Impact #3: Commercial exploitation of developed toxicological tests & services PDF
Bart van de Burg/Barry Hardy
The EU-ToxRisk Commercialization Partnership PDF
Barry Hardy
The EU-ToxRisk Syngenta Case Study PDF
Rabea Graepel/Damiano
Dermal Exposure to Propylparaben: joint RAx case study with Cosmetics Europe PDF
Gladys Ouedraogo
Poster session : Regulatory Impact
Impact #4: Advancement of international co-operation in toxicology PDF
Giorgia Pallocca/Martijn Mone
Communication strategy to harmonize research and regulatory needs PDF
Giorgia Pallocca/Martijn Mone
The ToxTemp document PDF
Marcel Leist
EU-ToxRisk’s sustainability plan PDF
Bob van de Water
Impact #5: Reduced use of laboratory animals in safety testing PDF
Andy White/Tom Cull/Giorgia Pallocca
The EU-ToxRisk dissemination activities…in figures PDF
Giorgia Pallocca
Case studies
Case Studies of the EU-ToxRisk project
Prediction of microvesicular liver steatosis – a read-across case study with short branched carboxylic acids
Keywords
REACH, read-across, RDT, systemic toxicity, NAM, uncertainty, mode of action
Objective
In-vivo evidence indicates that short branched carboxylic acids –such as the drug valproic acid (VPA)– induce microvesicular liver steatosis in animals and humans. Would an analogue compound induce the same adverse outcome? To investigate this, we investigated a category of branched carboxylic acids by characterizing their toxicology profile with an in-vitro test battery. This study aimed to explore how far biological data from NAMs can be used in a read-across scenario to prove a shared mode of action and similar toxicokinetics.
Testing Strategy
Based on available in-vivo data of three structurally related analogues, the target compound 2-ethylbutyric acid (2-EBA) was assumed to be a liver toxicant with special concern for hepatic steatosis.
Toxicokinetics and toxicodynamics properties of 2-EBA were analysed and compared to a category of structurally highly similar carboxylic acids that vary only with regard to their aliphatic side chain length.
To characterize the toxicodynamics, published signalling pathways/AOPs leading to steatosis were compiled from literature and described in an AOP network. Two high-throughput reporter gene assays (CALUX and stress pathway responses in HepG2) were used to measure some of the described molecular initiating events (MIEs). Furthermore, three liver models were used to measure lipid accumulation as a direct in-vitro surrogate for in-vivo steatosis. It was shown that the number of activated MIEs and the induction of lipid accumulation increased with the side chain length of the tested carboxylic acids, whereas short-chain analogues like 2-EBA remained inactive up to the highest tested dose in vitro. The low activity of short-chain analogues was in good agreement with known in-vivo animal data.
To characterize the toxicokinetics, a PBPK model was developed and parameterized with in-vitro ADME data. Bioavailable concentrations were predicted and QIVIVE extrapolation was performed using PBPK-based reverse dosimetry.
Overall, the NAM data proved the initial read-across hypothesis to be valid by showing a consistent trend concerning toxicokinetics and toxicodynamics within grouped compounds.
Publications
van Vugt-Lussenburg et al. 2018 [link]; Leist et al. 2017 [link]; Tolosa et al. 2017 [link]; Fisher et al. 2018 [link]; Gadaleta et al. 2018 [link]; Wink et al. 2018 [link]; Niemeijer et al. 2018 [link]; Escher et al. 2022 [link]; Escher et al. 2019 [link]; Rovida et al. 2021 [link]
OECD IATA report
Report [link]; Annex II [link]; Annex III [link]
Contributors
ITEM, UL, UM, RISE, INERIS, BDS, TNO, DC, IRFMN, SYMCYP, VUA, UOF, UNIVIE, HULAFE, UCPH, CRX, IS, UHEI, L’OREAL, LHASA.
Prediction of developmental and reproductive toxicity (DART): a read-across case study with short branched carboxylic acids
Keywords
REACH, read-across, DART
Objective
2-Methylhexanoic acid (MHA) is mostly used as a food additive. Developmental and reproductive toxicity (DART) data for MHA were taken to be lacking. The aim was to find structural analogues for which DART data is available and to attempt to show that a NAM-based read-across would rightly predict the DART profile of MHA.
Testing Strategy
MHA and its selected chemical analogues were tested in a battery of in-vitro tests relevant to developmental toxicity, including the zebrafish embryotoxicity test (ZET), the mouse embryonic stem cell test (mEST), an iPSC-based neurodevelopmental model (UKN1), and a series of CALUX reporter assays. Also, toxicokinetic models were developed and applied to calculate effective cellular concentrations and associated in-vivo exposure doses.
The applied NAM-based read-across was used to predict the in-vivo developmental toxicity of MHA from the developmental toxicity data of selected source chemicals. This data would also allow us to further explore the relationship between structure and developmental toxicity within this series of aliphatic carboxylic acids. We also investigated the potential to inhibit histone deacetylase in these test models, as this enzyme is postulated to be the molecular target initiating neural tube defects, an observed developmental toxicity for some of these analogues. NAM results showed that VPA, PHA, EHA, and 4-ene-VPA were correctly predicted as in-vivo developmental toxicants, and EBA and DMPA as non-developmental toxicants. The results indicate that MHA, which is a non-developmental toxicant, cannot be classified as fully negative based on this NAM-based read-across.
Publications
Shinde et al. 2016 [link]; Waldman et al. 2016 [link]; van Vugt-Lussenburg et al. 2018 [link]; Fisher et al. 2017 [link]; Simeon et al. 2020 [link]; Escher et al. 2019 [link]; Brotzmann et al. 2021 [link]; Koch et al. 2021 [link]; Escher et al. 2019 [link]; Rovida et al. 2021 [link]
OECD IATA report
Report [link]; Annex II [link]; Annex III [link]
Contributors
TNO, UKN, UM, INERIS, BDS, IFADO, SIMCYP, LUMC, ROCHE, UHEI, NC3Rs, UNIVIE, RISE.
Peroxisome proliferation / Organic anion transporter interference
Keywords
REACH, read-across, RDT, systemic toxicity, NAM, metabolomics
Objective
The phenoxy acetic/propionic acid herbicides form a group of structurally similar herbicides are known to induce similar systemic toxicity in rat studies. The main toxicological effects observed are liver toxicity due to peroxisome proliferation as well as kidney toxicity associated with oxidative stress. Since the liver effects are mediated through activation of peroxisome proliferation, other non-herbicidal peroxisome proliferators – such as phthalates or pharmaceutical peroxisome proliferators– were tested to evaluate the NAMs in terms of general detection of peroxisome proliferation.
Testing Strategy
Data from CALUX assays, HepG2 metabolomics, and stress responses showed that the biological effects observed can be linked to the toxicological mode of action in the liver. The metabolite profile indicated changes in lipid metabolism as had been seen for peroxisome proliferators in vivo. The data for the herbicides were well in line with published in vivo findings (van Ravenzwaay et al., 2016) and demonstrated that the in vitro data might be used to substantiate a read-across based on in vitro methodologies. PBPK modelling for the compounds and test substances will be performed.
Publications
Van Ravenzwaay et al. 2016 [link]; Escher et al. [link]
Contributors
BASF, RISE, KI, BDS, ITEM, DC, MUI, VU.
Repeated dose toxicity (RDT)/ Developmental and reproductive toxicity (DART) – Mitochondrial toxicity. The case of the strobilurin fungicides.
Keywords
REACH, read-across, RDT, DART, NAM, AOP
Objective
A large group of pesticides used in the agrochemical sector targets mitochondria functionality. The synthetic strobilurin fungicides, derived from the naturally occurring strobilurin A and B, belong to this group. Strobilurin fungicidal mode of action is known. The chemical binds to the quinol oxidation site of cytochrome b of complex III (CIII) of the mitochondria. The degree of in vivo inhibition of the mitochondrial respiratory system depends on the respiratory activity and thereby tissues like the brain can be more susceptible if exposed. Evidence of potential neurotoxicity was also shown in in vitro studies. The objective of this case is to characterise potential CIII-mediated neurotoxicity of target compound azoxystrobin by NAM-enhanced read-across. The objective is to answer the question: ‘Can the absence of a neurotoxic potential of azoxystrobin-mediated inhibition of complex III of mitochondria be predicted by toxicodynamic and toxicokinetic NAM data?’
