Respiratory sensitization is a complex immunological process eventually leading to hypersensitivity following re-exposure to the chemical. A frequent consequence is occupational asthma, which may occur after long latency periods. Although chemical-induced respiratory hypersensitivity has been known for decades, there are currently no comprehensive and validated approaches available for the prospective identification of chemicals that induce respiratory sensitization, while the expectations of new approach methodologies (NAMs) are high. A great hope is that due to a better understanding of the molecular key events, new methods can be developed now. However, this is a big challenge due to the different chemical classes to which respiratory sensitizers belong, as well as because of the complexity of the response and the late manifestation of symptoms. In this review article, the current information on respiratory sensitization related processes is summarized by introducing it in the available adverse outcome pathway (AOP) concept. Potentially useful models for prediction are discussed. Knowledge gaps and gaps of regulatory concern are identified.

Computational modeling has emerged as a time-saving and cost-effective alternative to traditional animal testing for assessing chemicals for their potential hazards. However, few computational modeling studies for immunotoxicity were reported, with few models available for predicting toxicants due to the lack of training data and the complex mechanisms of immunotoxicity. In this study, we employed a data-driven quantitative structure-activity relationship (QSAR) modeling workflow to extensively enlarge the limited training data by revealing multiple targets involved in immunotoxicity. To this end, a probe data set of 6,341 chemicals was obtained from a high-throughput screening (HTS) assay testing for the activation of the aryl hydrocarbon receptor (AhR) signaling pathway, a key event leading to immunotoxicity. Searching this probe data set against PubChem yielded 3,183 assays with testing results for varying proportions of these 6,341 compounds. 100 assays were selected to develop QSAR models based on their correlations to AhR agonism. Twelve individual QSAR models were built for each assay using combinations of four machine-learning algorithms and three molecular fingerprints. 5-fold cross-validation of the resulting models showed good predictivity (average CCR = 0.73). A total of 20 assays were further selected based on QSAR model performance, and their resulting QSAR models showed good predictivity of potential immunotoxicants from external chemicals. This study provides a computational modeling strategy that can utilize large public toxicity data sets for modeling immunotoxicity and other toxicity endpoints, which have limited training data and complicated toxicity mechanisms.

Allergic contact dermatitis (ACD) is the predominant form of immunotoxicity in humans. The sensitizing potential of chemicals can be assessed in vitro. However, a better mechanistic understanding could improve the current OECD-validated test battery. The aim of this study was to get insights into toxicity mechanisms of four contact allergens, p-benzoquinone (BQ), 2,4-dinitrochlorobenzene (DNCB), p-nitrobenzyl bromide (NBB) and NiSO4, by analyzing differential proteome alterations in THP-1 cells using two common proteomics workflows, stable isotope labeling by amino acids in cell culture (SILAC) and label-free quantification (LFQ). Here, SILAC was found to deliver more robust results. Overall, the four allergens induced similar responses in THP-1 cells, which underwent profound metabolic reprogramming, including a striking upregulation of the TCA cycle accompanied by pronounced induction of the Nrf2 oxidative stress response pathway. The magnitude of induction varied between the allergens with DNCB and NBB being most potent. A considerable overlap between transcriptome-based signatures of the GARD assay and the proteins identified in our study was found. When comparing the results of this study to a previous proteomics study in human primary monocyte-derived dendritic cells, we found a rather low share in regulated proteins. However, on pathway level, the overlap was high, indicating that affected pathways rather than single proteins are more eligible to investigate proteomic changes induced by contact allergens. Overall, this study confirms the potential of proteomics to obtain a profound mechanistic understanding, which may help improving existing in vitro assays for skin sensitization.

