Antisense oligonucleotides (ASOs) are promising therapeutics, but safety concerns such as liver toxicity and off-target (OffT) effects necessitate thorough evaluation during the compound selection process. This study leverages time course global proteomics and transcriptomics to assess ASO-induced changes in vitro, comparing liver toxic versus non-liver toxic ASOs. The research confirms that ASOs perturb different cellular pathways at both RNA and protein levels, effectively discriminating between liver toxic and non-liver toxic ASOs. Contrary to expectations, protein level reduction isn't delayed relative to ASO-induced RNA reduction, highlighting the importance of understanding RNA and protein level relationships in specific model systems. Furthermore, many OffT effects observed at the RNA level do not directly translate to corresponding protein level changes. These findings suggest that current RNA-focused OffT assessment strategies capture predicted OffTs but could benefit from protein level studies that could potentially de-risk oligonucleotide drug (OND) candidates with seemingly problematic OffT profiles at the RNA level. The study underscores the value of global proteomics as a complement to RNAseq in ASO drug development, refining safety assessment and improving candidate selection.

Early warning systems (EWSs) are currently being developed by various authorities aiming at identifying potentially hazardous chemicals before they become a threat to the environment and human health. In this context, patents provide an excellent data source for exploring novel chemistry or the use of chemicals in materials and products. However, analysis of patents is challenging, including unraveling molecular structures presented as graphics depicting various elements, functional groups, and molecular bonds. Our study aims to improve EWS using automated artificial intelligence-based molecular structure recognition methods for encoding these for further hazard analysis. Current structure extraction tools are primarily trained on chemical structures collected from publicly available data sets, and the application of these tools to patent-specific chemical data has received little attention. This paper presents a field study utilizing the three tools Decimer, Molscribe, and Mathpix and assesses their performance in recognizing chemical structures in patents. Two data sets were compiled and curated including (1) diverse organic chemicals and (2) per- and polyfluoroalkyl substances (PFAS). It was revealed that these tools perform well on simpler molecular structures, whereas they struggle with more complex structural features, including repetitive units, cross-bonding, and Markush structures. Furthermore, it was discovered that these tools are extremely sensitive to image artifacts such as noise from lines and dots or distortions. Overcoming these challenges will be critical before implementation in automated EWS and thereby enable screening of patents for rapid and effective identification of potentially hazardous emerging chemicals.

Oligonucleotide therapeutics (ONTs) are a growing class of nucleic acid-based therapies with the potential to treat a variety of diseases through several different mechanisms of action (MoA). The most prevalent MoA entails the inhibition of therapeutically relevant levels of protein expression via mRNA degradation, exemplified by numerous approved ONTs. ONTs have unique physicochemical properties, pharmacokinetic characteristics, and MoAs that are distinct from other drug classes. The result can be a disconnect between the administered dose, plasma drug concentrations, pharmacodynamics, and toxicity. Thus, ONT development poses unique scientific and regulatory challenges that are not fully addressed by current International Council for Harmonisation (ICH) guidelines. The complexity of ONT development has recently been recognized with the acceptance of the new ICH topic proposal "ICH S13-Nonclinical Safety Evaluation of Oligonucleotide-based Therapeutics." In preparation for the ICH S13 Step 2 public consultation period, the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) DruSafe ONT Working Group convened to identify and discuss key considerations for ONT development, and to communicate areas where regulatory clarity and harmonization are most needed. Specifically, these include strategies to assess off-target toxicities, safety pharmacology, general toxicity studies, First-In-Human dose selection, genotoxicity studies, reproductive and developmental toxicity studies, carcinogenicity assessments, and the appropriate use of a surrogate molecule in development. The intended goals of this paper are to provide a means for communicating input towards the ICH process and to provide a resource for assisting with the public review of the draft ICH S13 Guidance.

