Adverse Outcome Pathways Mechanistically Describing Hepatotoxicity.

Adverse outcome pathways (AOPs) describe toxicological processes from a dynamic perspective by linking a molecular initiating event to a specific adverse outcome via a series of key events and key event relationships. In the field of computational toxicology, AOPs can potentially facilitate the design and development of in silico prediction models for hazard identification. Various AOPs have been introduced for several types of hepatotoxicity, such as steatosis, cholestasis, fibrosis, and liver cancer. This chapter provides an overview of AOPs on hepatotoxicity, including their development, assessment, and applications in toxicology.

Elevated risk of adverse effects from foodborne contaminants and drugs in inflammatory bowel disease: a review.

The global burden of Inflammatory bowel disease (IBD) has been rising over the last decades. IBD is an intestinal disorder with a complex and largely unknown etiology. The disease is characterized by a chronically inflamed gastrointestinal tract, with intermittent phases of exacerbation and remission. This compromised intestinal barrier can contribute to, enhance, or even enable the toxicity of drugs, food-borne chemicals and particulate matter. This review discusses whether the rising prevalence of IBD in our society warrants the consideration of IBD patients as a specific population group in toxicological safety assessment. Various in vivo, ex vivo and in vitro models are discussed that can simulate hallmarks of IBD and may be used to study the effects of prevalent intestinal inflammation on the hazards of these various toxicants. In conclusion, risk assessments based on healthy individuals may not sufficiently cover IBD patient safety and it is suggested to consider this susceptible subgroup of the population in future toxicological assessments.

Artificial intelligence-based data extraction for next generation risk assessment: Is fine-tuning of a large language model worth the effort?

To underpin scientific evaluations of chemical risks, agencies such as the European Food Safety Authority (EFSA) heavily rely on the outcome of systematic reviews, which currently require extensive manual effort. One specific challenge constitutes the meaningful use of vast amounts of valuable data from new approach methodologies (NAMs) which are mostly reported in an unstructured way in the scientific literature. In the EFSA-initiated project 'AI4NAMS', the potential of large language models (LLMs) was explored. Models from the GPT family, where GPT refers to Generative Pre-trained Transformer, were used for searching, extracting, and integrating data from scientific publications for NAM-based risk assessment. A case study on bisphenol A (BPA), a substance of very high concern due to its adverse effects on human health, focused on the structured extraction of information on test systems measuring biologic activities of BPA. Fine-tuning of a GPT-3 model (Curie base model) for extraction tasks was tested and the performance of the fine-tuned model was compared to the performance of a ready-to-use model (text-davinci-002). To update findings from the AI4NAMS project and to check for technical progress, the fine-tuning exercise was repeated and a newer ready-to-use model (text-davinci-003) served as comparison. In both cases, the fine-tuned Curie model was found to be superior to the ready-to-use model. Performance improvement was also obvious between text-davinci-002 and the newer text-davinci-003. Our findings demonstrate how fine-tuning and the swift general technical development improve model performance and contribute to the growing number of investigations on the use of AI in scientific and regulatory tasks.

Report of the First ONTOX Stakeholder Network Meeting: Digging Under the Surface of ONTOX Together With the Stakeholders.

The first Stakeholder Network Meeting of the EU Horizon 2020-funded ONTOX project was held on 13-14 March 2023, in Brussels, Belgium. The discussion centred around identifying specific challenges, barriers and drivers in relation to the implementation of non-animal new approach methodologies (NAMs) and probabilistic risk assessment (PRA), in order to help address the issues and rank them according to their associated level of difficulty. ONTOX aims to advance the assessment of chemical risk to humans, without the use of animal testing, by developing non-animal NAMs and PRA in line with 21st century toxicity testing principles. Stakeholder groups (regulatory authorities, companies, academia, non-governmental organisations) were identified and invited to participate in a meeting and a survey, by which their current position in relation to the implementation of NAMs and PRA was ascertained, as well as specific challenges and drivers highlighted. The survey analysis revealed areas of agreement and disagreement among stakeholders on topics such as capacity building, sustainability, regulatory acceptance, validation of adverse outcome pathways, acceptance of artificial intelligence (AI) in risk assessment, and guaranteeing consumer safety. The stakeholder network meeting resulted in the identification of barriers, drivers and specific challenges that need to be addressed. Breakout groups discussed topics such as hazard versus risk assessment, future reliance on AI and machine learning, regulatory requirements for industry and sustainability of the ONTOX Hub platform. The outputs from these discussions provided insights for overcoming barriers and leveraging drivers for implementing NAMs and PRA. It was concluded that there is a continued need for stakeholder engagement, including the organisation of a 'hackathon' to tackle challenges, to ensure the successful implementation of NAMs and PRA in chemical risk assessment.