Animal testing has been prohibited for the safety assessment of cosmetic ingredients or finished products. Thus, alternative non-animal methods, followed by confirmatory clinical studies on human volunteers, should be used as the sole legally acceptable approach within the EU. The safety assessment of cosmetic products requires the involvement of multiple scientific disciplines, including analytical chemistry and biomedicine, as well as in chemico, in vitro and in silico toxicology. Recent data suggest that fragrance components may exert multiple adverse biological effects, e.g. cytotoxicity, skin sensitisation, (photo)genotoxicity, mutagenicity, reprotoxicity and endocrine disruption. Therefore, a pilot study was conducted with selected samples of fragrance-based products, such as deodorant, eau de toilette and eau de parfum, with the aim of integrating results from a number of alternative non-animal methods suitable for the detection of the following toxicological endpoints: cytotoxicity (with 3T3 Balb/c fibroblasts); skin sensitisation potential (in chemico method, DPRA); skin sensitisation potential (LuSens in vitro method, based on human keratinocytes); genotoxicity potential (in vitro Comet assay with 3T3 Balb/c cells); and endocrine disruption (in vitro YES/YAS assay). The presence of twenty-four specific known allergens in the products was determined by using GC-MS/MS. The strategies for estimation of the NOAEL of a mixture of allergens, which were proposed by the Scientific Committee on Consumer Products in their 'Opinion on Tea tree oil' document and by the Norwegian Food Safety Authority in their 'Risk Profile of Tea tree oil' report, were used as models for the NOAEL estimation of the mixtures of allergens that were identified in the individual samples tested in this study.

The importance of the inert environment in the transmission of pathogens has been reassessed in recent years. To reduce cross-contamination, new biocidal materials used in high touch surfaces (e.g., stair railings, door handles) have been developed. However, their impact on skin remains poorly described. The present study aimed to evaluate the antibacterial properties and the risk of skin irritation of two materials based on hard-anodized aluminum (AA) impregnated with quaternary ammonium compound solutions (QAC#1 or QAC#2). The QAC#1 or QAC#2 solutions vary in composition, QAC#2 being free of dioctyl dimethyl ammonium chloride (Dio-DAC) and octyl decyl dimethyl ammonium chloride (ODDAC). Unlike AA used as a control, both AA-QAC#1 and AA-QAC#2 had excellent and rapid antibacterial efficacy, killing 99.9 % of Staphylococcus aureus and Escherichia coli bacteria, in 15 s and 1 min, respectively. The impregnation solutions (QAC#1 and QAC#2) did not show any skin sensitizing effect on transformed human keratinocytes. Nevertheless, these solutions as well as the materials (AA-QAC#1, AA-QAC#2), and the liquid extracts derived from them, induced a very rapid cytotoxicity on L929 murine fibroblasts (>70 % after 1 h of contact) as shown by LDH, MTS and neutral red assays. This cytotoxicity can be explained by the fast QACs release occurring when AA-QAC#1 and AA-QAC#2 were immersed in aqueous medium. To overcome the limitation of assays based on liquid condition, an in vitro skin irritation assay on reconstructed human epidermis (RHE) was developed. The effect of the materials upon their direct contact with the epidermis grown at the liquid-air interface was determined by evaluating tissue viability and quantifying interleukin-1 alpha (IL-1α) which is released in skin during injury or infection. AA-QAC#1 induced a significant decrease in RHE viability, close to OECD and ISO 10993-10 acceptability thresholds and enhanced the pro-inflammatory IL-1α secretion compared with AA-QAC#2. Finally, these results were corroborated by in vivo assays on mice using erythema and edema visual scores, histological observations, and epidermal thickness measurement. AA had no effect on the skin, while a stronger irritation was induced by AA-QAC#1 compared with AA-QAC#2. Hence, these materials were classified as moderate and slight irritants, respectively. In summary, this study revealed that AA-QAC#2 without Dio-DAC and ODDAC could be a great candidate for high touch surface applications, showing an extremely effective and rapid bactericidal activity, without inducing adverse effects for skin tissue.

The aim of the current study was to develop an in silico model to predict the sensitizing potential of cosmetic ingredients based on their physicochemical characteristics and to compare the predictions with historical animal data and results from "omics"-based in vitro studies. An in silico model was developed with the use of WEKA machine learning software fed with physicochemical and structural descriptors of haptens and trained with data from published epidemiological studies compiled into estimated odds ratio (eOR) and estimated attributable risk (eAR) indices. The outcome classification was compared to the results of animal studies and in vitro tests. Of all the models tested, the best results were obtained for the Naive Bayes classifier trained with 24 physicochemical descriptors and eAR, which yielded an accuracy of 86%, sensitivity of 80%, and specificity of 90%. This model was subsequently used to predict the sensitizing potential of 15 emerging and less-studied haptens, of which 7 were classified as sensitizers: cyclamen aldehyde, N,N-dimethylacrylamide, dimethylthiocarbamyl benzothiazole sulphide, geraniol hydroperoxide, isobornyl acrylate, neral, and prenyl caffeate. The best-performing model (NaiveBayes eAR, 24 parameters), along with an alternative model based on eOR (Random Comittee eOR, 17 parameters), are available for further tests by interested readers. In conclusion, the proposed infotechnomics approach allows for a prediction of the sensitizing potential of cosmetic ingredients (and possibly also other haptens) with accuracy comparable to historical animal tests and in vitro tests used nowadays. In silico models consume little resources, are free of ethical concerns, and can provide results for multiple chemicals almost instantly; therefore, the proposed approach seems useful in the safety assessment of cosmetics.

