Allergic contact dermatitis (ACD) is estimated to constitute about 10-15% of all occupational diseases. Predictive testing to characterise substances for their skin sensitisation potential has historically been based on animal models such as the Local Lymph Node Assay (LLNA) and the Guinea Pig Maximisation Test (GPMT). In recent years, EU regulations, have provided a strong incentive to develop non-animal alternatives. Significant progress has been made in developing and evaluating non-animal test methods. There have been efforts to develop and evaluate the utility of in silico models for skin sensitisation including local and global (Q)SARs as well as expert systems. In this study, we selected three different types of expert systems: VEGA (statistical), Derek Nexus (knowledge based), TIMES-SS (hybrid) and evaluated their performance using 2 large datasets of substances that had been assessed for their skin sensitisation potential in animal models. We considered a model to be successful at predicting skin sensitisation potential if it had at least the same balanced accuracy as the LLNA and the GPMT had in predicting the outcomes of one another, which ranged from 79% to 86% depending on the dataset. We found that none of the expert systems evaluated was able to achieve such a high balanced accuracy in their global predictions, with balanced accuracies ranging from 56% to 65%. However, for substances within the domain of TIMES-SS, balanced accuracies were found to be 79% and 82%, for the two datasets, in line with the animal data. The expert systems evaluated could be extended in light of the additional data collected as part of this study. The incorrect predictions offer new insights for how the existing alerts within these expert systems could be refined. These datasets also offer exciting opportunities for the development of new models. This dataset is associated with the following publication: Fitzpatrick, J., D. Roberts, and G. Patlewicz. (SAR and QSAR in ENVIRONMENTAL RESEARCH) An evaluation of selected (Q)SARs/expert systems for predicting skin sensitisation potential. SAR AND QSAR IN ENVIRONMENTAL RESEARCH. Taylor & Francis, Inc., Philadelphia, PA, USA, 29(6): 439-468, (2018).

Appendix Skin sensitization data and non‐animal test data for 271 chemicals. This dataset is associated with the following publication: Roberts, D., and G. Patlewicz. Non‐animal assessment of skin sensitization hazard: Is an integrated testing strategy needed, and if so what should be integrated?. JOURNAL OF APPLIED TOXICOLOGY. John Wiley & Sons, Ltd., Indianapolis, IN, USA, 38(1): 41-50, (2017).

Background Allergic Contact Dermatitis (ACD) is regarded as a T-cell-mediated delayed-type hypersensitivity reaction. We studied the kinetics of the expression of CS-1 fibronectin, thymus and activation-regulated chemokine (CCL17/ TARC) and different chemokine receptors (CR) in skin biopsies from individuals suffering from back problems, with the antigen responsible of their contact dermatitis and an irrelevant antigen. Methods Samples were taken at 2, 10, and 48 hours for histological and immunohistochemical studies using monoclonal antibodies against human CS-1 fibronectin, CCL17, CD3, CD68, CD49d, CXCR3, CCR5, and CCR3. Results At positive antigen stimulated sites there was an early expression of CS-1 fibronectin (2 hours), followed by CCL17 and a later accumulation of alplha4/beta1+ (CD49d), CD3+, CD68+, CXCR3+ and CCR5+ mononuclear cells. At 48 hours, approximately 59 % of infiltrating cells were CXCR3+, 42% CCR5+, and only 14 % CCR3+. Conclusions These results showed for the first time a very early expression of CS-1 fibronectin which preceded production of CCL17 in blood endothelial cells (BCEs) from patients' skin with ACD. The role of these molecules in recruitment of monocytes and effector T cells in ACD is discussed.

Data from which figures and table in "A Model for Risk-Based Screening and Prioritization of Human Exposure to Chemicals from Near-Field Sources" were constructed. This dataset is associated with the following publication: Li, L., J. Westgate, L. Hughes, X. Zhang, B. Givehchi, L. Toose, J. Armitage, F. Wania, P. Egeghy, and J. Arnot. A Model for Risk-Based Screening and Prioritization of Human Exposure to Chemicals from Near-Field Sources. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(24): 14235-14244, (2018).