Using in vitro data to derive acceptable exposure levels: A case study on PBDE developmental neurotoxicity.

BACKGROUND: Current acceptable chemical exposure levels (e.g., tolerable daily intake) are mainly based on animal experiments, which are costly, time-consuming, considered non-ethical by many, and may poorly predict adverse outcomes in humans. OBJECTIVE: To evaluate a method using human in vitro data and biological modeling to calculate an acceptable exposure level through a case study on 2,2',4,4'-tetrabromodiphenyl ether (BDE-47) developmental neurotoxicity (DNT). METHODS: We reviewed the literature on in vitro assays studying BDE-47-induced DNT. Using the most sensitive endpoint, we derived a point of departure using a mass-balance in vitro disposition model and benchmark dose modeling for a 5% response (BMC05) in cells. We subsequently used a pharmacokinetic model of gestation and lactation to estimate administered equivalent doses leading to four different metrics of child brain concentration (i.e., average prenatal, average postnatal, average overall, and maximum concentration) equal to the point of departure. The administered equivalent doses were translated into tolerable daily intakes using uncertainty factors. Finally, we calculated biomonitoring equivalents for maternal serum and compared them to published epidemiological studies of DNT. RESULTS: We calculated a BMC05 of 164 µg/kg of cells for BDE-47 induced alteration of differentiation in neural progenitor cells. We estimated administered equivalent doses of 0.925-3.767 µg/kg/day in mothers, and tolerable daily intakes of 0.009-0.038 µg/kg/day (composite uncertainty factor: 100). The lowest derived biomonitoring equivalent was 19.75 ng/g lipids, which was consistent with reported median (0.9-23 ng/g lipids) and geometric mean (7.02-26.9 ng/g lipids) maternal serum concentrations from epidemiological studies. CONCLUSION: This case study supports using in vitro data and biological modeling as a viable alternative to animal testing to derive acceptable exposure levels.

Use of Physiologically Based Kinetic Modeling to Predict Deoxynivalenol Metabolism and Its Role in Intestinal Inflammation and Bile Acid Kinetics in Humans.

Current points of departure used to derive health-based guidance values for deoxynivalenol (DON) are based on studies in laboratory animals. Here, an animal-free testing approach was adopted in which a reverse dosimetry physiologically based kinetic (PBK) modeling is used to predict in vivo dose response curves for DON's effects on intestinal pro-inflammatory cytokine secretion and intestinal bile acid reabsorption in humans from concentration-effect relationships for DON in vitro. The calculated doses for inducing a 5% added effect above the background level (ED5) of DON for increasing IL-1ß secretion in intestinal tissue and for increasing the amounts in the colon lumen of glycochenodeoxycholic acid (GCDCA) were 246 and 36 µg/kg bw/day, respectively. These in vitro-in silico-derived ED5 values were compared to human dietary DON exposure levels, indicating that the risk of DON's effects on these end points occurring in various human populations cannot be excluded. This in vitro-in silico approach provides a novel testing strategy for hazard and risk assessment without using laboratory animals.

Acetylcholinesterase Inhibition in Rats and Humans Following Acute Fenitrothion Exposure Predicted by Physiologically Based Kinetic Modeling-Facilitated Quantitative In Vitro to In Vivo Extrapolation.