Chemical pollution can affect ecosystems and human health, highlighting the need for approaches that identify, evaluate, and prioritize emerging chemical risks before they become established public-health issues requiring regulatory actions. This review and perspective article examines methodological components required for Early Warning Systems (EWSs) for chemical risks, with particular attention to the European policy context. It examines methodological components for chemical EWSs rather than proposing a fully implemented system. It considers how state-of-the-art and emerging methods can support signal generation, signal strengthening, prioritization, uncertainty assessment, communication, and follow-up. The reviewed components include matrices and sampling strategies; chemical monitoring, suspect screening, and non-target screening; effect-based methods, New Approach Methodologies, and effect-directed analysis; exposure and hazard modelling; QSAR, read-across, AI-supported and data-mining tools; expert evaluation; and governance processes that link scientific signals to proportionate follow-up. The conceptual workflow is used as an example of how these components may be organized into a signal-handling process, while EU-level developments provide the broader policy and governance context. The actionable value of a chemical EWS does not depend on any single method, but on structured integration of complementary evidence streams. An effective EWS should combine sensitive weak-signal detection with transparent prioritization, explicit uncertainty assessment, FAIR and interoperable data infrastructures, and clearly assigned responsibilities for communication and follow-up.

The Oligonucleotide Nonclinical Working Group (WG) of the European Federation of Pharmaceutical Industries and Associations conducted an industry survey to understand current practices and regulatory expectations for genotoxicity and carcinogenicity assessment of oligonucleotide therapeutics (ONTs), along with historical genotoxicity testing results. The survey, involving 29 pharmaceutical and biotechnology companies, revealed a consistent absence of genotoxicity across a diverse range of oligonucleotide classes and chemistries, consistent with previous observations. Despite the lack of genotoxicity, companies continue to follow standard testing guidelines, with only limited divergence. The survey data support the view that well-established ONT modifications can be considered "precedented," in terms of negligible genotoxic risk. As such, further testing of new ONT candidates containing only precedented modifications is unwarranted, when defined criteria are met. Further, we propose a pathway for novel ONT chemical modifications to achieve precedented status. The survey results also indicate that alternative strategies for carcinogenicity assessment (e.g., single-species testing) can be accepted by regulatory agencies under certain circumstances. Overall, the survey findings underscore the need for a more tailored approach to the nonclinical safety assessment of ONTs, and the WG proposes development of supplementary questions for International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use S2(R1) guidance to reflect this broad industry experience.

Hybridization-dependent off-target (OffT) effects, occurring when oligonucleotides bind via Watson-Crick-Franklin hybridization to unintended RNA transcripts, remain a critical safety concern for oligonucleotide therapeutics (ONTs). Despite the importance of OffT assessment of clinical trial ONT candidates, formal guidelines are lacking, with only brief mentions in Japanese regulatory documents (2020) and US Food and Drug Administration (FDA) recommendations for hepatitis B virus treatments (2022). This article presents updated industry recommendations for assessing OffTs of ONTs, building upon the 2012 Oligonucleotide Safety Working Group (OSWG) recommendations and accounting for recent technological advancements. A new OSWG subcommittee, comprising industry experts in RNase H-dependent and steric blocking antisense oligonucleotides and small interfering RNAs, has developed a comprehensive framework for OffT assessment. The proposed workflow encompasses five key steps: (1) OffT identification through in silico complementarity prediction and transcriptomics analysis, (2) focus on cell types with relevant ONT activity, (3) in vitro verification and margin assessment, (4) risk assessment based on the OffT biological role, and (5) management of unavoidable OffTs. The authors provide detailed considerations for various ONT classes, emphasizing the importance of ONT-specific factors such as chemistry, delivery systems, and tissue distribution in OffT evaluation. The article also explores the potential of machine learning models to enhance OffT prediction and discusses strategies for experimental verification and risk assessment. These updated recommendations aim to improve the safety profile of ONTs entering clinical trials and to manage unavoidable OffTs. The authors hope that these recommendations will serve as a valuable resource for ONT development and for the forthcoming finalization of the FDA draft guidance and the International Council for Harmonization S13 guidance on Nonclinical Safety Assessment of Oligonucleotide-Based Therapeutics.