Testing Strategy
Source compounds selected in this case study are other strobilurin fungicides. Existing regulatory in vivo data was collected for the source and target compounds with a focus on ADME, neurotoxicity, as well as target organ toxicity data. Source compounds showed no signs of neurotoxicity, neither in neurotoxicity studies nor in other RDT studies. Overall, based on the generated data on kinetics and effect data, there is no evidence for a stronger neurotoxic potential of azoxystrobin mediated by a CIII inhibitory mode of action as compared to the source compounds. Since source compounds did not elicit neurotoxicity in vivo, we concluded that also the target compound azoxystrobin is not a neurotoxicant.
Publications
Wink et al. 2018 [link]; Hiemstra et al. 2019 [link]; Delp et al. 2018 [link]; Terron et al. 2019 [link]; van der Stel W et al. 2020 [link]; Fisher et al. 2017 [link]; Delp et al. 2019 [link]; Hemmerich et al. 2020 [link]; Troger et al. 2020 [link]; Delp et al. 2019 [link]; Delp et al. 2018 [link]; Delp et al. 2021 [link]; Hemmerich et al. 2020 [link]; van der Stel et al. 2021 [link]; van der Stel et al. 2020 [link]; Troger et al. et al. 2020 [link]; Vrijenhoek et al. 2022 [link]; Escher et al. 2019 [link]; Rovida et al. 2021 [link]
OECD IATA report
Contributors
UL, UKN, BASF, Unilever, RISE, KI, BDS, ITEM, VU, UPF, UNIVIE, HULAFE, CRX, DTU, L’Oreal
Repeated dose toxicity (RDT)/ Developmental and reproductive toxicity (DART) – Mitochondrial toxicity. The case of mitochondrial complex I inhibitors: deguelin and rotenone.
Keywords
REACH, read-across, RDT, DART, NAM, AOP
Objective
There is an anticipated hazard for agrochemicals that inhibit complex I of the mitochondrial respiratory chain to cause toxicity to the nigrostriatal neurons leading to symptoms that reflect Parkinson's disease. This effect has been comprehensively described in an OECD-validated AOP (Terron et al. 2019). This case study aims to assess the application of an AOP approach in a read-across safety assessment of structurally related mitochondrial complex I inhibitors, deguelin, and rotenone.
Epidemiological studies indicate that exposure of workers to rotenone is statistically associated with an increased incidence of Parkinson's disease; moreover, rotenone is known to induce parkinsonian phenotypes in experimental animals. Therefore, rotenone was used as the source substance. Deguelin can induce parkinsonian-like phenotypes in rats. Whether deguelin has such a parkinsonian hazard liability in humans is currently unclear and therefore deguelin was the target substance for this case study.
Testing Strategy
Based on the AOP, structural modelling approaches were applied to define the binding of rotenone and deguelin to mitochondrial complex I, the molecular initiating event of the AOP. Then, previously established and routinely applied assays that reflect the various key events in this AOP were defined. Multiple human-based in vitro test systems to monitor mitochondrial effects of rotenone and deguelin were additionally integrated. To assess the effect on neuron toxicity, high-content imaging approaches to measure degeneration of neuronal neurites were applied. Finally, both biokinetic evaluation of cellular exposure to rotenone and deguelin, as well as PBPK modelling, were used to evaluate the relevance of observed effects in vitro towards a likely in vivo exposure situation. Both substances inhibit complex I activity and cause mitochondrial dysfunction. Similarly, rotenone is also more potent than deguelin in disrupting neurites.
The target compound deguelin displayed a similar mode-of-action as rotenone, but with minor potency. The case study showed how practical application of an AOP approach through the integration of specific technologies and test systems might find broader application in a read-across safety assessment of structurally related substances.
Publications
Wink et al. 2018 [link]; Hiemstra et al. 2019 [link]; Delp et al. 2018 [link]; Terron et al. 2019 [link]; van der Stel W et al. 2020 [link]; Fisher et al. 2017 [link]; Delp et al. 2019 [link]; Hemmerich et al. 2020 [link]; Troger et al. 2020 [link]; Delp et al. 2019 [link]; Delp et al. 2018 [link]; Delp et al. 2021 [link]; Hemmerich et al. 2020 [link]; van der Stel et al. 2021 [link]; van der Stel et al. 2020 [link]; Troger et al. et al. 2020 [link]; Vrijenhoek et al. 2022 [link]; Escher et al. 2019 [link]; Rovida et al. 2021 [link]
OECD IATA report
Contributors
UL, UKN, BASF, Unilever, RISE, KI, BDS, ITEM, VU, UPF, UNIVIE, HULAFE, CRX, DTU, L’Oreal
Liver toxicity
Keywords
RDT, liver toxicity, NAM
Objective
Drug-induced liver injury (DILI) cannot be accurately predicted by animal models. Also, currently available in vitro methods do not allow for the estimation of hepatotoxic doses or the determination of an acceptable daily intake (ADI). To overcome this limitation, an in vitro/in silico method was established that predicts the risk of human DILI concerning oral doses and blood concentrations.
Despite intensive research, it is currently not possible to reliably predict whether repeated exposure to a certain dose of a chemical leads to an increased risk of hepatotoxicity or can be considered harmless.
The main objectives of this case study are:
- To predict blood concentrations of chemicals that cause an increased risk of hepatotoxicity and to identify concentration ranges that can be considered harmless.
- To predict oral doses of chemicals that cause an increased risk of hepatotoxicity (reverse modelling).
Testing Strategy
The developed novel in vitro/in silico method can be used to estimate DILI risk if the maximal blood concentration of the test compound is known. Moreover, an ADI can be estimated even for compounds without information on blood concentrations.
To systematically optimize the in vitro system, two novel test performance metrics were introduced: the toxicity separation index (TSI), which quantifies how well a test differentiates between hepatotoxic and non-hepatotoxic compounds, and the toxicity estimation index (TEI), which measures how well hepatotoxic blood concentrations in vivo can be estimated.
In vitro test performance was optimized for a training set of compounds, based on TSI and TEI, to identify the most performing concentrations and incubation time. Additionally, metrics were moderately improved by adding gene expression to the test battery and evaluation of pharmacokinetic parameters were evaluated. With a support vector machine-based classifier, the cross-validated sensitivity, specificity, and accuracy for hepatotoxicity prediction were highly relevant, respectively 100, 88, and 93%. Currently, the novel in vitro/in silico method is validated in a set of >200 test compounds. A constantly ongoing activity in this project is the identification of key events of DILI that can be tested in vitro in order to integrate them into our in vitro test battery.
Publications
Albrecht et al. 2019 [link]; Gu et al. 2018 [link]; Leist et al. 2017 [link]; Sachinidis et al. 2019 [link]; Ghallab et al. 2018 [link]; Jansen et al. 2016 [link]; Kappenberg et al. 2021 [link]; Gupta et al. 2020 [link]; Kappenberg et al. [link]; Krebs et al. 2020 [link]; Hengstler et al. 2020 [link]; Fasbender et al. 2020 [link]; Ruoß et al. 2020 [link]; Campos et al. 2020 [link]; Ghallab et al. 2019 [link]
Contributors
IFADO, UL, UKN, UM, UNILEVER, RISE, KI, CE, TNO, ITEM, DC, SimCyp, EBI, UNIVIE, UCPH, TissUse, JHSPH, IS, L’Oreal.
Popcorn lung – a read-across case study on diketones class group
Keywords
Read-across, RDT, REACH, respiratory disease, NAM
Objective
The alpha-diketone diacetyl (2,3- butadiene) is known to induce the so-called “popcorn lung” condition. This disease was frequently observed among microwave popcorn manufacturing employees who inhaled the butter flavour vapour of diacetyl. This condition represents an obstructive pulmonary disease in which the airway epithelium is the initial target of injury. The disease is called bronchiolitis obliterans and is characterized by fibroproliferative airway lesions.
In this case study, the effects of alpha-diketone have been investigated together with two structurally similar groups (β and γ diketone) which seem to have a different mode of action based on available information.
This approach can show how far selected NAMs are also able to differentiate the α, β, and γ diketone specific toxicity in the selected in vitro test systems. The three groups of structurally related compounds are sufficiently data-rich to allow the exploration of NAMs to adequately perform chemical hazard identification and herewith replacing the regulatorily required animal study. EU-ToxRisk tools were applied to predict toxicokinetics properties of the target compounds (e.g. PBPK and metabolism). Furthermore, we explored to which extent chemical similarity can be enriched by biological data, e.g. derived from omics investigations or cellular readouts.