Worldwide use of organophosphate pesticides as agricultural chemicals aims to maintain a stable food supply, while their toxicity remains a major public health concern. A common mechanism of acute neurotoxicity following organophosphate pesticide exposure is the inhibition of acetylcholinesterase (AChE). To support Next Generation Risk Assessment for public health upon acute neurotoxicity induced by organophosphate pesticides, physiologically based kinetic (PBK) modeling-facilitated quantitative in vitro to in vivo extrapolation (QIVIVE) approach was employed in this study, with fenitrothion (FNT) as an exemplary organophosphate pesticide. Rat and human PBK models were parametrized with data derived from in silico predictions and in vitro incubations. Then, PBK model-based QIVIVE was performed to convert species-specific concentration-dependent AChE inhibition obtained from in vitro blood assays to corresponding in vivo dose-response curves, from which points of departure (PODs) were derived. The obtained values for rats and humans were comparable with reported no-observed-adverse-effect levels (NOAELs). Humans were found to be more susceptible than rats toward erythrocyte AChE inhibition induced by acute FNT exposure due to interspecies differences in toxicokinetics and toxicodynamics. The described approach adequately predicts toxicokinetics and acute toxicity of FNT, providing a proof-of-principle for applying this approach in a 3R-based chemical risk assessment paradigm.

Integrating distribution kinetics and toxicodynamics to assess repeat dose neurotoxicity in vitro using human BrainSpheres: a case study on amiodarone.

For ethical, economical, and scientific reasons, animal experimentation, used to evaluate the potential neurotoxicity of chemicals before their release in the market, needs to be replaced by new approach methodologies. To illustrate the use of new approach methodologies, the human induced pluripotent stem cell-derived 3D model BrainSpheres was acutely (48 h) or repeatedly (7 days) exposed to amiodarone (0.625-15 µM), a lipophilic antiarrhythmic drug reported to have deleterious effects on the nervous system. Neurotoxicity was assessed using transcriptomics, the immunohistochemistry of cell type-specific markers, and real-time reverse transcription-polymerase chain reaction for various genes involved in the lipid metabolism. By integrating distribution kinetics modeling with neurotoxicity readouts, we show that the observed time- and concentration-dependent increase in the neurotoxic effects of amiodarone is driven by the cellular accumulation of amiodarone after repeated dosing. The development of a compartmental in vitro distribution kinetics model allowed us to predict the change in cell-associated concentrations in BrainSpheres with time and for different exposure scenarios. The results suggest that human cells are intrinsically more sensitive to amiodarone than rodent cells. Amiodarone-induced regulation of lipid metabolism genes was observed in brain cells for the first time. Astrocytes appeared to be the most sensitive human brain cell type in vitro. In conclusion, assessing readouts at different molecular levels after the repeat dosing of human induced pluripotent stem cell-derived BrainSpheres in combination with the compartmental modeling of in vitro kinetics provides a mechanistic means to assess neurotoxicity pathways and refine chemical safety assessment for humans.

Integrating In Vitro Data and Physiologically Based Kinetic Modeling to Predict and Compare Acute Neurotoxic Doses of Saxitoxin in Rats, Mice, and Humans.

Current climate trends are likely to expand the geographic distribution of the toxigenic microalgae and concomitant phycotoxins, making intoxications by such toxins a global phenomenon. Among various phycotoxins, saxitoxin (STX) acts as a neurotoxin that might cause severe neurological symptoms in mammals following consumptions of contaminated seafood. To derive a point of departure (POD) for human health risk assessment upon acute neurotoxicity induced by oral STX exposure, a physiologically based kinetic (PBK) modeling-facilitated quantitative in vitro to in vivo extrapolation (QIVIVE) approach was employed. The PBK models for rats, mice, and humans were built using parameters from the literature, in vitro experiments, and in silico predictions. Available in vitro toxicity data for STX were converted to in vivo dose-response curves via the PBK models established for these three species, and POD values were derived from the predicted curves and compared to reported in vivo toxicity data. Interspecies differences in acute STX toxicity between rodents and humans were found, and they appeared to be mainly due to differences in toxicokinetics. The described approach resulted in adequate predictions for acute oral STX exposure, indicating that new approach methodologies, when appropriately integrated, can be used in a 3R-based chemical risk assessment paradigm.