Humans and wildlife are exposed to a complex mixture of anthropogenic chemicals of which only a few have been subjected to regulations. Chemical risk assessment is currently based on evaluating single chemicals, which is costly, time-consuming, and neglect toxicokinetic and toxicodynamic mixture effects. This study focused on interaction effects on the absorption, distribution, metabolism and excretion (ADME) processes of selected chemicals representing potential modulators of these processes. Adult female zebrafish (Danio rerio) were exposed to selected mixture of 11 chemicals and bioconcentration factors (BCFs) on tissue level were determined for 9 of them: bisphenol A (BPA), bisphenol AF (BPAF), bisphenol Z (BPZ), triclosan, tribromophenol, pentachlorophenol, heptafluorobutyric acid (PFBA), perfluorobutanesulfonic acid (PFBS), and perfluorooctanesulfonic acid (PFOS). Comparison of BCFs of bisphenols obtained from single chemical exposure experiments versus the current study revealed no statistically significant differences (p > 0.05), implying no mixture effects on kinetics of bisphenols at investigated concentrations. The same conclusion was reached using two physiologically based kinetic (PBK) models, developed for individual bisphenols and per- and polyfluoroalkyl substances (PFAS), showing good model fit for BPA, BPZ, BPAF, and PFOS. To simulate exposure scenarios where kinetic interaction effects may occur through competitive protein binding in blood, a new PBK model was developed. Simulations where zebrafish were dosed with BPA and BPZ, individually, and combined with varying levels of PFOS, showed that competitive binding to serum proteins alter tissue levels of bisphenols when levels of PFOS exceeded 1 μg/L. This indicates that chemicals acting in concert could perturb ADME but only at higher levels or in complex mixtures.

Identification of Endocrine-Disrupting Chemicals (EDCs) in a regulatory context requires a high level of evidence. However, lines of evidence (e.g. human, in vivo, in vitro or in silico) are heterogeneous and incomplete for quantifying evidence of the adverse effects and mechanisms involved. To date, for the regulatory appraisal of metabolism-disrupting chemicals (MDCs), no harmonised guidance to assess the weight of evidence has been developed at the EU or international level. To explore how to develop this, we applied a formal Expert Knowledge Elicitation (EKE) approach within the European GOLIATH project. EKE captures expert judgment in a quantitative manner and provides an estimate of uncertainty of the final opinion. As a proof of principle, we selected one suspected MDC -triphenyl phosphate (TPP) - based on its related adverse endpoints (obesity/adipogenicity) relevant to metabolic disruption and a putative Molecular Initiating Event (MIE): activation of peroxisome proliferator activated receptor gamma (PPARγ). We conducted a systematic literature review and assessed the quality of the lines of evidence with two independent groups of experts within GOLIATH, with the objective of categorising the metabolic disruption properties of TPP, by applying an EKE approach. Having followed the entire process separately, both groups arrived at the same conclusion, designating TPP as a “suspected MDC” with an overall quantitative agreement exceeding 85%, indicating robust reproducibility. The EKE method provides to be an important way to bring together scientists with diverse expertise and is recommended for future work in this area.

Pharmacokinetics (PK) of antisense oligonucleotides (ASOs) is characterized by rapid distribution from plasma to tissue and slow terminal plasma elimination driven by re-distribution from tissue. Quantitative understanding of tissue PK and RNA knockdown for various ASO chemistries, conjugations, and administration routes is critical for successful drug discovery. Here, we report concentration-time and RNA knockdown profiles for a gapmer ASO with locked nucleic acid ribose chemistry in mouse liver, kidney, heart, and lung after subcutaneous and intratracheal administration. Additionally, the same ASO with liver targeting conjugation (galactosamine-N-acetyl) is evaluated for subcutaneous administration. Data indicate that exposure and knockdown differ between tissues and strongly depend on administration route and conjugation. In a second study, we show that tissue PK is similar between the three different ribose chemistries locked nucleic acid, constrained ethyl and 2'-O-methoxyethyl, both after subcutaneous and intratracheal administration. Further, we show that the half-life in mouse liver may vary with ASO sequence. Finally, we report less than dose-proportional increase in liver concentration in the dose range of 3-30 μmol/kg. Overall, our studies contribute pivotal data to support design and interpretation of ASO in vivo studies, thereby increasing the probability of delivering novel ASO therapies to patients.