Testing Strategy
All case study compounds were evaluated in fluorescent cell stress reporter assay high-throughput screens. Alpha diketones are known to have a high electron affinity and can transfer electrons and, thus, can induce ROS and oxidative stress. Αlpha-diketones as well as the beta-diketone 2,4-pentanedione were shown to induce activation of oxidative stress and DNA damage response pathways. The air-liquid interface (ALI) exposure setup for diacetyl and analogues was preferred in further experiments since dose control is ensured by online measurements of volatile test atmosphere employing FT-IR spectroscopy. Cultures of primary airway epithelial cells (PBECs) as well as human precision cut lung slices (PCLuS) were set up for ALI exposures. Additionally, transcriptomics as well as cytokine data are currently being analysed. Kinetic studies with diacetyl aiming at the determination of diacetyl uptake and intracellular concentrations are ongoing.
Contributors
ITEM, UL, UKN, DC, SimCyp, LUMC, Mario Negri IRCCS
Parabens
Keywords
Cosmetics regulation, industry-sponsored case study, read-across, ab-initio
Objective
This case study aims at establishing a proof-of-concept approach for the use of NAM-enhanced read-across in a next-generation risk assessment context. Parabens are esters of para-hydroxybenzoic acid (pHBA) that are widely used as preservatives in diverse product sectors including agrochemical, pharmaceutical, food, and cosmetics. In this case study, the use of in silico information, in vitro toxicodynamic (toxicogenomics, endocrine activity) and toxicokinetic data were combined to support biological similarity among analogues and establish potency trends to inform the selection of the best source chemical from within a category. This approach, along with consideration of aggregate exposure, was here used in an example safety assessment of low-toxicity chemicals. The chemical category under consideration is short linear chain parabens.
Testing Strategy
The external dermal cosmetic exposure to four parabens of primary interest (methyl, ethyl, propyl, and butyl) was analysed. Deterministic external exposure values were used to predict human plasma systemic exposure to the compounds.
A comprehensive human in vitro dataset was obtained, which enabled PBPK modelling of systemic plasma concentrations of the parent compounds following dermal exposure in humans. This data comprised human skin penetration data; biotransformation data in skin, liver, enterocytes (Caco-2 cells), and plasma, which characterized major metabolites and intrinsic clearance rates; plus plasma protein binding. The parabens are readily hydrolysed to p-hydroxy benzoic acid in presence of metabolic activation. The human ADME parameters were used to develop PBPK-based multi-compartment models of human systemic plasma parabens concentrations following dermal external exposure to compounds.
Parabens were shown to lack specific target organ toxicity at very high doses in repeated dose toxicity studies. However, they are active in some uterotrophic assays and were assigned a conservative point of departure (PoD) by the Scientific Committee for Consumer Safety. Also, data have emerged in the literature that show parabens exhibit low activity in in vitro assays relevant for endocrine activity. These in vitro assays suggest that parabens (the parent compounds but not the main metabolite) possess very weak activity on some nuclear receptors involved in endocrine homeostasis, many orders of magnitude lower than natural estrogens/androgens. In this case study, NAMs have been applied to explore this oestrogenic activity as an approach to inform on biological similarity and relative potency of the category members. This relative potency is then used to adjust the conservative PoD derived from butylparaben to carry out a theoretical risk assessment for propylparaben based on read-across.
For the read-across risk assessment, a margin of safety was derived using internal concentrations: margin of internal exposure –MoiE- which is protective of human health.
In conclusion this case study demonstrated the value added by NAMs in identifying, characterizing analogues, in informing similarities/differences on toxicokinetic and toxicodynamic properties and in the calculation of the internal margin of safety.
Publications
Berggren et al. (2017) [link]
OECD IATA report
Report [link]
Contributors
L’OREAL, UL, P&G, BASF, Unilever, Clariant, INERIS, CE, BDS, TNO, ITEM, LHASA, University of Liverpool.
Multi-target organ toxicity
Keywords
REACH, RDT, LOEL
Objective
The majority of toxic chemicals cause their most sensitive toxicological effects in liver, kidney or the respiratory tract in studies with repeated exposure. Nevertheless, there are compounds that show other types of toxicity. However, even if unaffected at the lowest observed effect level (LOEL), there is a 95% probability that effects on liver or kidney are observed in vivo at the next higher dose. The objective of this case study is to gain knowledge on how toxicological data derived from neuro, lung, liver, or kidney in vitro models can be used to predict the LOEL of test compounds and whether an additional safety factor will be needed.
Testing Strategy
In this case study, compounds that show specific toxicity effects in target organs different from the EU-ToxRisk test method panel have been selected for testing. In this way, knowledge will be gained in how far we can use the results of neuro/lung/liver or kidney models to predict the LOEL of such compounds. This case study applies cross-system testing and a 3-tiered approach: hypothesis generation, test cellular assays, PBPK modeling. Finally, data will be analyzed and the next tests will be refined based on the information gained in the first phase.
Contributors
ITEM, UL, BDS, VU, LUMC, HULAFE, IRFM, CRX, SIMCYP.
High-concern toxicity profile screening
Keywords
RDT/DART ab initio
Objective
Currently, for an enormous proportion of REACH registrations, no safety information is available. This particularly applies to 'lower tonnage' chemicals. Here there is a need to prioritize chemicals based on the likelihood of safety issues. The main objective of the case study is to demonstrate the overall feasibility of high-throughput NAM hazard-based information to identify substances of high-toxicity concern.
Testing Strategy
The driving hypothesis is that only toxic substances will strongly impact cell biology. This would be reflected by the activation of specific transcriptional networks that will provide mechanistic mode-of-action information. We anticipate that high-throughput NAM approaches could provide this mechanistic insight and thereby allow to rank substances based on their mode-of-action.
To demonstrate the feasibility to prioritize chemicals for further safety assessment, a training set of high tonnage compounds, for which in vivo safety data is available, will be used. These compounds will all be tested in dose-response scenarios in high-throughput test systems to assess the impact on the cell biology, and include: in silico approaches (metabolism, QSAR, target prediction); high-throughput reporter assays; targeted transcriptomics in selected cell types. All compounds will be ranked and we will relate our findings to the available in vivo adversity and potency information.
Contributors
UL, UKN, BASF, Unilever, BDS, TNO, ITEM, EWC, IRFMN, LUMC, UPF, EMBL-EBI, UNIVIE, HULAFE, CRX, L’Oreal, LHASA, VU, RISE.
Next-generation risk assessment of developmental neurotoxicity liabilities of neonicotinoid insecticides
Keywords
DART, OECD DNT TG426, IATA
Objective
In 2013, the European Food Safety Authority (EFSA) published a scientific opinion raising concerns regarding the DNT potential based on newer mechanistic in vitro data and insufficient hazard characterization based on available in vivo DNT tests of two neonicotinoid pesticides, acetamiprid and imidacloprid. This action has resulted in a proposal for revision of the human reference values. The objective of the case study is the development of an IATA to support hazard identification/characterization of selected neonicotinoids and to validate the biological plausibility and sufficiency of data from available datasets.
Testing Strategy
Data on neonicotinoid compounds in a combination of NAMs have been contextualized in an IATA. The selected NAMs span from molecular receptor docking, gene expression, assays covering endpoints involved in key neurodevelopmental processes as well as zebrafish embryos, and PBPK modelling.
Many endpoints of the in vitro test battery were not affected by high concentrations (up to 100 µM) of neonicotinoids. However, the functional properties of neurons were affected by a subset of test compounds in similar directions as observed with the well-known DNT toxicant nicotine. The case study now focuses on a more detailed molecular characterization of the observed hazard and potency estimates. Results across the testing battery expand the knowledge of available in vivo data and can, therefore, contribute to a better risk assessment. This approach aligns with the OECD program on „OECD DNT guidance on the interpretation of in vitro DNT data that can be used in an IATA", a global effort to test up to 120 DNT compounds in an in vitro test battery, generation of a database, and generation of IATA cases supporting endorsed guidance.
Publications
Loser et al. 2021 [link]; Loser et al. 2021 [link]; Loser et al. 2021 [link]
Contributors
DTU, UKN INERIS, BIOT, SIMCYP, UHEI, VU, SU.
Multi-organ metabolism (MOM)
Keywords
REACH, RTD, hepatotoxicity, nephrotoxicity, metabolism, kinetics
Objective
Halogenated alkenes are a family of chemicals that have been widely used in various industrial applications, like pesticides, solvents, and dry cleaning, and pose a significant hazard to human health. Occupational investigations and animal studies have indeed demonstrated that halogenated alkenes – especially trichloroethylene (TCE), perchloroethylene (PER), and hexachlorobutadiene (HCBD) – can cause various types of toxicity, including hepatotoxicity and nephrotoxicity. Mechanistic in vivo and in vitro animal studies have demonstrated that the renal toxicity of these chemicals is not caused by the parent compounds but is a result of several enzymatic reactions (GST, GGT, dipeptidase, and β-lyase) at hepatic and renal levels. The resulting reactive metabolites will lead to oxidative stress and mitochondrial dysfunction, which are considered key events in renal proximal tubule toxicity.