Drug Metabolism of Hepatocyte-like Organoids and Their Applicability in In Vitro Toxicity Testing.

Emerging advances in the field of in vitro toxicity testing attempt to meet the need for reliable human-based safety assessment in drug development. Intrahepatic cholangiocyte organoids (ICOs) are described as a donor-derived in vitro model for disease modelling and regenerative medicine. Here, we explored the potential of hepatocyte-like ICOs (HL-ICOs) in in vitro toxicity testing by exploring the expression and activity of genes involved in drug metabolism, a key determinant in drug-induced toxicity, and the exposure of HL-ICOs to well-known hepatotoxicants. The current state of drug metabolism in HL-ICOs showed levels comparable to those of PHHs and HepaRGs for CYP3A4; however, other enzymes, such as CYP2B6 and CYP2D6, were expressed at lower levels. Additionally, EC50 values were determined in HL-ICOs for acetaminophen (24.0−26.8 mM), diclofenac (475.5−>500 µM), perhexiline (9.7−>31.5 µM), troglitazone (23.1−90.8 µM), and valproic acid (>10 mM). Exposure to the hepatotoxicants showed EC50s in HL-ICOs comparable to those in PHHs and HepaRGs; however, for acetaminophen exposure, HL-ICOs were less sensitive. Further elucidation of enzyme and transporter activity in drug metabolism in HL-ICOs and exposure to a more extensive compound set are needed to accurately define the potential of HL-ICOs in in vitro toxicity testing.

The effects of hexabromocyclododecane on the transcriptome and hepatic enzyme activity in three human HepaRG-based models.

The disruption of thyroid hormone homeostasis by hexabromocyclododecane (HBCD) in rodents is hypothesized to be due to HBCD increasing the hepatic clearance of thyroxine (T4). The extent to which these effects are relevant to humans is unclear. To evaluate HBCD effects on humans, the activation of key hepatic nuclear receptors and the consequent disruption of thyroid hormone homeostasis were studied in different human hepatic cell models. The hepatoma cell line, HepaRG, cultured as two-dimensional (2D), sandwich (SW) and spheroid (3D) cultures, and primary human hepatocytes (PHH) cultured as sandwich were exposed to 1 and 10 µM HBCD and characterized for their transcriptome changes. Pathway enrichment analysis showed that 3D models, followed by SW, had a stronger transcriptome response to HBCD, which is explained by the higher expression of hepatic nuclear receptors but also greater accumulation of HBCD measured inside cells in these models. The Pregnane X receptor pathway is one of the pathways most upregulated across the three hepatic models, followed by the constitutive androstane receptor and general hepatic nuclear receptors pathways. Lipid metabolism pathways had a downregulation tendency in all exposures and in both PHH and the three cultivation modes of HepaRG. The activity of enzymes related to PXR/CAR induction and T4 metabolism were evaluated in the three different types of HepaRG cultures exposed to HBCD for 48 h. Reference inducers, rifampicin and PCB-153 did affect 2D and SW HepaRG cultures' enzymatic activity but not 3D. HBCD did not induce the activity of any of the studied enzymes in any of the cell models and culture methods. This study illustrates that for nuclear receptor-mediated T4 disruption, transcriptome changes might not be indicative of an actual adverse effect. Clarification of the reasons for the lack of translation is essential to evaluate new chemicals' potential to be thyroid hormone disruptors by altering thyroid hormone metabolism.

The role of receptor-mediated activities of 4- and 5-ring unsubstituted and methylated polycyclic aromatic hydrocarbons (PAHs) in developmental toxicity.