BACKGROUND:Polychlorinated alkanes (PCAs) constitute a large group of individual congeners originating from commercial chlorinated paraffin (CP) products with carbon chain lengths of PCAs-C10-13, PCAs-C14-17, and PCAs-C18-32, occasionally containing PCAs-C6-9 impurities. The extensive use of CPs has led to global environmental pollution of PCAs. This study aimed to quantify PCAs in paired serum and breast milk of lactating Swedish mothers, exploring their concentration relationship. METHODS:Twenty-five paired samples of mothers' blood serum and breast milk were analysed and concentrations were determined for PCAs C6-32 and compared to 4,4'-DDE, the PCB congener 2,2',4,4',5,5'-hexachlorobiphenyl (CB-153), and hexachlorobenzene (HCB). RESULTS:The median concentrations of PCAs-C6-9, PCAs-C10-13, PCAs-C14-17, PCAs-C18-32 and ΣPCAs in serum were 14, 790, 520, 16 and 1350 ng/g lipid weight (lw), respectively, and in breast milk 0.84, 36, 63, 6.0 and 107 ng/g lw. Levels of 4,4'-DDE, CB-153 and HCB were comparable in the two matrices, serum and breast milk at 17, 12 and 4.9 ng/g lw. The results show significant differences of PCAs-C10-13 and PCAs-C14-17 in breast milk with 22- and 6.2-times lower lw-based concentrations than those measured in serum. On wet weight the differences serum/breast milk ratios of PCAs-C6-9, PCAs-C10-13, PCAs-C14-17, PCAs-C18-32 and ΣPCAs were 1.7, 3.2, 1.0, 0.4 and 1.6, respectively, while the ratio for 4,4'-DDE, CB-153 and HCB were each close to 0.1. CONCLUSION:Swedish lactating mothers had high serum concentrations of PCAs-C10-13 and PCAs-C14-17, with the ΣPCAs median serum concentration of 1350 ng/g lw. The breast milk concentration, although considerably lower at 107 ng/g lw, still surpassed those of 4,4'-DDE, CB-153 and HCB, suggesting an exposure risk of infants to PCAs. The variation in blood and breast milk accumulation between PCAs and studied legacy POPs, is rarely discussed but warrants further studies on partitioning properties as well as associated toxicological implications.

Materials in car cabins contain performance-enhancing semi-volatile organic compounds (SVOCs). As these SVOCs are not chemically bound to the materials, they can emit from the materials at slow rates to the surrounding, causing human exposure. This study aimed at increasing the understanding on abundance of SVOCs in car cabins by studying 18 potential endocrine disrupting chemicals in car cabin air (gas phase and airborne particles) and dust. We also studied how levels of these chemicals varied by temperature inside the car cabin along with ventilation settings, relevant to human exposure. A positive correlation was observed between temperature and SVOC concentration in both the gas and the particle phase, where average gas phase levels at 80 °C were a factor of 18-16,000 higher than average levels at 25 °C, while average particle phase levels were a factor of 4.6-40,000 higher for the studied substances. This study also showed that levels were below the limit of detection for several SVOCs during realistic driving conditions, i.e., with the ventilation activated. To limit human exposure to SVOCs in car cabins, it is recommended to ventilate a warm car before entering and have the ventilation on during driving, as both temperature and ventilation have a significant impact on SVOC levels.

Innovative tools suitable for chemical risk assessment are being developed in numerous domains, such as non-target chemical analysis, omics, and computational approaches. These methods will also be critical components in an efficient early warning system (EWS) for the identification of potentially hazardous chemicals. Much knowledge is missing for current use chemicals and thus computational methodologies complemented with fast screening techniques will be critical. This paper reviews current computational tools, emphasizing those that are accessible and suitable for the screening of new and emerging risk chemicals (NERCs). The initial step in a computational EWS is an automatic and systematic search for NERCs in literature and database sources including grey literature, patents, experimental data, and various inventories. This step aims at reaching curated molecular structure data along with existing exposure and hazard data. Next, a parallel assessment of exposure and effects will be performed, which will input information into the weighting of an overall hazard score and, finally, the identification of a potential NERC. Several challenges are identified and discussed, such as the integration and scoring of several types of hazard data, ranging from chemical fate and distribution to subtle impacts in specific species and tissues. To conclude, there are many computational systems, and these can be used as a basis for an integrated computational EWS workflow that identifies NERCs automatically.

AbstractEarly identification of new and emerging risk chemicals (NERCs) is critical in protecting human and environmental health while chemical invention and production is growing on a global market. Chemicals market data is information on the production, import, and use of chemicals in materials and products. By integration of chemicals market data with suspect screening strategies NERCs could potentially be detected early. In silico tools play an important role in this integration to identify blind spots in current analytical approaches and in identification of the potentially most hazardous chemicals. This chapter starts with a brief presentation of the term “chemicals market data.” The integrated approach is then presented in three steps: (1) Data collection and curation, (2) Scoring, ranking, and filtering, and (3) Suspect screening. Each step is first presented conceptually and then exemplified with use cases from the authors. The use of chemicals market data provides a solid basis for identification of true NERCs with confidence, and true and false negative findings can more confidently be distinguished. Chemicals market data should be provided to authorities and researchers so that early warning systems for NERCs can be installed and analytical blind spots identified and addressed.