Propylene glycol (PG) has widespread use in pharmaceuticals, cosmetics, fragrances and personal care products. PG is not classified as hazardous under the Globally Harmonised System of Classification and Labelling of Chemicals (GHS) but poses an intriguing scientific and regulatory conundrum with respect to allergic contact dermatitis (ACD), the uncertainty being whether and to what extent PG has the potential to induce skin sensitisation. In this article we review the results of predictive tests for skin sensitisation with PG, and clinical evidence for ACD. Patch testing in humans points to PG having the potential to be a weak allergen under certain conditions, and an uncommon cause of ACD in subjects without underlying/pre-disposing skin conditions. In clear contrast PG is negative in predictive toxicology tests for skin sensitisation, including guinea pig and mouse models (e.g. local lymph node assay), validated in vitro test methods that measure various key events in the pathway leading to skin sensitisation, and predictive methods in humans (Human Repeat Insult Patch and Human Maximisation Tests). We here explore the possible scientific basis for this intriguing inconsistency, recognising there are arguably no known contact allergens that are universally negative in, in vitro, animal and human predictive tests methods.

To maintain the integrity of an organism, a well-functioning immune system is essential. Immunity is dynamic, with constant surveillance needed to determine whether to initiate an immune response or to not respond. Both inappropriate immunostimulation and decreased immune response can be harmful to the host. A reduced immune response can lead to high susceptibility to cancer or infections, whereas an increased immune response can be related to autoimmunity or hypersensitivity reactions. Animal testing has been the gold standard for hazard assessment in immunotoxicity but a lot of efforts are ongoing to develop non-animal-based test systems, and important successes have been achieved. The term "new approach methodologies" (NAMs) refer to the approaches which are not based on animal models. They are applied in hazard and risk assessment of chemicals and include approaches such as defined approaches for data interpretation and integrated approaches to testing and assessment. This review aims to summarize the available NAMs for immunotoxicity assessment, taking into consideration both inappropriate immunostimulation and immunosuppression, including implication for cancer development.

Skin sensitization is induced when certain chemicals bind to skin proteins. Direct peptide reactivity assay (DPRA) has been adopted by the OECD as an alternative method to evaluate skin sensitization by assessing a substance's reaction to two model peptides. A modified spectrophotometric method, Spectro-DPRA, can evaluate skin sensitization, in a high throughput fashion, to obviate some limitations of DPRA. Pre-validation studies for Spectro-DPRA were conducted to determine transferability and proficiency, within- and between-laboratory reproducibility, and predictive ability based on GLP principles at three laboratories (AP, KTR, and KCL). All laboratories confirmed high (> 90%) concordance for evaluating the sensitivity induced by ten chemical substances. The concordance among the three tests performed by each laboratory was 90% for AP, 100% for KTR, and 100% for KCL. The mean accuracy of the laboratories was 93.3% [compared to the standard operating procedure (SOP)]. The reproducibility among the three laboratories was as high as 86.7%; the accuracy was 86.7% for AP, 100% for KTR, and 86.7% for KCL (compared to the SOP). An additional 54 substances were assessed in 3 separate labs to verify the prediction rate. Based on the result, 29 out of 33 substances were classified as sensitizers, and 19 out of 21 identified as non-sensitizers; the corresponding sensitivity, specificity, and accuracy values were 87.9%, 90.5%, and 88.9%, respectively. These findings indicate that the Spectro-DPRA can address the molecular initiating event with improved predictability and reproducibility, while saving time and cost compared to DPRA or ADRA.