The present study evaluated the aryl hydrocarbon receptor (AhR), estrogen receptor-α (ER-α), and retinoic acid receptor (RAR) mediated activities of nine 4- and 5-ring unsubstituted and monomethylated polycyclic aromatic hydrocarbons (PAHs) using a series of Chemical-Activated LUciferase gene eXpression (CALUX) assays. The potential role of these aforementioned receptors in relation to the developmental toxicity of these PAHs was further assessed in the zebrafish embryotoxicity test (ZET). The results show that all nine tested PAHs were AhR agonists, benz[a]anthracene (BaA) and 8-methyl-benz[a]anthracene (8-MeBaA) were ER-α agonists, and none of the tested PAHs induced ER-α antagonistic or RAR (ant)agonistic activities. In the AhR CALUX assay, all the methylated PAHs showed higher potency (lower EC50) in activating the AhR than their respective unsubstituted PAHs, implying that the addition of a methyl substituent on the aromatic ring of PAHs could enhance their AhR-mediated activities. Co-exposure of zebrafish embryos with each individual PAH and an AhR antagonist (CH223191) counteracted the observed developmental retardations and embryo lethality to a certain extent, except for 8-methyl-benzo[a]pyrene (8-MeBaP). Co-exposure of zebrafish embryos with either of the two estrogenic PAHs (i.e., BaA and 8-MeBaA) and an ER-α antagonist (fulvestrant) neutralized embryo lethality induced by 50 µM BaA and the developmental retardations induced by 15 µM 8-MeBaA. Altogether, our findings suggest that the observed developmental retardations in zebrafish embryos by the PAH tested may partially be AhR- and/or ER-α-mediated, whereas the RAR seems not to be relevant for the PAH-induced developmental toxicity in the ZET.

Applicability of generic PBK modelling in chemical hazard assessment: A case study with IndusChemFate.

Toxicology is moving away from animal testing towards in vitro tools to assess chemical safety. This new testing framework requires a quantitative method, i.e. kinetic modelling, which extrapolates effective concentrations in vitro to a bioequivalent human dose in vivo and which can be applied on "high throughput screening" of a wide variety of chemicals. Generic physiologically based kinetic (PBK) models help account for the role of toxicokinetics in setting human toxic exposure levels. Furthermore these models may be parameterized only on in silico QSARs and in vitro metabolism assays, thereby circumventing the use of in vivo toxicokinetics for this purpose. Though several such models exist their applicability domains have yet to be comprehensively assessed. This study extends previous evaluations of the PBK model IndusChemFate and compares it with its more complex biological complement ("TNO Model"). Both models were evaluated with a broad span of chemicals, varying regarding physicochemical properties. The results reveal that the "simpler" performed best, illustrating that IndusChemFate can be a useful first-tier for simulating toxicokinetics based on QSARs and in vitro parameters. Finally, proper quantitative in vitro to in vivo extrapolation conditions were illustrated starting with acetaminophen induced in vitro cytotoxicity in human HepaRG cells.

Dynamic Mass Balance Modeling for Chemical Distribution Over Time in In Vitro Systems With Repeated Dosing.

As toxicologists and risk assessors move away from animal testing and more toward using in vitro models and biological modeling, it is necessary to produce tools to quantify the chemical distribution within the in vitro environment prior to extrapolating in vitro concentrations to human equivalent doses. Although models predicting chemical distribution in vitro have been developed, very little has been done for repeated dosing scenarios, which are common in prolonged experiments where the medium needs to be refreshed. Failure to account for repeated dosing may lead to inaccurate estimations of exposure and introduce bias into subsequent in vitro to in vivo extrapolations. Our objectives were to develop a dynamic mass balance model for repeated dosing in in vitro systems; to evaluate model accuracy against experimental data; and to perform illustrative simulations to assess the impact of repeated doses on predicted cellular concentrations. A novel dynamic in vitro partitioning mass balance model (IV-MBM DP v1.0) was created based on the well-established fugacity approach. We parameterized and applied the dynamic mass balance model to single dose and repeat dosing scenarios, and evaluated the predicted medium and cellular concentrations against available empirical data. We also simulated repeated dosing scenarios for organic chemicals with a range of partitioning properties and compared the in vitro distributions over time. In single dose scenarios, for which only medium concentrations were available, simulated concentrations predicted measured concentrations with coefficients of determination (R 2) of 0.85-0.89, mean absolute error within a factor of two and model bias of nearly one. Repeat dose scenario simulations displayed model bias <2 within the cell lysate, and ∼1.5-3 in the medium. The concordance between simulated and available experimental data supports the predictive capacity of the IV-MBM DP v1.0 tool, but further evaluation as empirical data becomes available is warranted, especially for cellular concentrations.