Per- and polyfluoroalkyl substances (PFAS) are ubiquitously distributed in the aquatic environment. They include persistent, mobile, bioaccumulative, and toxic chemicals and it is therefore critical to increase our understanding on their adsorption, distribution, metabolism, excretion (ADME). The current study focused on uptake of seven emerging PFAS in zebrafish (Danio rerio) and their potential maternal transfer. In addition, we aimed at increasing our understanding on mixture effects on ADME by developing a physiologically based kinetic (PBK) model capable of handling co-exposure scenarios of any number of chemicals. All studied chemicals were taken up in the fish to varying degrees, whereas only perfluorononanoate (PFNA) and perfluorooctanoate (PFOA) were quantified in all analysed tissues. Perfluorooctane sulfonamide (FOSA) was measured at concerningly high concentrations in the brain (Cmax over 15 μg/g) but also in the liver and ovaries. All studied PFAS were maternally transferred to the eggs, with FOSA and 6:2 perfluorooctane sulfonate (6,2 FTSA) showing significant (p < 0.02) signs of elimination from the embryos during the first 6 days of development, while perfluorobutane sulfonate (PFBS), PFNA, and perfluorohexane sulfonate (PFHxS) were not eliminated in embryos during this time-frame. The mixture PBK model resulted in >85 % of predictions within a 10-fold error and 60 % of predictions within a 3-fold error. At studied levels of PFAS exposure, competitive binding was not a critical factor for PFAS kinetics. Gill surface pH influenced uptake for some carboxylates but not the sulfonates. The developed PBK model provides an important tool in understanding kinetics under complex mixture scenarios and this use of New Approach Methodologies (NAMs) is critical in future risk assessment of chemicals and early warning systems.

Zebrafish embryos (ZFE) is a widely used model organism, employed in various research fields including toxicology to assess e.g., developmental toxicity and endocrine disruption. Variation in effects between chemicals are difficult to compare using nominal dose as toxicokinetic properties may vary. Toxicokinetic (TK) modeling is a means to estimate internal exposure concentration or dose at target and to enable extrapolation between experimental conditions and species, thereby improving hazard assessment of potential pollutants. In this study we advance currently existing TK models for ZFE with physiological ZFE parameters and novel experimental bisphenol data, a class of chemicals with suspected endocrine activity. We developed a five-compartment model consisting of water, plastic, chorion, yolk sack and embryo in which surface area and volume changes as well as the processes of biotransformation and blood circulation influence mass fluxes. For model training and validation, we measured internal concentrations in ZFE exposed individually to BPA, bisphenol AF (BPAF) and Z (BPZ). Bayesian inference was applied for parameter calibration based on the training data set of BPZ. The calibrated TK model predicted internal ZFE concentrations of the majority of external test data within a 5-fold error and half of the data within a 2-fold error for bisphenols A, AF, F, and tetrabromo bisphenol A (TBBPA). We used the developed model to rank the hazard of seven bisphenols based on predicted internal concentrations and measured in vitro estrogenicity. This ranking indicated a higher hazard for BPAF, BPZ, bisphenol B and C (BPB, BPC) than for BPA.

Receptor-mediated molecular initiating events (MIEs) and their relevance in endocrine activity (EA) have been highlighted in literature. More than 15 receptors have been associated with neurodevelopmental adversity and metabolic disruption. MIEs describe chemical interactions with defined biological outcomes, a relationship that could be described with quantitative structure-activity relationship (QSAR) models. QSAR uncertainty can be assessed using the conformal prediction (CP) framework, which provides similarity (i.e., nonconformity) scores relative to the defined classes per prediction. CP calibration can indirectly mitigate data imbalance during model development, and the nonconformity scores serve as intrinsic measures of chemical applicability domain assessment during screening. The focus of this work was to propose an in silico predictive strategy for EA. First, 23 QSAR models for MIEs associated with EA were developed using high-throughput data for 14 receptors. To handle the data imbalance, five protocols were compared, and CP provided the most balanced class definition. Second, the developed QSAR models were applied to a large data set (∼55,000 chemicals), comprising chemicals representative of potential risk for human exposure. Using CP, it was possible to assess the uncertainty of the screening results and identify model strengths and out of domain chemicals. Last, two clustering methods, t-distributed stochastic neighbor embedding and Tanimoto similarity, were used to identify compounds with potential EA using known endocrine disruptors as reference. The cluster overlap between methods produced 23 chemicals with suspected or demonstrated EA potential. The presented models could be utilized for first-tier screening and identification of compounds with potential biological activity across the studied MIEs.