Considerable progress has been made in the design of New Approach Methodologies (NAMs) for the hazard identification of skin sensitising chemicals. However, effective risk assessment requires accurate measurement of sensitising potency, and this has proven more difficult to achieve without recourse to animal tests. One important requirement for the development and adoption of novel approaches for this purpose is the availability of reliable databases for determining the accuracy with which sensitising potency can be predicted. Some previous approaches have relied on comparisons with potency estimates based on either human or animal (local lymph node assay) data. In contrast, we here describe the development of a carefully curated Reference Chemical Potency List (RCPL) which is based on consideration of the best available human and animal data. The RCPL is comprised of 33 readily available chemicals that span a wide range of chemistry and sensitising potency, and contain examples of both direct and indirect (pre- and pro-) haptens. For each chemical a potency value (PV) was derived, and chemicals ranked according to PV without the use of potency categories. It is proposed that the RCPL provides an effective resource for assessment of the accuracy with which NAMs can measure skin sensitising potency.

The assessment of skin sensitisation is a key requirement in all regulated sectors, with the European Union's regulation of cosmetic ingredients being most challenging, since it requires quantitative skin sensitisation assessment based on new approach methodologies (NAMs). To address this challenge, an in-depth and harmonised understanding of NAMs is fundamental to inform the assessment. Therefore, we compiled a database of NAMs, and in vivo (human and local lymph node assay) reference data. Here, we expanded this database with 41 substances highly relevant for cosmetic industry. These structurally different substances were tested in six NAMs (Direct Peptide Reactivity Assay, KeratinoSens™, human Cell Line Activation Test, U-SENS™, SENS-IS, Peroxidase Peptide Reactivity Assay). Our analysis revealed that the substances could be tested without technical limitations, but were generally overpredicted when compared to reference results. Reasons for this reduced predictivity were explored through pairwise NAM comparisons and association of overprediction with hydrophobicity. We conclude that more detailed understanding of how NAMs apply to a wider range of substances is needed. This would support a flexible and informed choice of NAMs to be optimally applied in the context of a next generation risk assessment framework, ultimately contributing to the characterisation and reduction of uncertainty.

There is growing awareness that a range of environmental chemicals target the immune system of fish and may compromise the resistance towards infectious pathogens. Existing concepts to assess chemical hazards to fish, however, do not consider immunotoxicity. Over recent years, the application of in vitro assays for ecotoxicological hazard assessment has gained momentum, what leads to the question whether in vitro assays using piscine immune cells might be suitable to evaluate immunotoxic potentials of environmental chemicals to fish. In vitro systems using primary immune cells or immune cells lines have been established from a wide array of fish species and basically from all immune tissues, and in principal these assays should be able to detect chemical impacts on diverse immune functions. In fact, in vitro assays were found to be a valuable tool in investigating the mechanisms and modes of action through which environmental agents interfere with immune cell functions. However, at the current state of knowledge the usefulness of these assays for immunotoxicity screening in the context of chemical hazard assessment appears questionable. This is mainly due to a lack of assay standardization, and an insufficient knowledge of assay performance with respect to false positive or false negative signals for the different toxicant groups and different immune functions. Also the predictivity of the in vitro immunotoxicity assays for the in vivo immunotoxic response of fishes is uncertain. In conclusion, the currently available database is too limited to support the routine application of piscine in vitro assays as screening tool for assessing immunotoxic potentials of environmental chemicals to fish.

The U-SENS™ assay was developed to address the third key event of the skin sensitization adverse outcome pathway (AOP) and is described in OECD test guideline 442E, Annex II. A dataset of 68 fragrance ingredients comprised of 7 non-sensitizers and 61 sensitizers was tested in the U-SENS™ assay. The potential for fragrance ingredients to activate dendritic cells, measured by U-SENS™, was compared to the sensitization potential determined by weight of evidence (WoE) from historical data. Of the non-sensitizers, 4 induced CD86 cell surface marker ≥1.5-fold while 3 did not. Of the sensitizers, 50 were predicted to be positive in U-SENS™, while the remaining 11 were negative. Positive and negative predictive values (PPV and NPV) of U-SENS™ were 93% and 21%, respectively. No specific chemical property evaluated could account for misclassified ingredients. Assessment of parent and metabolite protein binding alerts in silico suggests that parent chemical metabolism may play a role in CD86 activation in U-SENS™. Combining the U-SENS™ assay in a "2 out of 3" defined approach with the direct peptide reactivity assay (DPRA) and KeratinoSens™ predicted sensitization hazard with PPV and NPV of 97% and 24%, respectively. Combining complementary in silico and in vitro methods to the U-SENS™ assay should be integrated to define the hazard classification of fragrance ingredients, since a single NAM cannot replace animal-based methods.