The case study aims to develop a quantitative model for halogenated alkene metabolism, distribution and target organ toxicity for halogenated alkenes, focusing on TCE.
Testing Strategy
An integrative workflow that includes in vitro hepatic studies for biotransformation of parent compounds, monitorisation of renal metabolism of hepatic conjugates and toxicity testing in hepatic, renal, and neuro in vitro systems has been developed. NAMs have been integrated into the testing approach. An in vitro model was developed utilizing human liver preparations, human recombinant enzymes, synthetic chemistry, and the human renal cell proximal tubule cell line RPTEC/TERT1. Metabolism stages and eventual mitochondrial toxicity have been evaluated in this system. LC-MS based analytical methods were applied to monitor the kinetics of parent compounds and tested metabolites which will also provide data for the support of an improved physiologically based pharmacokinetic (PBPK) model for human in vivo TCE, PER, and HCBD exposures.
Publications
Zgheib et al. 2018 [link]; Limonciel et al. 2018 [link]; van der Stel et al. 2020 [link]; Aschauer et al. 2015 [link]; Capinha et al. 2021 [link]; Capinha et al. 2021 [link]
Contributors
VU, UL, UKN, BIOT, EwC, IRFMN, SIMCYP.
EU-ToxRisk publications
Publications of the EU-ToxRisk project
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Identifying multi-scale translational safety biomarkers using a network-based systems approach2023 | iScienceCallegaro GiuliaDOI: 10.1016/j.isci.2023.106094 RISK-HUNT3RPMID: 36895646
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Collaborative SAR Modeling and Prospective In Vitro Validation of Oxidative Stress Activation in Human HepG2 Cells2023 | Journal of Chemical Information and ModelingBéquignon Olivier J.M.DOI: 10.1021/acs.jcim.3c00220 RISK-HUNT3RPMID: 37616385
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Identification of the bacterial metabolite aerugine as potential trigger of human dopaminergic neurodegeneration2023 | Environment InternationalÜckert Anna-KatharinaDOI: 10.1016/j.envint.2023.108229 RISK-HUNT3RPMID: 37797477
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A quantitative AOP of mitochondrial toxicity based on data from three cell lines2022 | Toxicology in VitroTebby CleoDOI: 10.1016/j.tiv.2022.105345 RISK-HUNT3RPMID: 35278637
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A Novel UPLC-MS Metabolomic Analysis-Based Strategy to Monitor the Course and Extent of iPSC Differentiation to Hepatocytes2022 | Journal of Proteome ResearchMoreno-Torres MartaDOI: 10.1021/acs.jproteome.1c00779 RISK-HUNT3RPMID: 34982937
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Specific attenuation of purinergic signaling during bortezomib-induced peripheral neuropathy2022 | International Journal of Molecular SciencesHolzer Anna-KatharinaDOI: 10.1101/2022.02.17.479688 RISK-HUNT3RPMID: 35409095
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Zebrafish embryo neonicotinoid developmental neurotoxicity in the FET test and behavioral assays2022 | ALTEXvon Hellfeld RebeccaDOI: 10.14573/altex.2111021 RISK-HUNT3R
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Metabolically Improved Stem Cell Derived Hepatocyte-Like Cells Support HBV Life Cycle and Are a Promising Tool for HBV Studies and Antiviral Drug Screenings2022 | BiomedicinesTricot TineDOI: 10.3390/biomedicines10020268 RISK-HUNT3RPMID: 35203482
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Application of high-throughput transcriptomics for mechanism-based biological read-across of short-chain carboxylic acid analogues of valproic acid2022 | ALTEXVrijenhoek Nanette G.DOI: 10.14573/altex.2107261 RISK-HUNT3R
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HiPSC-Derived Hepatocyte-like Cells Can Be Used as a Model for Transcriptomics-Based Study of Chemical Toxicity2022 | ToxicsGhosh SreyaDOI: 10.3390/toxics10010001 RISK-HUNT3R
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Mapping the cellular response to electron transport chain inhibitors reveals selective signaling networks triggered by mitochondrial perturbation2022 | Archives of Toxicologyvan der Stel WandaDOI: 10.1007/s00204-021-03160-7 RISK-HUNT3R
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The hepatocyte export carrier inhibition assay improves the separation of hepatotoxic from non-hepatotoxic compounds2022 | Chemico-Biological InteractionsBrecklinghaus TimDOI: 10.1016/j.cbi.2021.109728 RISK-HUNT3RPMID: 34717914
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Integrate mechanistic evidence from new approach methodologies (NAMs) into a read-across assessment to characterise trends in shared mode of action2022 | Toxicology in VitroEscher Sylvia E.DOI: 10.1016/j.tiv.2021.105269 RISK-HUNT3RPMID: 34757180
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Specificity of time- and dose-dependent morphological endpoints in the fish embryo acute toxicity (FET) test for substances with diverse modes of action: the search for a “fingerprint”2022 | Environmental Science and Pollution Researchvon Hellfeld RebeccaDOI: 10.1007/s11356-021-16354-4 RISK-HUNT3R
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Mapping the cellular response to electron transport chain inhibitors reveals selective signaling networks triggered by mitochondrial perturbation2022 | Archives of Toxicologyvan der Stel WandaDOI: 10.1007/s00204-021-03160-7 RISK-HUNT3R
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Transcriptomic Cross-Species Analysis of Chronic Liver Disease Reveals Consistent Regulation Between Humans and Mice2022 | Hepatology CommunicationsHolland Christian H.DOI: 10.1002/hep4.1797 RISK-HUNT3R
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Towards an advanced testing strategy for genotoxicity using image-based 2D and 3D HepG2 DNA damage response fluorescent protein reporters2022 | Mutagenesis, Volume 37, Issue 2, April 2022, Pages 130–142ter Braak BasDOI: 10.1093/mutage/geab031 RISK-HUNT3R
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Combining In Vivo Data with In Silico Predictions for Modeling Hepatic Steatosis by Using Stratified Bagging and Conformal Prediction2021 | Chem. Res. ToxicolJain SankalpDOI: 10.1021/acs.chemrestox.0c00511 RISK-HUNT3R
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A quantitative in vivo assay for craniofacial developmental toxicity of histone deacetylases2021 | Toxicology LettersKoch BjornDOI: 10.1016/j.toxlet.2021.02.005 RISK-HUNT3R
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Evaluation of the global performance of eight in silico skin sensitization models using human data2021 | AltexGolden EmilyDOI: https://doi.org/10.14573/altex.1911261 RISK-HUNT3R
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Acute effects of the imidacloprid metabolite desnitro-imidacloprid on human nACh receptors relevant for neuronal signaling2021 | Archives of ToxicologyLoser DominikDOI: 10.1007/s00204-021-03168-z RISK-HUNT3R
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Neurotoxic effects in zebrafish embryos by valproic acid and nine of its analogues: the fish-mouse connection?2021 | Archives of ToxicologyBrotzmann KatharinaDOI: 10.1007/s00204-020-02928-7 RISK-HUNT3R
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Neurodevelopmental toxicity assessment of flame retardants using a human DNT in vitro testing battery2021 | Cell Biology and ToxicologyKlose JördisDOI: 10.1007/s10565-021-09603-2 RISK-HUNT3RPMID: 33969458
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PLoS Computational Biology2021 | PLoS Computational BiologyHanspers KristinaDOI: 10.1371/journal.pcbi.1009226 RISK-HUNT3R
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ELIXIR and Toxicology: a community in development2021 | F1000ResearchMartens MarvinDOI: 10.12688/f1000research.74502.1 RISK-HUNT3R
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A fully defined matrix to support a pluripotent stem cell derived multi-cell-liver steatohepatitis and fibrosis model2021 | BiomaterialsKumar ManojDOI: 10.1016/j.biomaterials.2021.121006 RISK-HUNT3R
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Fluorescent tagging of endogenous Heme oxygenase-1 in human induced pluripotent stem cells for high content imaging of oxidative stress in various differentiated lineages2021 | Archives of Toxicology volume 95, pages 3285–3302 (2021)Snijders Kirsten E.DOI: 10.1007/s00204-021-03127-8 RISK-HUNT3R
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Identifying novel transcript biomarkers for hepatocellular carcinoma (HCC) using RNA-Seq datasets and machine learning2021 | BMC Cancer 21, 962 (2021)Gupta RajinderDOI: https://doi.org/10.1186/s12885-021-08704-9 RISK-HUNT3R
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Factors that Influence the Quality of Metabolomics Data in in Vitro Cell Toxicity Studies: A Systematic Survey2021 | Research SquareMoreno-Torres MartaDOI: https://doi.org/10.21203/rs.3.rs-724307/v1 RISK-HUNT3R
