Use of in vitro methods combined with in silico analysis to identify potential skin sensitizers in the Tox21 10K compound library.

Introduction: Skin sensitization, which leads to allergic contact dermatitis, is a key toxicological endpoint with high occupational and consumer prevalence. This study optimized several in vitro assays listed in OECD skin sensitization test guidelines for use on a quantitative high-throughput screening (qHTS) platform and performed in silico model predictions to assess the skin sensitization potential of prioritized compounds from the Tox21 10K compound library. Methods: First, we screened the entire Tox21 10K compound library using a qHTS KeratinoSensTM (KS) assay and built a quantitative structure-activity relationship (QSAR) model based on the KS results. From the qHTS KS screening results, we prioritized 288 compounds to cover a wide range of structural chemotypes and tested them in the solid phase extraction-tandem mass spectrometry (SPE-MS/MS) direct peptide reactivity assay (DPRA), IL-8 homogeneous time-resolved fluorescence (HTRF) assay, CD86 and CD54 surface expression in THP1 cells, and predicted in silico sensitization potential using the OECD QSAR Toolbox (v4.5). Results: Interpreting tiered qHTS datasets using a defined approach showed the effectiveness and efficiency of in vitro methods. We selected structural chemotypes to present this diverse chemical collection and to explore previously unidentified structural contributions to sensitization potential. Discussion: Here, we provide a skin sensitization dataset of unprecedented size, along with associated tools, and analysis designed to support chemical assessments.

Applying a next generation risk assessment framework for skin sensitisation to inconsistent new approach methodology information.

Cosmetic products must be safe for their intended use. Regulatory bans on animal testing for new ingredients have resulted in a shift towards the use of new approach methodologies (NAMs) such as in silico predictions and in chemico / in vitro data. Defined approaches (DAs) have been developed to interpret combinations of NAMs to provide information on skin sensitization hazard and potency, three having been adopted within OECD Test Guideline 497. However, the challenge remains as to how DAs can be used to derive a quantitative point of departure for use in next generation risk assessment (NGRA). Here we provide an update to our previously published NGRA framework and present two hypothetical consumer risk assessment scenarios (rinse-off and leave-on) on one case study ingredient. Diethanolamine (DEA) was selected as the case study ingredient based on the existing NAM information demonstrating differences with respect to the outcomes from in silico predictions and in chemico / in vitro data. Seven DAs were applied, and these differences resulted in divergent DA outcomes and reduced confidence with respect to the hazard potential and potency predictions. Risk assessment conclusion for the rinse-off exposure led to an overall decision of safe for all applied DAs. Risk assessment conclusion for the higher leave-on exposure was safe when based on some DAs but unsafe based on others. The reasons for this were evaluated as well as the inherent uncertainty from the use of each NAM and DA in the risk assessment, enabling further refinement of our NGRA framework.

Development of a Defined Approach for Eye hazard identification of chemicals having surfactant properties according to the three UN GHS categories.

The purpose of this study was to develop a defined approach (DA) for eye hazard identification according to the three UN GHS categories for surfactants (DASF). The DASF is based on a combination of Reconstructed human Cornea-like Epithelium test methods (OECD TG 492; EpiOcular™ EIT and SkinEthic™ HCE EIT) and the modified Short Time Exposure (STE) test method (0.5% concentration of the test substance after a 5-min exposure). DASF performance was assessed by comparing the prediction results with the historical in vivo data classification and against the criteria established by the OECD expert group on eye/skin. The DASF yielded a balanced accuracy of 80.5% and 90.9% of Cat. 1 (N = 22), 75.0% of Cat. 2 (N = 8), and 75.5% of No Cat. (N = 17) surfactants were correctly predicted. The percentage of mispredictions was below the established maximum values except for in vivo No Cat. surfactants that were over-predicted as Cat. 1 (5.6%, N = 17), with a maximum value set at 5%. The percentage of correct predictions did meet the minimum performance values of 75% Cat. 1, 50% Cat. 2, and 70% No Cat. established by the OECD experts. The DASF has shown to be successful for eye hazard identification of surfactants.

Incorporating integrated testing strategy (ITSv1) defined approach into read-across (RAx) in predicting skin sensitization potency: ITSv1-based RAx.