Skin sensitisation is a key adverse health effect to be addressed in the safety assessment of cosmetic ingredients. Regulatory demands have urged the development of Next Generation Risk Assessment (NGRA) using New Approach Methodologies (NAM) and Defined Approaches (DA) instead of animal models. An illustrative NGRA case study shall demonstrate if the use of propyl paraben at 0.2% in a face cream was safe for consumers. A sequential stacking tier testing DA based on NAM data predicted propyl paraben to be a non-sensitiser, while some NAM input data showed positive results. To increase confidence, structurally related parabens were considered, which revealed NAM and DA hazard predictions similar to those of propyl paraben, non-sensitiser classifications in animal models and very rare cases of human skin allergy. Based on a weight of evidence it was decided that propyl paraben should be considered a non-sensitiser leading to a favourable NGRA conclusion, in line with traditional risk assessment. Examination of an ab initio NGRA based on NAM and metabolism data resulted in a more conservative weak sensitiser consideration as point of departure, which still led to a favourable conclusion.

The human cell line activation test (h-CLAT) is an OECD approved (Test No. 442E) assay to identify novel skin sensitizers. h-CLAT simulates dendritic cell activation in the skin sensitization pathway and is based on the measurement of CD54 and CD86 overexpression on monocytic, leukemic THP-1 cells. However, the current h-CLAT markers show inconsistent results with moderate and weak sensitizers. Moreover, these markers have accessory roles in cell adhesion and signaling rather than a direct role in cellular inflammation. Therefore, we have explored other inflammation-related markers in this study. PBMCs comprises a mixture of cells that resemble the complex immunological milieu in adults and were primarily used to identify markers. PBMCs (n = 10) and THP-1 cells were treated with 1-chloro-2,4-dinitrobenzene (DNCB, strong) and NiCl₂ (Ni, moderate) sensitizers or DMSO (control) and incubated for 24 h. The samples were subjected to RNA sequencing to obtain log₂fold change in gene expression. DNCB and NiCl₂ significantly upregulated 80 genes in both cell types. Of these, CD109, CD181, CD183, CLEC5A, CLEC8A & CD354 were experimentally validated. DNCB and Ni but not isopropyl alcohol (non-sensitizer) significantly induced the expression of all novel markers except CLEC8A. Moreover, the percentage induction of all novel markers except CLEC8A satisfied the OECD acceptance criteria. In summary, we identified five novel markers that may supplement the current repertoire of h-CLAT markers.

Skin sensitization potential or potency is an important end point in the safety assessment of new chemicals and new chemical mixtures. Formerly, animal experiments such as the local lymph node assay (LLNA) were the main form of assessment. Today, however, the focus lies on the development of nonanimal testing approaches (i.e., in vitro and in chemico assays) and computational models. In this work, we investigate, based on publicly available LLNA data, the ability of aggregated, Mondrian conformal prediction classifiers to differentiate between non- sensitizing and sensitizing compounds as well as between two levels of skin sensitization potential (weak to moderate sensitizers, and strong to extreme sensitizers). The advantage of the conformal prediction framework over other modeling approaches is that it assigns compounds to activity classes only if a defined minimum level of confidence is reached for the individual predictions. This eliminates the need for applicability domain criteria that often are arbitrary in their nature and less flexible. Our new binary classifier, named Skin Doctor CP, differentiates nonsensitizers from sensitizers with a higher reliability-to-efficiency ratio than the corresponding nonconformal prediction workflow that we presented earlier. When tested on a set of 257 compounds at the significance levels of 0.10 and 0.30, the model reached an efficiency of 0.49 and 0.92, and an accuracy of 0.83 and 0.75, respectively. In addition, we developed a ternary classification workflow to differentiate nonsensitizers, weak to moderate sensitizers, and strong to extreme sensitizers. Although this model achieved satisfactory overall performance (accuracies of 0.90 and 0.73, and efficiencies of 0.42 and 0.90, at significance levels 0.10 and 0.30, respectively), it did not obtain satisfying class-wise results (at a significance level of 0.30, the validities obtained for nonsensitizers, weak to moderate sensitizers, and strong to extreme sensitizers were 0.70, 0.58, and 0.63, respectively). We argue that the model is, in consequence, unable to reliably identify strong to extreme sensitizers and suggest that other ternary models derived from the currently accessible LLNA data might suffer from the same problem. Skin Doctor CP is available via a public web service at https://nerdd.zbh.uni-hamburg.de/skinDoctorII/.