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New approach methods (NAMs) supporting read-across: Two neurotoxicity AOP-based IATA case studies2021 | ALTEX - Alternatives to animal experimentation, 38(4), pp. 615–635van der Stel WandaDOI: https://doi.org/10.14573/altex.2103051 RISK-HUNT3R
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The in vitro assessment of the toxicity of volatile, oxidisable, redox-cycling compounds: phenols as an example2021 | Archives of Toxicology volume 95, pages2109–2121 (2021)Tolosa LaiaDOI: https://doi.org/10.1007/s00204-021-03036-w RISK-HUNT3R
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Flame: An Open Source Framework for Model Development, Hosting, and Usage in Production Environments2021 | Journal of CheminformaticsPastor ManuelDOI: https://doi.org/10.21203/rs.3.rs-107430/v1 RISK-HUNT3R
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Generation and characterization of iPSC-derived renal proximal tubule-like cells with extended stability2021 | Scientific Reports volume 11, Article number: 11575 (2021)Chandrasekaran VidyaDOI: https://doi.org/10.1038/s41598-021-89550-4 RISK-HUNT3R
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Neurodevelopmental toxicity assessment of flame retardants using a human DNT in vitro testing battery2021 | Cell Biology and Toxicology (2021)Klose JördisDOI: https://doi.org/10.1007/s10565-021-09603-2 RISK-HUNT3R
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Stimulation of de novo glutathione synthesis by nitrofurantoin for enhanced resilience of hepatocytes2021 | Cell Biology and Toxicology (2021)Wijaya Lukas S.DOI: https://doi.org/10.1007/s10565-021-09610-3 RISK-HUNT3R
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Directed differentiation of human induced pluripotent stem cells to hepatic stellate cells2021 | Nature ProtocolsVallverdu JuliaDOI: 10.1038/s41596-021-00509-1 RISK-HUNT3R
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Integration of temporal single cell cellular stress response activity with logic-ODE modeling reveals activation of ATF4-CHOP axis as a critical predictor of drug-induced liver injury2021 | Biochemical PharmacologyWijaya Lukas S.DOI: https://doi.org/10.1016/j.bcp.2021.114591 RISK-HUNT3R
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A human stem cell-derived test system for agents modifying neuronal N-methyl-D-aspartate-type glutamate receptor Ca2+-signalling2021 | Archives of Toxicology volume 95, pages 1703–1722 (2021)Klima StefanieDOI: https://doi.org/10.1007/s00204-021-03024-0 RISK-HUNT3R
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Physiologically Relevant Estrogen Receptor Alpha Pathway Reporters for Single-Cell Imaging-Based Carcinogenic Hazard Assessment of Estrogenic Compounds2021 | Toxicological Sciences, Volume 181, Issue 2, June 2021, Pages 187–198Duijndam BrittDOI: https://doi.org/10.1093/toxsci/kfab037 RISK-HUNT3R
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Systematic transcriptome-based comparison of cellular adaptive stress response activation networks in hepatic stem cell-derived progeny and primary human hepatocytes2021 | Toxicology in Vitroter Braak BasDOI: 10.1016/j.tiv.2021.105107 RISK-HUNT3R
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Functional alterations by a subgroup of neonicotinoid pesticides in human dopaminergic neurons2021 | Archives of Toxicology volume 95, pages 2081–2107 (2021)Loser DominikDOI: https://doi.org/10.1007/s00204-021-03031-1 RISK-HUNT3R
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Effective exposure of chemicals in in vitro cell systems: A review of chemical distribution models2021 | Toxicology in Vitro Volume 73, June 2021, 105133Proença SusanaDOI: https://doi.org/10.1016/j.tiv.2021.105133 RISK-HUNT3R
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Statement on advancing the assessment of chemical mixtures and their risks for human health and the environment2020 | Environment InternationalDrakvik Paula EDOI: 10.1016/j.envint.2019.105267 RISK-HUNT3R
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Automated integration of structural, biological and metabolic similarities to improve read-across2020 | AltexGadaleta DomenicoDOI: https://doi.org/10.14573/altex.2002281 RISK-HUNT3R
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Multiparametric assessment of mitochondrial respiratory inhibition in HepG2 and RPTEC/TERT1 cells using a panel of mitochondrial targeting agrochemicals2020 | Archives of Toxicologyvan der Stel WandaDOI: 10.1007/s00204-020-02792-5 RISK-HUNT3RPMID: 32607615
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Determination of benchmark concentrations and their statistical uncertainty for cytotoxicity test data and functional in vitro assays2020 | AltexKrebs AliceDOI: https://doi.org/10.14573/altex.1912021 RISK-HUNT3R
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Biology-inspired Microphysiological systems to advance patient benefit and animal welfare in drug development2020 | AltexMarx UweDOI: https://doi.org/10.14573/altex.2001241 RISK-HUNT3R
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Internationalization of read-across as a validated new approach method (NAM) for regulatory toxicology2020 | AltexRovida CostanzaDOI: 10.14573/altex.1912181 RISK-HUNT3RPMID: 32369604
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Harnessing the power of novel animal-free test methods for the development of COVID-19 drugs and vaccines2020 | Archives of ToxicologyBusquet FrancoisDOI: 10.1007/s00204-020-02787-2 RISK-HUNT3RPMID: 32447523
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The EU-ToxRisk method documentation, data processing and chemical testing pipeline for the regulatory use of new approach methods2020 | Archives of ToxicologyKrebs AliceDOI: 10.1007/s00204-020-02802-6 RISK-HUNT3RPMID: 32632539
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Human Induced Pluripotent Stem Cell-Derived 3D-Neurospheres are Suitable for Neurotoxicity Screening2020 | CellsKobolák JuliannaDOI: 10.3390/cells9051122 RISK-HUNT3RPMID: 32369990
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Design and evaluation of bi-functional iron chelators for protection of dopaminergic neurons from toxicants2020 | Archives of ToxicologyGutbier SimonDOI: 10.1007/s00204-020-02826-y RISK-HUNT3RPMID: 32607613
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Incorporation of stem cell-derived astrocytes into neuronal organoids to allow neuro-glial interactions in toxicological studies2020 | AltexBrüll MarkusDOI: https://doi.org/10.14573/altex.1911111 RISK-HUNT3RPMID: 32150624
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Development of a generic zebrafish embryo PBPK model and application to the developmental toxicity assessment of valproic acid analogs2020 | Reproductive ToxicologySiméon SégolèneDOI: 10.1016/j.reprotox.2020.02.010 Erratum in RISK-HUNT3RPMID: 32114065
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Using Machine Learning Methods and Structural Alerts for Prediction of Mitochondrial Toxicity2020 | Molecular InformaticsHemmerich JenniferDOI: 10.1002/minf.202000005 RISK-HUNT3RPMID: 32108997
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The exposome – a new approach for risk assessment2020 | AltexSillé Fenna C. M.DOI: 10.14573/altex.2001051 RISK-HUNT3RPMID: 31960937
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Setting the stage for next-generation risk assessment with non-animal approaches: the EU-ToxRisk project experience2020 | Archives of ToxicologyMoné Martijn J.DOI: 10.1007/s00204-020-02866-4 RISK-HUNT3RPMID: 32886186
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Inflammation-associated suppression of metabolic gene networks in acute and chronic liver disease2020 | Archives of ToxicologyCampos GiselaDOI: 10.1007/s00204-019-02630-3 RISK-HUNT3RPMID: 31919559
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ATF6 Is a Critical Determinant of CHOP Dynamics during the Unfolded Protein Response2020 | iScienceYang HuanDOI: 10.1016/j.isci.2020.100860 RISK-HUNT3RPMID: 32058971
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Adverse effects in the fish embryo acute toxicity (FET) test: a catalogue of unspecific morphological changes versus more specific effects in zebrafish (Danio rerio) embryos2020 | Environmental Sciences Europevon Hellfeld RebeccaDOI: 10.1186/s12302-020-00398-3 RISK-HUNT3R
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Road map for development of stem cell-based alternative test methods.2019 | Trends in Molecular Medicine, Volume 25, Issue 6, June 2019, Pages 470-481Sachinidis AgapiosDOI: 10.1016/j.molmed.2019.04.003 RISK-HUNT3R
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Structure learning of Bayesian networks involving cyclic structures2019 | HAL ArchivesWiecek WitoldDOI: 10.48550/arXiv.1906.04992 RISK-HUNT3R