Recently, due to regulatory and ethical demands, new approach methodologies (NAMs), defined approaches (DAs), and read-across (RAx) have been used in the risk assessment of skin sensitization. Integrated testing strategy (ITS)v1 DA, adopted in OECD Guideline No. 497, can be used for skin sensitization potency categorization. However, ITSv1 DA alone is not used for further refinement of the potency prediction based on EC3 (the estimated concentration that produces a stimulation index of 3 in murine local lymph node assay) values. Moreover, there is no explicit approach to incorporating NAM/DA data into RAx to fill the data gap of EC3 values with high confidence. This study developed a strategy incorporating ITSv1 DA into RAx to predict skin sensitization potency: ITSv1-based RAx. To examine the reliability of this novel strategy, a case study with lilial, a fragrance material, was performed. Based on ITSv1-based RAx, the skin sensitization potency of lilial was determined by extrapolating the EC3 value of 9.5% for the suitable analogue bourgeonal, which was close to the historical EC3 value of 8.6%. The result suggested that the strategy can refine the prediction of EC3 values with high confidence and be useful for the risk assessment of skin sensitization.

Plant extracts, polymers and new approach methods: Practical experience with skin sensitization assessment.

Over the last decade, research into methodologies to identify skin sensitization hazards has led to the adoption of several non-animal methods as OECD test guidelines. However, predictive accuracy beyond the chemical domains of the individual validation studies remains largely untested. In the present study, skin sensitization test results from in vitro and in chemico methods for 12 plant extracts and 15 polymeric materials are reported and compared to available in vivo skin sensitization data. Eight plant extracts were tested in the DPRA and h-CLAT, with the 2 out of 3 approach resulting in a balanced accuracy of 50%. The balanced accuracy for the 11 plant extracts assessed in the SENS-IS was 88%. Excluding 5 polymers inconclusive in vitro, the remainder, assessed using the 2 out of 3 approach, resulted in 63% balanced accuracy. The SENS-IS method, excluding one polymeric material due to technical inapplicability, showed 68% balanced accuracy. Although based on limited numbers, the results presented here indicate that some substance subgroups may not be in the applicability domains of the method used and careful analysis is required before positive or negative results can be accepted.

Decision making in next generation risk assessment for skin allergy: Using historical clinical experience to benchmark risk.

Our aim is to develop and apply next generation approaches to skin allergy risk assessment that do not require new animal test data and better quantify uncertainties. Quantitative risk assessment for skin sensitisation uses safety assessment factors to extrapolate from the point of departure to an acceptable human exposure level. It is currently unclear whether these safety assessment factors are appropriate when using non-animal test data to derive a point-of departure. Our skin allergy risk assessment model Defined Approach uses Bayesian statistics to infer a human-relevant metric of sensitiser potency with explicit quantification of uncertainty, using any combination of human repeat insult patch test, local lymph node assay, direct peptide reactivity assay, KeratinoSens™, h-CLAT or U-SENS™ data. Here we describe the incorporation of benchmark exposures pertaining to use of consumer products with clinical data supporting a high/low risk categorisation for skin sensitisation. Margins-of-exposure (potency estimate to consumer exposure level ratio) are regressed against the benchmark risk classifications, enabling derivation of a risk metric defined as the probability that an exposure is low risk. This approach circumvents the use of safety assessment factors and provides a simple and transparent mechanism whereby clinical experience can directly feed-back into risk assessment decisions.

A development of a graph-based ensemble machine learning model for skin sensitization hazard and potency assessment.

Many defined approaches (DAs) for skin sensitization assessment based on the adverse outcome pathway (AOP) have been developed to replace animal testing because the European Union has banned animal testing for cosmetic ingredients. Several DAs have demonstrated that machine learning models are beneficial. In this study, we have developed an ensemble prediction model utilizing the graph convolutional network (GCN) and machine learning approach to assess skin sensitization. The model integrates in silico parameters and data from alternatives to animal testing of well-defined AOP to improve DA predictivity. Multiple ensemble models were created using the probability produced by the GCN with six physicochemical properties, direct peptide reactivity assay, KeratinoSens™, and human cell line activation test (h-CLAT), using a multilayer perceptron approach. Models were evaluated by predicting the testing set's human hazard class and three potency classes (strong, weak, and non-sensitizer). When the GCN feature was used, 11 models out of 16 candidates showed the same or improved accuracy in the testing set. The ensemble model with the feature set of GCN, KeratinoSens™, and h-CLAT produced the best results with an accuracy of 88% for assessing human hazards. The best three-class potency model was created with the feature set of GCN and all three assays, resulting in 64% accuracy. These results from the ensemble approach indicate that the addition of the GCN feature could provide an improved predictivity of skin sensitization hazard and potency assessment.

Integrated skin sensitization assessment based on OECD methods (II): Hazard and potency by combining kinetic peptide reactivity and the "2 out of 3" Defined Approach.