Dataset used to generate tables/figures demonstrating the effects of water disinfection on allergic hypersensitivity and dermal irritation. This dataset is associated with the following publication: Lehmann, D., M. Armstrong, W. Williams, C. Postigo, and J. Simmons. Assessing the skin irritation and sensitizing potential of concentrates of water chlorinated in the presence of iodinated X-ray contrast media. TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 480: 153335, (2022).

Since the publication of the Adverse Outcome Pathway (AOP) for skin sensitization, there have been many efforts to develop systematic approaches to integrate the information generated from different key events for decision making. The types of information characterizing key events in an AOP can be generated from in silico, in chemico, in vitro or in vivo approaches. Integration of this information and interpretation for decision making are known as integrated approaches to testing and assessment or IATA. One such IATA that has been developed was published by Jaworska et al (2013) which describes a Bayesian network model known as ITS-2. The current work evaluated the performance of ITS-2 using a stratified cross validation approach. We also characterized the impact of refinements to the network by replacing the most significant component, the output from a commercial expert system TIMES-SS with structural alert information readily generated from the freely available OECD QSAR Toolbox. Lack of any structural alert flags or TIMES-SS predictions, yielded a sensitization potential prediction of 79% +3%/-4%. If the TIMES-SS prediction was replaced by an indicator for the presence of a structural alert, the network predictivity increased to 84% +2%/-4%, which was only slightly less than found for the original network (89% ±2%). The local applicability domain of the original ITS-2 network was also evaluated using reaction mechanistic domains to better understand what types of chemicals ITS-2 was able to make the best predictions for – i.e. a local validity domain analysis. We ultimately found that the original network was successful at predicting which chemicals would be sensitizers, but not at predicting their relative potency. This dataset is associated with the following publication: Fitzpatrick, J., and G. Patlewicz. (SAR AND QSAR IN ENVIRONMENTAL RESEARCH) Application of IATA - A case study in evaluating the global and local performance of a Bayesian Network model for Skin Sensitization. SAR AND QSAR IN ENVIRONMENTAL RESEARCH. Taylor & Francis, Inc., Philadelphia, PA, USA, 28(4): 297-310, (2017).

Dermal absorption is an important route of exposure that includes pharmaceuticals, consumer products and occupational exposures. "httk" is being developed as a tool to predict internal dose after exposure. The dermal route will be added to this package in order to account for dermal exposure. This dataset is associated with the following publication: Evans, M., T. Moxon, G. Lian, B. Deacon, T. Chen, L. Adams, A. Meade, and J. Wambaugh. A regression analysis using simple descriptors for multiple dermal datasets: Going from individual membranes to the full skin. JOURNAL OF APPLIED TOXICOLOGY. John Wiley & Sons, Ltd., Indianapolis, IN, USA, 43(6): 940-950, (2023).

t is widely accepted that substances that cannot penetrate through the skin will not be sensitizers. LogKow and molecular weight (MW) have been used to set thresholds for sensitization potential. Highly hydrophilic substances e.g. LogKow ≤ 1 are expected not to penetrate effectively to induce sensitization. To investigate whether LogKow >1 is a true requirement for sensitization, a large dataset of substances that had been evaluated for their skin sensitization potential under Registration, Evaluation, Authorisation and restriction of CHemicals (REACH), together with available measured LogKow values was compiled using the OECD eChemPortal. The incidence of sensitizers relative to non-sensitizers above and below a LogKow of 1 was explored. Reaction chemistry principles were used to explain the sensitization observed for the subset of substances with a LogKow ≤0. 1482 substances were identified with skin sensitization data and measured LogKow values. 525 substances had a measured LogKow ≤ 1, 100 of those were sensitizers. There was no significant difference in the incidence of sensitizers above and below a LogKow of 1. Reaction chemistry principles that had been established for lower MW and more hydrophobic substances were found to be still valid in rationalizing the skin sensitizers with a LogKow ≤ 0. The LogKow threshold arises from the widespread misconception that the ability to efficiently penetrate the stratum corneum is a key determinant of sensitization potential and potency. This dataset is associated with the following publication: Fitzpatrick, J., D. Roberts, and G. Patlewicz. (Journal of Applied Toxicology) Is skin penetration a determining factor in skin sensitisation potential and potency? Refuting the notion of a LogKow threshold for Skin Sensitisation. JOURNAL OF APPLIED TOXICOLOGY. John Wiley & Sons, Ltd., Indianapolis, IN, USA, 1-11, (2016).