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Integrating in silico models and read-across methods for predicting toxicity of chemicals: A step-wise strategy2019 | Environment InternationalBenfenati EmilioDOI: 10.1016/j.envint.2019.105060 RISK-HUNT3RPMID: 31377600
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Towards grouping concepts based on new approach methodologies in chemical hazard assessment: the read-across approach of the EU-ToxRisk project2019 | Archives of ToxicologyEscher Sylvia E.DOI: 10.1007/s00204-019-02591-7 RISK-HUNT3R
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Analysis of Time-Series Gene Expression Data to Explore Mechanisms of Chemical-Induced Hepatic Steatosis Toxicity2019 | Frontiers in GeneticsAguayo-Orozco AlejandroDOI: https://doi.org/10.3389/fgene.2018.00396 RISK-HUNT3R
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Optimizing drug discovery by investigative toxicology: Current and future trends2019 | ALTEX - Alternatives to animal experimentationBeilmann MarioDOI: 10.14573/altex.1808181 RISK-HUNT3R
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A systematic analysis of Nrf2 pathway activation dynamics during repeated xenobiotic exposure2019 | Archives of ToxicologyBischoff Luc J. M.DOI: https://doi.org/10.1007/s00204-018-2353-2 RISK-HUNT3R
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Current EU research activities on combined exposure to multiple chemicals2019 | Environment InternationalBopp Stephanie KDOI: 10.1016/j.envint.2018.07.037 RISK-HUNT3R
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Regulatory acceptance of read-across2019 | ALTEXChesnut MeganDOI: 10.14573/altex.1805081 RISK-HUNT3R
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Characterisation of the NRF2 transcriptional network and its response to chemical insult in primary human hepatocytes: implications for prediction of drug-induced liver injury2019 | Archives of ToxicologyCopple Ian M.DOI: 10.1007/s00204-018-2354-1 RISK-HUNT3R
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Computational Toxicology: Risk Assessment for Chemicals2019 | Computational Toxicology: Risk Assessment for ChemicalsEkins SeanDOI: 10.1002/9781119282594 RISK-HUNT3R
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Toxicogenomics directory of rat hepatotoxicants in vivo and in cultivated hepatocytes2019 | Archives of Toxicology volume 92, pages 3517–3533 (2018)Grinberg MariannaDOI: 10.1007/s00204-018-2352-3 RISK-HUNT3R
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QSAR Development for Plasma Protein Binding: Influence of the Ionization State2019 | Pharmaceutical ResearchToma CosimoDOI: 10.1007/s11095-018-2561-8 RISK-HUNT3R
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Application of three approaches for quantitative AOP development to renal toxicity2019 | Computational ToxicologyZgheib EliasDOI: 10.1016/j.comtox.2019.02.001 RISK-HUNT3R
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Prediction of human drug-induced liver injury (DILI) in relation to oral doses and blood concentrations2019 | Archives of ToxicologyAlbrecht WiebkeDOI: 10.1007/s00204-019-02492-9 RISK-HUNT3R
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Development of a neurotoxicity assay that is tuned to detect mitochondrial toxicants2019 | Archives of ToxicologyDelp JohannesDOI: 10.1007/s00204-019-02473-y RISK-HUNT3R
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Paradigm shift in safety assessment using new approach methods: The EU-ToxRisk strategy2019 | Current Opinion in Toxicology Volume 15, June 2019, Pages 33-39Graepel RabeaDOI: 10.1016/j.cotox.2019.03.005 RISK-HUNT3R
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Chemical concentrations in cell culture compartments (C5) – concentration definitions2019 | ALTEXKisitu JaffarDOI: 10.14573/altex.1901031 RISK-HUNT3R
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System Microscopy of Stress Response Pathways in Cholestasis Research2019 | Methods in Molecular BiologySchimming Johannes P.DOI: 10.1007/978-1-4939-9420-5_13 RISK-HUNT3R
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SUIKER: Quantification of antigens in cell organelles, neurites and cellular sub-structures by imaging2019 | ALTEXKarreman ChristiaanDOI: 10.14573/altex.1906251 RISK-HUNT3R
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Finding synergies for the 3Rs – Repeated Dose Toxicity testing: Report from an EPAA Partners' Forum2019 | Regulatory Toxicology and Pharmacology Volume 108, November 2019, 104470Laroche CharlesDOI: 10.1016/j.yrtph.2019.104470 RISK-HUNT3R
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Autologous induced pluripotent stem cell-derived four-organ-chip2019 | FUTURE SCIENCERamme Anja PatriciaDOI: 10.2144/fsoa-2019-0065 RISK-HUNT3R
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Predicting toxicity of chemicals: software beats animal testing2019 | EFSA JournalHartung ThomasDOI: 10.2903/j.efsa.2019.e170710 RISK-HUNT3R
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High-throughput confocal imaging of differentiated 3D liver-like spheroid cellular stress response reporters for identification of drug-induced liver injury liability2019 | Archives of Toxicology volume 93, pages 2895–2911 (2019)Hiemstra StevenDOI: 10.1007/s00204-019-02552-0 RISK-HUNT3R
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Template for the description of cell-based toxicological test methods to allow evaluation and regulatory use of the data2019 | ALTEXKrebs AliceDOI: 10.14573/altex.1909271 RISK-HUNT3R
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Development of a neural rosette formation assay (RoFA) to identify neurodevelopmental toxicants and to characterize their transcriptome disturbances2019 | Archives of ToxicologyDreser NadineDOI: 10.1007/s00204-019-02612-5 RISK-HUNT3R
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VIVD: Virtual in vitro distribution model for the mechanistic prediction of intracellular concentrations of chemicals in in vitro toxicity assays2019 | Toxicology in VitroFisher CiaránDOI: 10.1016/j.tiv.2018.12.017 RISK-HUNT3R
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Time and space-resolved quantification of plasma membrane sialylation for measurements of cell function and neurotoxicity2019 | Archives of ToxicologyKranaster PetraDOI: 10.1007/s00204-019-02642-z RISK-HUNT3RPMID: 31828357
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The use of systems biology in chemical risk assessment2019 | Current Opinion in ToxicologyAguayo-Orozco AlejandroDOI: 10.1016/j.cotox.2019.03.003 RISK-HUNT3R
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sAOP: linking chemical stressors to adverse outcomes pathway networks2019 | BioinformaticsAguayo-Orozco AlejandroDOI: 10.1093/bioinformatics/btz570 RISK-HUNT3RPMID: 31329252
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A read-across study on diketones.2019 | The Toxicologist Supplement to Toxicological SciencesKühne BrittaDOI: RISK-HUNT3R
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An adverse outcome pathway for parkinsonian motor deficits associated with mitochondrial complex I inhibition2018 | Archives of ToxicologyTerron AndreaDOI: 10.1007/s00204-017-2133-4 RISK-HUNT3RPMID: 29209747
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Stem Cell Transcriptome Responses and Corresponding Biomarkers That Indicate the Transition from Adaptive Responses to Cytotoxicity2018 | Chemical Research in ToxicologyWaldmann TanjaDOI: 10.1021/acs.chemrestox.6b00259 RISK-HUNT3RPMID: 28001369
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A structure-activity relationship linking non-planar PCBs to functional deficits of neural crest cells: new roles for connexins2018 | Archives of ToxicologyNyffeler JohannaDOI: 10.1007/s00204-017-2125-4 RISK-HUNT3RPMID: 29164306
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Stage-specific metabolic features of differentiating neurons: Implications for toxicant sensitivity2018 | Toxicology and Applied PharmacologyDelp JohannesDOI: 10.1016/j.taap.2017.12.013 RISK-HUNT3RPMID: 29278688
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Big-data and machine learning to revamp computational toxicology and its use in risk assessment2018 | Toxicology ResearchLuechtefeld ThomasDOI: 10.1039/c8tx00051d RISK-HUNT3RPMID: 30310652
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A snapshot on the progress of in vitro toxicology for safety assessment2018 | Toxicology in VitroJennings PaulDOI: 10.1016/j.tiv.2017.10.024 RISK-HUNT3RPMID: 29195642
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Towards optimisation of induced pluripotent cell culture: Extracellular acidification results in growth arrest of iPSC prior to nutrient exhaustion2018 | Toxicology in VitroWilmes AnjaDOI: 10.1016/j.tiv.2017.07.023 RISK-HUNT3RPMID: 28821352
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A high-throughput approach to identify specific neurotoxicants/ developmental toxicants in human neuronal cell function assays2018 | AltexDelp JohannesDOI: 10.14573/altex.1712182 RISK-HUNT3RPMID: 29423527