Allergic contact dermatitis is an important occupational health issue, and there is a need to identify accurately those chemicals that have the potential to induce skin sensitisation. Hazard identification was performed initially using animal (guinea pig and mouse) models. More recently, as a result of the drive towards non-animal methods, alternative in vitro and in silico approaches have been developed. Some of these new in vitro methods have been formally validated and have been assigned OECD Test Guideline status. The performance of some of these recently developed in vitro methods, and of 2 quantitative structure-activity relationships (QSAR) approaches, with a series of methacrylate esters has been reviewed and reported previously. In this article that first review has been extended further with additional data and complementary analyses. Results obtained using in vitro methods (Direct Peptide Reactivity Assay, DPRA; ARE-Nrf2 luciferase test methods, KeratinoSens and LuSens; Epidermal Sensitisation Assay, EpiSensA; human Cell Line Activation Test, h-CLAT, and the myeloid U937 Skin Sensitisation test, U-SENS), and 2 QSAR approaches (DEREK™-nexus and TIMES-SS), with 11 methacrylate esters and methacrylic acid are reported here, and compared with existing data from the guinea pig maximisation test and the local lymph node assay. With this series of chemicals it was found that some in vitro tests (DPRA and ARE-Nrf2 luciferase) performed well in comparison with animal test results and available human skin sensitisation data. Other in vitro tests (EpiSensA and h-CLAT) proved rather more problematic. Results with DEREK™-nexus and TIMES-SS failed to reflect accurately the skin sensitisation potential of the methacrylate esters. The implications for assessment of skin sensitising activity are discussed.

Alternatives to mammalian testing are highly desirable to predict the skin sensitisation potential of agrochemical active ingredients (AI). The GARD assay, a stimulated, dendritic cell-like, cell line measuring genomic signatures, was evaluated using twelve AIs (seven sensitisers and five non-sensitisers) and the results compared with historical results from guinea pig or local lymph node assay (LLNA) studies. Initial GARD results suggested 11/12 AIs were sensitisers and six concurred with mammalian data. Conformal predictions changed one AI to a non-sensitiser. An AI identified as non-sensitising in the GARD assay was considered a potent sensitiser in the LLNA. In total 7/12 GARD results corresponded with mammalian data. AI chemistries might not be comparable to the GARD training set in terms of applicability domains. Whilst the GARD assay can replace mammalian tests for skin sensitisation evaluation for compounds including cosmetic ingredients, further work in agrochemical chemistries is needed for this assay to be a viable replacement to animal testing. The work conducted here is, however, considered exploratory research and the methodology needs further development to be validated for agrochemicals. Mammalian and other alternative assays for regulatory safety assessments of AIs must provide confidence to assign the appropriate classification for human health protection.

Hypersensitivity drug reactions (HDRs) are common among drugs, despite this, there are no validated in vitro or in vivo methods for screening the sensitizing potential of drugs in the preclinical phase. We previously developed the THP-1 activation assay, based on CD86 upregulation and IL-8 production, for the in vitro identification of drugs able to induce selective dendritic cell activation. In this paper, we investigated the predictive capacity of the method toward drugs associated with HDRs for which a correlation with specific human leukocyte antigens (HLA) have been demonstrated. For that purpose, abacavir, carbamazepine and clozapine were used. Metformin was used as negative control. Dose- and time-course experiments were conducted. The surface markers CD86, CD54 and HLA-DR were evaluated by flow cytometry analysis, whereas IL-8 release by ELISA. Abacavir, carbamazepine and clozapine gave positive results with CD86 upregulation and/or IL-8 release, with abacavir also inducing HLA-DR. The test reveals the ability of drugs to induce dendritic cell activation (signals 1/2), that preceded the adaptive immune response, which will be manifested only in a minority of patients carrying the specific HLA genotypes. The idea is to integrate this simple method during drug development to identify the potential of drugs to induce hypersensitivity reactions in the pre-clinical phase.