Towards best use and regulatory acceptance of generic physiologically based kinetic (PBK) models for in vitro-to-in vivo extrapolation (IVIVE) in chemical risk assessment.

With an increasing need to incorporate new approach methodologies (NAMs) in chemical risk assessment and the concomitant need to phase out animal testing, the interpretation of in vitro assay readouts for quantitative hazard characterisation becomes more important. Physiologically based kinetic (PBK) models, which simulate the fate of chemicals in tissues of the body, play an essential role in extrapolating in vitro effect concentrations to in vivo bioequivalent exposures. As PBK-based testing approaches evolve, it will become essential to standardise PBK modelling approaches towards a consensus approach that can be used in quantitative in vitro-to-in vivo extrapolation (QIVIVE) studies for regulatory chemical risk assessment based on in vitro assays. Based on results of an ECETOC expert workshop, steps are recommended that can improve regulatory adoption: (1) define context and implementation, taking into consideration model complexity for building fit-for-purpose PBK models, (2) harmonise physiological input parameters and their distribution and define criteria for quality chemical-specific parameters, especially in the absence of in vivo data, (3) apply Good Modelling Practices (GMP) to achieve transparency and design a stepwise approach for PBK model development for risk assessors, (4) evaluate model predictions using alternatives to in vivo PK data including read-across approaches, (5) use case studies to facilitate discussions between modellers and regulators of chemical risk assessment. Proof-of-concepts of generic PBK modelling approaches are published in the scientific literature at an increasing rate. Working on the previously proposed steps is, therefore, needed to gain confidence in PBK modelling approaches for regulatory use.

Application of the Adverse Outcome Pathway Concept to In Vitro Nephrotoxicity Assessment: Kidney Injury due to Receptor-Mediated Endocytosis and Lysosomal Overload as a Case Study.

Application of adverse outcome pathways (AOP) and integration of quantitative in vitro to in vivo extrapolation (QIVIVE) may support the paradigm shift in toxicity testing to move from apical endpoints in test animals to more mechanism-based in vitro assays. Here, we developed an AOP of proximal tubule injury linking a molecular initiating event (MIE) to a cascade of key events (KEs) leading to lysosomal overload and ultimately to cell death. This AOP was used as a case study to adopt the AOP concept for systemic toxicity testing and risk assessment based on in vitro data. In this AOP, nephrotoxicity is thought to result from receptor-mediated endocytosis (MIE) of the chemical stressor, disturbance of lysosomal function (KE1), and lysosomal disruption (KE2) associated with release of reactive oxygen species and cytotoxic lysosomal enzymes that induce cell death (KE3). Based on this mechanistic framework, in vitro readouts reflecting each KE were identified. Utilizing polymyxin antibiotics as chemical stressors for this AOP, the dose-response for each in vitro endpoint was recorded in proximal tubule cells from rat (NRK-52E) and human (RPTEC/TERT1) in order to (1) experimentally support the sequence of key events (KEs), to (2) establish quantitative relationships between KEs as a basis for prediction of downstream KEs based on in vitro data reflecting early KEs and to (3) derive suitable in vitro points of departure for human risk assessment. Time-resolved analysis was used to support the temporal sequence of events within this AOP. Quantitative response-response relationships between KEs established from in vitro data on polymyxin B were successfully used to predict in vitro toxicity of other polymyxin derivatives. Finally, a physiologically based kinetic (PBK) model was utilized to transform in vitro effect concentrations to a human equivalent dose for polymyxin B. The predicted in vivo effective doses were in the range of therapeutic doses known to be associated with a risk for nephrotoxicity. Taken together, these data provide proof-of-concept for the feasibility of in vitro based risk assessment through integration of mechanistic endpoints and reverse toxicokinetic modelling.