Prenatal exposure to a mixture (MIX N) of eight endocrine-disrupting chemicals has been associated with language delay in children in a Swedish pregnancy cohort. A novel approach was proposed linking this epidemiological association with experimental evidence, where the effect of MIX N on thyroid hormone signaling was assessed using the Xenopus eleuthero-embryonic thyroid assay (XETA OECD TG248). From this experimental data, a point of departure (PoD) was derived based on OECD guidance. Our aim in the current study was to use updated toxicokinetic models to compare exposures of women of reproductive age in the US population to MIX N using a Similar Mixture Approach (SMACH). Based on our findings, 66% of women of reproductive age in the US (roughly 38 million women) had exposures sufficiently similar to MIX N. For this subset, a Similar Mixture Risk Index (SMRIHI) was calculated comparing their exposures to the PoD. Women with SMRIHI > 1 represent 1.1 million women of reproductive age. Older women, Mexican American and other/multi race women were less likely to have high SMRIHI values compared to Non-Hispanic White women. These findings indicate that a reference mixture of chemicals identified in a Swedish cohort-and tested in an experimental model for establishment of (PoDs)-is also of health relevance in a US population.

The omnipresence of microplastics (MPs) across Earth's surface has raised concerns about their environmental impact and created an urgent need for methods to identify them in complex soil and sedimentary matrices. However, detecting MPs in the O horizons of soils is difficult because plastic polymers share many physical and chemical properties with natural soil organic matter (SOM). In this study, we assessed whether sodium hypochlorite (NaOCl), a reagent that can oxidize SOM and simultaneously preserve mineral constituents, can be used for MP analysis and characterization in soil environments. In addition, we scrutinized how factors such as MP size, polymer type, extraction methods, and soil matrix affect the recovery of microplastic particles. We used both hydrophobic and density-dependent separation methods to assess the effects of our oxidation treatment on the recovery of MP. We observed that NaOCl effectively removed SOM without greatly altering the surface properties of resistant MP polymers (polypropylene, polylactic acid, low-density polyethylene, and polyethylene terephthalate), which were characterized using scanning electron microscopy and Fourier-transform infrared spectroscopy after SOM removal. The NaOCl treatment caused some chlorination and formation of additional C-OH bonds on polymer surfaces, which likely contributed to the reduced efficiency of the hydrophobic-based (oil) extraction. We conclude that NaOCl treatment can improve detection of MPs in SOM-rich soil and that recovery of MPs from soils is influenced by MP size, polymer type, extraction method, and soil type, which makes it challenging to develop a universal analytical method.

The nucleic acid therapeutics field has made tremendous progress in the past decades. Continuous advances in chemistry and design have led to many successful clinical applications, eliciting even more interest from researchers including both academic groups and drug development companies. Many preclinical studies in the field focus on improving the delivery of antisense oligonucleotide drugs (ONDs) and/or assessing their efficacy in target tissues, often neglecting the evaluation of toxicity, at least in early phases of development. A series of consensus recommendations regarding regulatory considerations and expectations have been generated by the Oligonucleotide Safety Working Group and the Japanese Research Working Group for the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use S6 and Related Issues (WGS6) in several white papers. However, safety aspects should also be kept in sight in earlier phases while screening and designing OND to avoid subsequent failure in the development phase. Experts and members of the network "DARTER," a COST Action funded by the Cooperation in Science and Technology of the EU, have utilized their collective experience working with OND, as well as their insights into OND-mediated toxicities, to generate a series of consensus recommendations to assess OND toxicity in early stages of preclinical research. In the past few years, several publications have described predictive assays, which can be used to assess OND-mediated toxicity in vitro or ex vivo to filter out potential toxic candidates before moving to in vivo phases of preclinical development, that is, animal toxicity studies. These assays also have the potential to provide translational insight since they allow a safety evaluation in human in vitro systems. Yet, small preliminary in vivo studies should also be considered to complement this early assessment. In this study, we summarize the state of the art and provide guidelines and recommendations on the different tests available for these early stage preclinical assessments.