Recently, several non-animal approaches contributing to the identification of skin sensitisation hazard have been introduced. Their validation and acceptance has largely been directed towards regulatory classification. Considering the driving force for replacement of in vivo tests centred on cosmetics, it is reasonable to ask how well the new approaches perform in this respect. In the present study, 219 substances, largely cosmetic raw materials (including dyes, preservatives and fragrances), have been evaluated in our Defined Approach integrating a stacking meta model (version 5), incorporating the individual outcomes of 3 in vitro validated methods (Direct Peptide Reactivity Assay, Keratinosens™, U-SENS™), 2 in silico tools (TIMES SS, TOXTREE) and physicochemical parameters (volatility, pH). Stacking meta model outcomes were compared with existing local lymph node assay (LLNA) data. Non-sensitisers comprised 68/219; 86 were weak/moderate and 65 were stronger sensitisers. The model version revision demonstrate the gain to discriminate sensitizers to non-sensitiser when the in silico TIMES model is incorporated as input parameter. The 85% to 91% accuracy for the cosmetics categories, indicates the stacking meta model offers value for the next generation risk assessment framework. These results pinpoint the power of the stacking meta model relying on a confidence based on the probability given in any individual prediction.

In vitro methods that can replace animal testing in the identification of skin sensitisers are now a reality. However, as cell culture and related techniques usually rely on animal-derived products, these methods may be failing to address the complete replacement of animals in safety assessment. The objective of this study was to identify the animal-derived products that are used as part of in vitro methods for skin sensitisation testing. Thus, a systematic review of 156 articles featuring 83 different in vitro methods was carried out and, from this review, the use of several animal-derived products from different species was identified, with the use of fetal bovine serum being cited in most of the methods (78%). The use of sera from other animals, monoclonal antibodies and animal proteins were also variously mentioned. While non-animal alternatives are available and methods free of animal-derived products are emerging, most of the current methods reported used at least one animal-derived product, which raises ethical and technical concerns. Therefore, to deliver technically and ethically better in vitro methods for the safety assessment of chemicals, more effort should be made to replace products of animal origin in existing methods and to avoid their use in the development of new method protocols.

The ability to predict the skin sensitization potential of small organic molecules is of high importance to the development and safe application of cosmetics, drugs and pesticides. One of the most widely accepted methods for predicting this hazard is the local lymph node assay (LLNA). The goal of this work was to develop in silico models for the prediction of the skin sensitization potential of small molecules that go beyond the state of the art, with larger LLNA data sets and, most importantly, a robust and intuitive definition of the applicability domain, paired with additional indicators of the reliability of predictions. We explored a large variety of molecular descriptors and fingerprints in combination with random forest and support vector machine classifiers. The most suitable models were tested on holdout data, on which they yielded competitive performance (Matthews correlation coefficients up to 0.52; accuracies up to 0.76; areas under the receiver operating characteristic curves up to 0.83). The most favorable models are available via a public web service that, in addition to predictions, provides assessments of the applicability domain and indicators of the reliability of the individual predictions.

Reconstructed human epidermis (RhE) is widely used to replace animal models in order to assess the proinflammatory and allergenic effects of chemicals. Unfortunately, RhE lacks proinflammatory responsiveness for metal haptens, which are the most prevalent human contact allergens, raising concerns about its reliability for predicting skin allergens.

To investigate whether this limitation of RhE might be attributable to a lack of functional expression of Toll-like receptor 4 (TLR4), which governs proinflammatory sensitivity to nickel and cobalt.

RhE, dendritic cell (DC)-containing RhE and full-thickness skin equivalent (FTSE) were compared regarding their proinflammatory responsiveness to metal allergens.

The incorporation of dermal fibroblasts was sufficient to confer metal sensitivity to RhE. Unlike keratinocytes, normal human fibroblasts expressed high levels of TLR4 mRNA and induced interleukin-8 expression upon stimulation with nickel or cobalt. Consistently, dermal isolates from FTSE expressed considerable amounts of TLR4 mRNA, whereas RhE or epidermis isolated from FTSE, normal human epidermis or inflamed human epidermis failed to express TLR4. Similarly, co-culture with TLR4-positive DCs bestowed RhE with proinflammatory responsiveness to metals.