Depending on regulatory requirements, the skin sensitization risk for new chemicals with potential consumer skin contact must be assessed by experimental testing by (i) binary hazard assessment to identify sensitizers, (ii) subclassification of sensitizers according to the Global Harmonized System (GHS), and (iii) derivation of a point of departure (PoD) for risk assessment. The Organisation for Economic Co-operation and Development (OECD) recently published a test guideline incorporating the "2 out of 3" defined approach (2o3 DA) for skin sensitization hazard assessment and added the kinetic direct peptide reactivity assay (kDPRA) as a stand-alone test guideline method for GHS subclassification. The 2o3 DA requires that at least two in vitro tests are conducted. The cell-based tests and the kDPRA generate, next to a binary outcome with a fixed threshold, continuous concentration-response data, which can be used in quantitative regression models to derive a PoD. The sequence of testing for the 2o3 DA is flexible. Here we compare different testing sequences and how they can be combined with kDPRA data to provide a PoD in parallel to hazard identification (hazard ID) and GHS subclassification. A set of 188 chemicals with available in vitro data was evaluated for the final PoD using these dif-ferent testing sequences. The results indicate that testing can start with DPRA / kDPRA and either of the cell-based assays, and that testing can stop after two congruent tests without major impact on the final PoD for chemicals within the applica-bility domain of the kDPRA.

A triangular approach for the validation of new approach methods for skin sensitization.

The availability of reference data is a key requirement for the development of new approach methods (NAM), i.e., in vitro, in chemico and in silico methods and integrated approaches, like defined approaches (DA), which combine these data sources. Reference data are of even greater importance for regulatory acceptance. In contrast to most other adverse effects, human skin sensitization data on many chemicals are available, next to data from animal studies, such as the local lymph node assay (LLNA). Skin sensitization NAM data can therefore be compared to different reference datasets. Recent publications and validation at the OECD focused on human and LLNA reference data. The "2 out of 3" DA (2o3 DA) is the first DA for skin sensitization solely based on experimental data from validated tests and was recently adopted as an OECD test guideline. Here we review the predictivity of the 2o3 DA on multiple human and LLNA reference datasets. Concomitantly, we compare the predictivity of the LLNA for human data within the same datasets. Comparing predictivity of methods not only bilaterally (NAM or DA vs. animal method) but including human data in a triangle "NAM data ­ animal data ­ human data" offers a comprehensive assessment of the NAM's and DA's predictivity. In all these assessments, the 2o3 DA was superior to the LLNA in predicting human skin sensitization hazard. This highlights the importance of a holistic view of reference data instead of limiting validation of NAMs and DAs to data from a single animal test only.

Assessing chemical carcinogenicity: hazard identification, classification, and risk assessment. Insight from a Toxicology Forum state-of-the-science workshop.

The Toxicology Forum convened an international state-of-the-science workshop Assessing Chemical Carcinogenicity: Hazard Identification, Classification, and Risk Assessment in December 2020. Challenges related to assessing chemical carcinogenicity were organized under the topics of (1) problem formulation; (2) modes-of-action; (3) dose-response assessment; and (4) the use of new approach methodologies (NAMs). Key topics included the mechanisms of genotoxic and non-genotoxic carcinogenicity and how these in conjunction with consideration of exposure conditions might inform dose-response assessments and an overall risk assessment; approaches to evaluate the human relevance of modes-of-action observed in rodent studies; and the characterization of uncertainties. While the scientific limitations of the traditional rodent chronic bioassay were widely acknowledged, knowledge gaps that need to be overcome to facilitate the further development and uptake of NAMs were also identified. Since one single NAM is unlikely to replace the bioassay, activities to combine NAMs into integrated approaches for testing and assessment, or preferably into defined approaches for testing and assessment that include data interpretation procedures, were identified as urgent research needs. In addition, adverse outcome pathway networks can provide a framework for organizing the available evidence/data for assessing chemical carcinogenicity. Since a formally accepted decision tree to guide use of the best and most current science to advance carcinogenicity risk assessment is currently unavailable, a Decision Matrix for carcinogenicity assessment could be useful. The workshop organizers developed and presented a decision matrix to be considered within a carcinogenicity hazard and risk assessment that is offered in tabular form.

Skin sensitization in silico protocol.