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Normalization of Data for Viability and Relative Cell Function Curves2018 | AltexKrebs AliceDOI: 10.14573/1803231 RISK-HUNT3RPMID: 29984806
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Dynamic imaging of adaptive stress response pathway activation for prediction of drug induced liver injury2018 | Archives of ToxicologyWink StevenDOI: 10.1007/s00204-018-2178-z RISK-HUNT3RPMID: 29502165
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Highlight report: 'Big data in the 3R's: outlook and recommendations', a roundtable summary2018 | Archives of ToxicologyMahony CatherineDOI: 10.1007/s00204-017-2145-0 RISK-HUNT3RPMID: 29340744
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QSARpy: A new flexible algorithm to generate QSAR models based on dissimilarities. The log Kow case study2018 | Science of the Total EnvironmentFerrari ThomasDOI: 10.1016/j.scitotenv.2018.05.072 RISK-HUNT3RPMID: 29801209
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SAR for gastro-intestinal absorption and blood-brain barrier permeation of pesticides2018 | Chemico-Biological InteractionsToropov Andrey A.DOI: 10.1016/j.cbi.2018.04.030 RISK-HUNT3RPMID: 29753609
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The application of new HARD-descriptor available from the CORAL software to building up NOAEL models2018 | Food and Chemical ToxicologyToropova Alla P.DOI: 10.1016/j.fct.2017.03.060 RISK-HUNT3RPMID: 28366846
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Customised in vitro model to detect human metabolism-dependent idiosyncratic drug-induced liver injury2018 | Archives of ToxicologyTolosa LaiaDOI: 10.1007/s00204-017-2036-4 RISK-HUNT3RPMID: 28762043
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New microRNA Biomarkers for Drug-Induced Steatosis and Their Potential to Predict the Contribution of Drugs to Non-alcoholic Fatty Liver Disease2018 | PubMed.govLópez-Riera MireiaDOI: 10.1007/s00204-021-03215-9 RISK-HUNT3RPMID: 35103819
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Legacy data sharing to improve drug safety assessment: the eTOX project2018 | Nature Reviews Drug DiscoverySanz FerranDOI: 10.1038/nrd.2017.177 RISK-HUNT3RPMID: 29026211
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Prediction of liver toxicity and mode of action using metabolomics in vitro in HepG2 cells2018 | Archives of ToxicologyRamirez TzutzuyDOI: 10.1007/s00204-017-2079-6 RISK-HUNT3RPMID: 28965233
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Generation of hepatocyte- and endocrine pancreatic-like cells from human induced endodermal progenitor cells2018 | PLoS OneSambathkumar RangarajanDOI: 10.1371/journal.pone.0197046 RISK-HUNT3RPMID: 29750821
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Strategies for In Vivo Genome Editing in Nondividing Cells2018 | Trends in BiotechnologyNami FatemeharefehDOI: 10.1016/j.tibtech.2018.03.004 RISK-HUNT3RPMID: 29685818
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Efficient Recombinase-Mediated Cassette Exchange in hPSCs to Study the Hepatocyte Lineage Reveals AAVS1 Locus-Mediated Transgene Inhibition2018 | Stem Cell ReportsOrdovás LauraDOI: 10.1016/j.stemcr.2018.01.034 Free PMC article RISK-HUNT3RPMID: 29444475
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A model-based assay design to reproduce in vivo patterns of acute drug-induced toxicity2018 | Archives of ToxicologyKuepfer LarsDOI: 10.1007/s00204-017-2041-7 RISK-HUNT3RPMID: 28852801
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SOX10 Single Transcription Factor-Based Fast and Efficient Generation of Oligodendrocytes from Human Pluripotent Stem Cells2018 | Stem Cell ReportsGarcía-León Juan AntonioDOI: 10.1016/j.stemcr.2017.12.014 RISK-HUNT3RPMID: 29337119
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Integrated 'omics analysis reveals new drug-induced mitochondrial perturbations in human hepatocytes2018 | Toxicology LettersWolters Jarno E JDOI: 10.1016/j.toxlet.2018.02.026 RISK-HUNT3RPMID: 29501571
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Validation of gene expression profiles from cholestatic hepatotoxicants in vitro against human in vivo cholestasis2018 | Toxicology in VitroVan den Hof Wim F P MDOI: 10.1016/j.tiv.2017.07.024 RISK-HUNT3RPMID: 28778767
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A systems biology approach to predictive developmental neurotoxicity of a larvicide used in the prevention of Zika virus transmission2018 | Toxicology and Applied PharmacologyAudouze KarineDOI: 10.1016/j.taap.2018.02.014 Free PMC article RISK-HUNT3RPMID: 29476864
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Prevention of neuronal apoptosis by astrocytes through thiol-mediated stress response modulation and accelerated recovery from proteotoxic stress2018 | Cell Death & Differentiation volume 25, pages 2101–2117 (2018)Gutbier SimonDOI: 10.1038/s41418-018-0229-x RISK-HUNT3R
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Toxicity, recovery, and resilience in a 3D dopaminergic neuronal in vitro model exposed to rotenone2018 | Archives of Toxicology volume 92, pages 2587–2606 (2018)Harris GeorginaDOI: 10.1007/s00204-018-2250-8 RISK-HUNT3R
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Essential components of methods papers2018 | ALTEXLeist MarcelDOI: 10.14573/altex.1807031 RISK-HUNT3R
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Machine Learning of Toxicological Big Data Enables Read-Across Structure Activity Relationships (RASAR) Outperforming Animal Test Reproducibility2018 | Toxicological SciencesLuechtefeld ThomasDOI: 10.1093/toxsci/kfy152 RISK-HUNT3R
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Model-based identification of TNFα-induced IKKβ-mediated and IκBα-mediated regulation of NFκB signal transduction as a tool to quantify the impact of drug-induced liver injury compounds2018 | npj Systems Biology and ApplicationsOppelt AngelaDOI: 10.1038/s41540-018-0058-z RISK-HUNT3RPMID: 29900006
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Advanced Good Cell Culture Practice for human primary, stem cell-derived and organoid models as well as microphysiological systems2018 | ALTEXPamies DavidDOI: 10.14573/altex.1710081 RISK-HUNT3R
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The BioStudies database—one stop shop for all data supporting a life sciences study2018 | Nucleic Acids Research, Volume 46, Issue D1, 4 January 2018, Pages D1266–D1270Sarkans UgisDOI: https://doi.org/10.1093/nar/gkx965 RISK-HUNT3R
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Spatio-temporal visualization of the distribution of acetaminophen as well as its metabolites and adducts in mouse livers by MALDI MSI2018 | Archives of ToxicologySezgin SelahaddinDOI: 10.1007/s00204-018-2271-3 RISK-HUNT3R
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An adverse outcome pathway for parkinsonian motor deficits associated with mitochondrial complex I inhibition2018 | Archives of ToxicologyTerron AndreaDOI: 10.1007/s00204-017-2133-4 RISK-HUNT3R
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Bile Microinfarcts in Cholestasis Are Initiated by Rupture of the Apical Hepatocyte Membrane and Cause Shunting of Bile to Sinusoidal Blood2018 | HepatologyGhallab AhmedDOI: 10.1002/hep.30213 RISK-HUNT3R
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Introducing WikiPathways as a Data-Source to Support Adverse Outcome Pathways for Regulatory Risk Assessment of Chemicals and Nanomaterials2018 | Frontiers in GeneticsMartens MarvinDOI: 10.3389/fgene.2018.00661 RISK-HUNT3R
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Predicting drug resistance related to ABC transporters using unsupervised Consensus Self-Organizing Maps2018 | Scientific ReportsEstrada-Tejedor RogerDOI: 10.1038/s41598-018-25235-9 RISK-HUNT3RPMID: 29717183
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Insights into the Structure, Function, and Ligand Discovery of the Large Neutral Amino Acid Transporter 1, LAT12018 | International Journal of Molecular SciencesSingh NateshDOI: 10.3390/ijms19051278 RISK-HUNT3RPMID: 29695141
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Comparing the performance of meta-classifiers-a case study on selected imbalanced data sets relevant for prediction of liver toxicity2018 | Journal of Computer-Aided Molecular DesignJain SankalpDOI: 10.1007/s10822-018-0116-z RISK-HUNT3RPMID: 29626291
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Generation of Hepatic Stellate Cells from Human Pluripotent Stem Cells Enables In Vitro Modeling of Liver Fibrosis2018 | Cell Stem CellColl MarDOI: 10.1016/j.stem.2018.05.027 RISK-HUNT3R
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Comparison of base-line and chemical-induced transcriptomic responses in HepaRG and RPTEC/TERT1 cells using TempO-Seq2018 | Archives of ToxicologyLimonciel AliceDOI: 10.1007/s00204-018-2256-2 RISK-HUNT3RPMID: 30008028