A regression-based QSAR-model to predict acute toxicity of aromatic chemicals in tadpoles of the Japanese brown frog (Rana japonica): Calibration, validation, and future developments to support risk assessment of chemicals in amphibians.

Amphibian populations are undergoing a global decline worldwide. Such decline has been attributed to their unique physiology, ecology, and exposure to multiple stressors including chemicals, temperature, and biological hazards such as fungi of the Batrachochytrium genus, viruses such as Ranavirus, and habitat reduction. There are limited toxicity data for chemicals available for amphibians and few quantitative structure-activity relationship (QSAR) models have been developed and are publicly available. Such QSARs provide important tools to assess the toxicity of chemicals particularly in a data poor context. QSARs provide important tools to assess the toxicity of chemicals particularly when no toxicological data are available. This manuscript provides a description and validation of a regression-based QSAR model to predict, in a quantitative manner, acute lethal toxicity of aromatic chemicals in tadpoles of the Japanese brown frog (Rana japonica). QSAR models for acute median lethal molar concentrations (LC50-12 h) of waterborne chemicals using the Monte Carlo method were developed. The statistical characteristics of the QSARs were described as average values obtained from five random distributions into training and validation sets. Predictions from the model gave satisfactory results for the overall training set (R2 = 0.72 and RMSE = 0.33) and were even more robust for the validation set (R2 = 0.96 and RMSE = 0.11). Further development of QSAR models in amphibians, particularly for other life stages and species, are discussed.

In Silico Methods for Environmental Risk Assessment: Principles, Tiered Approaches, Applications, and Future Perspectives.

This chapter aims to introduce the reader to the basic principles of environmental risk assessment of chemicals and highlights the usefulness of tiered approaches within weight of evidence approaches in relation to problem formulation i.e., data availability, time and resource availability. In silico models are then introduced and include quantitative structure-activity relationship (QSAR) models, which support filling data gaps when no chemical property or ecotoxicological data are available. In addition, biologically-based models can be applied in more data rich situations and these include generic or species-specific models such as toxicokinetic-toxicodynamic models, dynamic energy budget models, physiologically based models, and models for ecosystem hazard assessment i.e. species sensitivity distributions and ultimately for landscape assessment i.e. landscape-based modeling approaches. Throughout this chapter, particular attention is given to provide practical examples supporting the application of such in silico models in real-world settings. Future perspectives are discussed to address environmental risk assessment in a more holistic manner particularly for relevant complex questions, such as the risk assessment of multiple stressors and the development of harmonized approaches to ultimately quantify the relative contribution and impact of single chemicals, multiple chemicals and multiple stressors on living organisms.

Bioprinting of Human Liver-Derived Epithelial Organoids for Toxicity Studies.

There is a need for long-lived hepatic in vitro models to better predict drug induced liver injury (DILI). Human liver-derived epithelial organoids are a promising cell source for advanced in vitro models. Here, organoid technology is combined with biofabrication techniques, which holds great potential for the design of in vitro models with complex and customizable architectures. Here, porous constructs with human hepatocyte-like cells derived from organoids are generated using extrusion-based printing technology. Cell viability of bioprinted organoids remains stable for up to ten days (88-107% cell viability compared to the day of printing). The expression of hepatic markers, transporters, and phase I enzymes increased compared to undifferentiated controls, and is comparable to non-printed controls. Exposure to acetaminophen, a well-known hepatotoxic compound, decreases cell viability of bioprinted liver organoids to 21-51% (p < 0.05) compared to the start of exposure, and elevated levels of damage marker miR-122 are observed in the culture medium, indicating the potential use of the bioprinted constructs for toxicity testing. In conclusion, human liver-derived epithelial organoids can be combined with a biofabrication approach, thereby paving the way to create perfusable, complex constructs which can be used as toxicology- and disease-models.