The assessment of skin sensitization has evolved over the past few years to include in vitro assessments of key events along the adverse outcome pathway and opportunistically capitalize on the strengths of in silico methods to support a weight of evidence assessment without conducting a test in animals. While in silico methods vary greatly in their purpose and format; there is a need to standardize the underlying principles on which such models are developed and to make transparent the implications for the uncertainty in the overall assessment. In this contribution, the relationship between skin sensitization relevant effects, mechanisms, and endpoints are built into a hazard assessment framework. Based on the relevance of the mechanisms and effects as well as the strengths and limitations of the experimental systems used to identify them, rules and principles are defined for deriving skin sensitization in silico assessments. Further, the assignments of reliability and confidence scores that reflect the overall strength of the assessment are discussed. This skin sensitization protocol supports the implementation and acceptance of in silico approaches for the prediction of skin sensitization.

Replacing the refinement for skin sensitization testing: Considerations to the implementation of adverse outcome pathway (AOP)-based defined approaches (DA) in OECD guidelines.

While single non-animal methods have been adopted in OECD test guidelines, combinations of methods (so called defined approaches, DA) are not. Hardly any animal study can be replaced by a single non-animal method, rather DA are needed. The OECD published the Adverse Outcome Pathway (AOP) on skin sensitization in 2012 and is currently discussing the implementation of DA into a guideline. Obviously, it takes thorough considerations and evaluations to validate such DA. Currently we see four preconditions for a proper and expedient implementation of DA in a guideline: (i) The reference data should be selected to allow meaningful evaluations and must not replicate the limitations of the murine local lymph node assay (LLNA) (ii) Methods and prediction models should be validated before they are used in an OECD-adopted DA, (iii) An OECD-adopted DA should follow the respective AOP and (iv) acknowledge regulatory needs and successful toxicological practice. These points still need to be considered in the current discussion at the OECD. A guideline for skin sensitization DA is setting the scene for regulatory acceptance of all new approaches (for any toxicological endpoint) in the future. In this commentary, we are expounding these preconditions to allow a scientifically valid and sustainable application of modern (no-animal) approaches in regulatory toxicology.

Assessment of a defined approach based on a stacking prediction model to identify skin sensitization hazard.

Skin sensitization is an important toxicological endpoint in the safety assessment of chemicals and cosmetic ingredients. Driven by ethical considerations and European Union (EU) legislation, its assessment has progressed from the reliance on traditional animal models to the use of non-animal test methods. It is generally accepted that the assessment of skin sensitization requires the integration of various non-animal test methods in defined approaches (DAs), to cover the mechanistic key events of the adverse outcomes pathway (AOP) (OECD, 2014). Several case studies for DAs predicting skin sensitization hazard or potency have been submitted to the OECD, including a stacking meta-model developed by L'Oréal Research & Innovation (OECD, 2017b; Del Bufalo et al., 2018; Noçairi et al., 2016). The present study evaluated the predictive performance of the defined approach integrating a stacking meta-model incorporating in silico, in chemico and in vitro assays, using the Cosmetics Europe (CE) skin sensitization database. Based on the optimized prediction cut-offs, the defined approach provided a hazard prediction for 97 chemicals with a sensitivity of 91%, a specificity of 76% and accuracy of 86% (kappa of 0.67) against human skin sensitization hazard data and a sensitivity of 85%, specificity of 91% and accuracy of 87% (kappa of 0.67) against Local Lymph Node Assay (LLNA) hazard data. A comparison of the in vivo LLNA with human hazard data for the same 97 chemicals showed a sensitivity of 92%, specificity of 51% and accuracy of 78% (kappa of 0.48). Thus, the defined approach showed a higher degree of concordance, as compared to the LLNA for predicting human skin sensitization hazard. Moreover, a comparison with the six DAs selected for evaluation of their predictivity in the study by Kleinstreuer et al. (2018) showed a similar high accuracy of 86% for 97 overlapping chemicals. The next step will be an independent evaluation of the DA for its integration in the performances based test guidelines (PBTG) for skin sensitization.

Development of a defined approach for eye irritation or serious eye damage for neat liquids based on cosmetics Europe analysis of in vitro RhCE and BCOP test methods.

The focus of Cosmetics Europe's ocular toxicity programme is on development of testing strategies and defined approaches for identification of ocular effects of chemicals in the context of OECD's Guidance Document on an Integrated Approach on Testing and Assessment (IATA) for Serious Eye Damage and Eye Irritation. Cosmetics Europe created a comprehensive database of chemicals for which in vitro data are available with corresponding historical in vivo Draize eye data and physicochemical properties. This database allowed further exploration of the initially proposed strategies from the CON4EI project and to identify opportunities for refinement. One key outcome of this project is that combining in vitro test methods (RhCE and BCOP LLBO) with physicochemical properties in a two-step Bottom-Up approach applicable to neat liquids, resulted in an improvement of the specificity, without reducing the sensitivity, when compared to the combination of in vitro methods alone. The Bottom-Up approach proposed here for neat liquids correctly predicted 58.3% (EpiOcular™ EIT followed by BCOP LLBO) to 62.6% (SkinEthic™ HCE EIT followed by BCOP LLBO) of No Cat., 59.1% to 68.7% of Cat. 2, and 76.5% of Cat. 1. Incorporating specific physicochemical properties with this Bottom-Up approach increased the correct identification of No Cat. neat liquids to between 72.7% and 79.7%.