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QSAR Modeling of ToxCast Assays Relevant to the Molecular Initiating Events of AOPs Leading to Hepatic Steatosis2018 | Journal of Chemical Information and ModelingGadaleta DomenicoDOI: 10.1021/acs.jcim.8b00297 RISK-HUNT3RPMID: 29949360
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Relevance of the incubation period in cytotoxicity testing with primary human hepatocytes2018 | Archives of ToxicologyGu XiaolongDOI: 10.1007/s00204-018-2302-0 RISK-HUNT3RPMID: 30317417
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Development of an Infrastructure for the Prediction of Biological Endpoints in Industrial Environments. Lessons Learned at the eTOX Project2018 | Frontiers in PharmacologyPastor ManuelDOI: 10.3389/fphar.2018.01147 RISK-HUNT3R
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Major changes of cell function and toxicant sensitivity in cultured cells undergoing mild, quasi-natural genetic drift2018 | Archives of ToxicologyGutbier SimonDOI: 10.1007/s00204-018-2326-5 RISK-HUNT3RPMID: 30298209
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A new semi-automated workflow for chemical data retrieval and quality checking for modeling applications2018 | Journal of CheminformaticsGadaleta DomenicoDOI: 10.1186/s13321-018-0315-6 RISK-HUNT3RPMID: 30536051
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Persistence of Epigenomic Effects After Recovery From Repeated Treatment With Two Nephrocarcinogens2018 | Frontiers in GeneticsLimonciel AliceDOI: https://doi.org/10.3389/fgene.2018.00558 RISK-HUNT3R
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Investigation of Nrf2, AhR and ATF4 Activation in Toxicogenomic Databases2018 | Frontiers in GeneticsZgheib EliasDOI: 10.3389/fgene.2018.00429 RISK-HUNT3RPMID: 30333853
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In vitro acute and developmental neurotoxicity screening: an overview of cellular platforms and high-throughput technical possibilities2017 | PubMed.govSchmidt Béla Z.DOI: 10.1007/s00204-016-1805-9 RISK-HUNT3R
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Good Cell Culture Practice for stem cells and stem-cell-derived models2017 | AltexPamies DavidDOI: 10.14573/altex.1607121 RISK-HUNT3RPMID: 27554434
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Improved building up a model of toxicity towards Pimephales promelas by the Monte Carlo method2017 | Environmental Toxicology and PharmacologyToropova Alla P.DOI: 10.1016/j.etap.2016.11.010 RISK-HUNT3R
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The ascending pathophysiology of cholestatic liver disease2017 | HepatologyJansen Peter L.M.DOI: 10.1002/hep.28965 RISK-HUNT3R
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CORAL: Binary classifications (active/inactive) for drug-induced liver injury2017 | Toxicology LettersToropova Alla P.DOI: 10.1016/j.toxlet.2017.01.011 RISK-HUNT3R
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Impairment of human neural crest cell migration by prolonged exposure to interferon-beta2017 | Archives of ToxicologyPallocca GiorgiaDOI: 10.1007/s00204-021-03215-9 RISK-HUNT3RPMID: 35103819
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OECD/EFSA workshop on developmental neurotoxicity (DNT): The use of non-animal test methods for regulatory purposes2017 | AltexFritsche EllenDOI: 10.14573/altex.1701171 RISK-HUNT3RPMID: 28407175
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Tipping Points and Endogenous Determinants of Nigrostriatal Degeneration by MPTP2017 | Trends in Pharmacological SciencesSchildknecht StefanDOI: 10.1016/j.tips.2017.03.010 RISK-HUNT3RPMID: 28442167
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Combination of multiple neural crest migration assays to identify environmental toxicants from a proof-of-concept chemical library2017 | Archives of ToxicologyNyffeler JohannaDOI: 10.1007/s00204-021-03215-9 RISK-HUNT3RPMID: 35103819
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New animal-free concepts and test methods for developmental toxicity and peripheral neurotoxicity2017 | Alternatives to Laboratory AnimalsLeist MarcelDOI: 10.1177/026119291704500505 RISK-HUNT3RPMID: 29112453
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The index of ideality of correlation: A criterion of predictive potential of QSPR/QSAR models?2017 | Mutation Research/Genetic Toxicology and Environmental MutagenesisToropov Andrey A.DOI: 10.1016/j.mrgentox.2017.05.008 RISK-HUNT3R
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Adverse outcome pathways: opportunities, limitations and open questions2017 | Archives of ToxicologyLeist MarcelDOI: 10.1007/s00204-017-2045-3 RISK-HUNT3RPMID: 29051992
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Hybrid optimal descriptors as a tool to predict skin sensitization in accordance to OECD principles2017 | Toxicology LettersToropova Alla P.DOI: 10.1016/j.toxlet.2017.03.023 RISK-HUNT3R
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Ab initio chemical safety assessment: A workflow based on exposure considerations and non-animal methods2017 | Computational ToxicologyBerggren ElisabetDOI: 10.1016/j.comtox.2017.10.001 RISK-HUNT3RPMID: 29214231
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Comprehensive Landscape of Nrf2 and p53 Pathway Activation Dynamics by Oxidative Stress and DNA Damage2017 | Chem Res ToxicolHiemstra Steven WDOI: 10.1021/acs.chemrestox.6b00322 RISK-HUNT3RPMID: 27982581
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A frequent misinterpretation in current research on liver fibrosis: the vessel in the center of CCl 4-induced pseudolobules is a portal vein2017 | Archives of ToxicologyHammad SeddikDOI: 10.1007/s00204-017-2040-8 RISK-HUNT3RPMID: 28825120
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Adverse outcome pathways: a concise introduction for toxicologists2017 | Archives of ToxicologyVinken MathieuDOI: 10.1007/s00204-017-2020-z RISK-HUNT3RPMID: 28660287
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Exposure to PFOA and PFOS and fetal growth: a critical merging of toxicological and epidemiological data2017 | Critical Reviews in ToxicologyNegri EvaDOI: 10.1080/10408444.2016.1271972 RISK-HUNT3RPMID: 28617200
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Framework for the quality assurance of 'omics technologies considering GLP requirements2017 | Regulatory Toxicology and PharmacologyKauffmann Hans-MartinDOI: 10.1016/j.yrtph.2017.10.007 RISK-HUNT3RPMID: 28987912
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DTNI: a novel toxicogenomics data analysis tool for identifying the molecular mechanisms underlying the adverse effects of toxic compounds2017 | Archives of ToxicologyHendrickx Diana MDOI: 10.1007/s00204-016-1922-5 RISK-HUNT3RPMID: 28032149
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Human Environmental Disease Network: A computational model to assess toxicology of contaminants2017 | ALTEXTaboureau OlivierDOI: 10.14573/altex.1607201 RISK-HUNT3RPMID: 27768803
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Highlight report: Launch of a large integrated European in vitro toxicology project: EU‑ToxRisk2016 | Archives of ToxicologyDaneshian MardasDOI: 10.1007/s00204-016-1698-7 RISK-HUNT3RPMID: 27017488
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Reference compounds for alternative test methods to indicate developmental neurotoxicity (DNT) potential of chemicals: example lists and criteria for their selection and use2016 | AltexAschner MichaelDOI: 10.14573/altex.1604201 RISK-HUNT3RPMID: 27452664
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A Multi-Compartment Liver Model for the Prediction of Toxicokinetics2016 | Toxicology LettersFisher CiaránDOI: 10.1016/j.toxlet.2016.06.1489 RISK-HUNT3RPMID: 35103819
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Definition of transcriptome‑based indices for quantitative characterization of chemically disturbed stem cell development: introduction of the STOP‑Toxukn and STOP‑Toxukk tests2016 | Archives of ToxicologyShinde VaibhavDOI: 10.1007/s00204-016-1741-8 RISK-HUNT3RPMID: 27188386
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Astrocyte Differentiation of Human Pluripotent Stem Cells: New Tools for Neurological Disorder Research2016 | Frontiers in Cellular NeuroscienceChandrasekaran AbinayaDOI: 10.3389/fncel.2016.00215 RISK-HUNT3RPMID: 27725795
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In Silico Systems Pharmacology to Assess Drug's Therapeutic and Toxic Effects2016 | Current Pharmaceutical DesignAguayo-Orozco AlejandroDOI: 10.2174/1381612822666160907093215 RISK-HUNT3R
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Human environmental disease network: A computational model to assess toxicology of contaminants2016 | AltexTaboureau OlivierDOI: 10.14573/altex.1607201 RISK-HUNT3RPMID: 27768803