Development of a defined approach for eye irritation or serious eye damage for liquids, neat and in dilution, based on cosmetics Europe analysis of in vitro STE and BCOP test methods.

The focus of Cosmetics Europe's programme on serious eye damage/eye irritation is on development of testing strategies and defined approaches for identification of ocular effects of chemicals in the context of OECD's Guidance Document on an Integrated Approach on Testing and Assessment (IATA) for Serious Eye Damage and Eye Irritation. Cosmetics Europe created a comprehensive database of chemicals for which in vitro data are available with corresponding historical in vivo Draize eye data. This database allowed further exploration of the initially proposed strategies from the CON4EI project and to identify opportunities for refinement. The current analysis focused on the development of a defined approach, applicable to liquid non-surfactant chemicals, neat and in dilution, that can distinguish between the three UN GHS categories (Cat. 1, Cat. 2, and No Cat.). Combining the modified-protocol Short Time Exposure (STE) test method (OECD TG 491 with extension to highly volatile substances) with the Bovine Corneal Opacity and Permeability Laser Light-Based Opacitometer (BCOP LLBO) test method in a Bottom-Up approach identified 81.2% Cat. 1, 56.3% Cat. 2, and 85.3% No. Cat correctly, with an NPV of 96.7% and a PPV of 68.6%. Therefore, the performance of the defined approach was better than the standalone test methods.

A defined approach for predicting skin sensitisation hazard and potency based on the guided integration of in silico, in chemico and in vitro data using exclusion criteria.

A decision tree-based defined approach (DA) has been designed using exclusion criteria based on applicability domain knowledge of in chemico/in vitro information sources covering key events 1-3 in the skin sensitisation adverse outcome pathway and an in silico tool predicting the adverse outcome (Derek Nexus). The hypothesis is that using exclusion criteria to de-prioritise less applicable assays and/or in silico outcomes produces a rational, transparent, and reliable DA for the prediction of skin sensitisation potential. Five exclusion criteria have been established: Derek Nexus reasoning level, Derek Nexus negative prediction, metabolism, lipophilicity, and lysine-reactivity. These are used to prioritise the most suitable information sources for a given chemical and results from which are used in a '2 out of 3' approach to provide a prediction of hazard. A potency category (and corresponding GHS classification) is then assigned using a k-Nearest Neighbours model containing human and LLNA data. The DA correctly identified the hazard (sensitiser/non-sensitiser) for 85% and 86% of a dataset with reference LLNA and human data. The correct potency category was identified for 59% and 68% of chemicals, and the GHS classification accurately predicted for 73% and 76% with reference LLNA and human data, respectively.

Non-animal methods to predict skin sensitization (I): the Cosmetics Europe database.

Cosmetics Europe, the European Trade Association for the cosmetics and personal care industry, is conducting a multi-phase program to develop regulatory accepted, animal-free testing strategies enabling the cosmetics industry to conduct safety assessments. Based on a systematic evaluation of test methods for skin sensitization, five non-animal test methods (DPRA (Direct Peptide Reactivity Assay), KeratinoSensTM, h-CLAT (human cell line activation test), U-SENSTM, SENS-IS) were selected for inclusion in a comprehensive database of 128 substances. Existing data were compiled and completed with newly generated data, the latter amounting to one-third of all data. The database was complemented with human and local lymph node assay (LLNA) reference data, physicochemical properties and use categories, and thoroughly curated. Focused on the availability of human data, the substance selection resulted nevertheless resulted in a high diversity of chemistries in terms of physico-chemical property ranges and use categories. Predictivities of skin sensitization potential and potency, where applicable, were calculated for the LLNA as compared to human data and for the individual test methods compared to both human and LLNA reference data. In addition, various aspects of applicability of the test methods were analyzed. Due to its high level of curation, comprehensiveness, and completeness, we propose our database as a point of reference for the evaluation and development of testing strategies, as done for example in the associated work of Kleinstreuer et al. We encourage the community to use it to meet the challenge of conducting skin sensitization safety assessment without generating new animal data.