Our data suggest that FTSE or DC/RhE co-culture models can circumvent the shortcomings of RhE assays, and combine the benefits of complex and monoculture-based test systems in a single assay.

As an alternative to animal tests for skin sensitization potency and risk assessment, cell viability and biomarkers related to skin sensitization were analyzed in THP-1 human monocytic leukemia cells. Cell viabilities of 90% (CV90) and 75% (CV75) were determined for 24 selected test chemicals. Further biomarkers related to skin sensitization were also determined under equivalent comparative conditions. In cell viability analyses, potent skin sensitizers exhibited high cytotoxicity, but non-sensitizers did not display this tendency. In biomarker analyses, interleukin-I beta (IL-1β), inducible nitric oxide synthase (iNOS), IL-1β+iNOS, and THP-1 IL-1β+Raw 264.7 IL-1β were found to be suitable for prediction of skin sensitization potency following classification as either skin sensitizers or non-sensitizers (accuracies of 91.7%, 87.5%, 83.3%, and 82.6%, respectively). A significant positive correlation was found between biomarkers and skin sensitization potency, with a correlation coefficient (R) of 0.7 or more (correlation coefficients of 0.77, 0.72, 0.7, and 0.84, respectively). Finally, the skin sensitization potency effective threefold concentration (EC) 3% was predicted using a biomarker equation, with resulting prediction rates (match rate with actual data) of 58.3%, 54.2%, 62.5%, and 60.9%, respectively. The prediction accuracy for the EC3 value obtained from animal data was calculated as 83.3%, 79.2%, 79.2%, and 73.9%, respectively. Thus, these biomarkers, IL-1β and iNOS, may be alternatively used to predict skin sensitization potency and risk assessment.

Skin sensitisation, one of the most frequent forms of human immune toxicity, is authenticated to be a significant endpoint in the field of drug discovery and cosmetics. Due to the drawbacks of traditional animal testing methods, in silico methods have advanced to study skin sensitisation. In this study, mechanism-based binary and ternary classification models were constructed with a comprehensive data set. 1007 compounds were collected to develop five series of local and global models based on mechanisms. In each series, compounds were classified into five groups according to EC3 values, and applied as training sets, test sets and external validation sets. For each of the five series, 81 binary classification models and 81 ternary classification models were acquired via 9 molecular fingerprints and 9 machine learning methods using a novel KNIME workflow. Meanwhile, the applicability domains for the best 10 models were figured out to certify the rationality of prediction effect. In addition, 8 toxic substructures probably causing skin sensitisation were identified to speculate whether a compound is a skin sensitiser. The mechanism-based prediction models and the toxic substructures can be applied to predict the skin sensitising potential and potency of compounds.

At the ESCD congress held in Manchester in 2016, a session was organized to encourage more dialogue between clinicians with expertise in skin sensitization and toxicologists seeking to provide effective risk assessment to prevent human health issues. That session focused on the remaining uncertainties regarding the induction and regulation of skin sensitization in humans, and the opportunities and challenges associated with the refinement and improvement of risk assessment methodologies. This short article, prompted by those discussions, debates what the authors regard as being among the most important and most intriguing uncertainties about skin sensitization and allergic contact dermatitis in humans, and the most significant opportunities for improving risk assessment. The aim has been to provide a basis for mapping out the areas that might benefit from a closer alignment between the relevant clinical community and toxicologists charged with the responsibility of ensuring that skin sensitization risks are understood and managed.

Skin sensitisation associated with allergic contact dermatitis is an important occupational and environmental disease. The identification of skin sensitisation hazards was traditionally performed using animal tests; originally guinea pig assays and subsequently the murine local lymph node assay (LLNA). More recently there has, for a variety of reasons, been an increased interest in, and requirement for, non-animal assays. There are now available both validated in vitro assays and a variety of approaches based on consideration of quantitative structure-activity relationships (QSAR). With the increased availability and use of non-animal alternatives for skin sensitisation testing there is a continuing need to monitor the performance of these approaches using series of chemicals that do not normally form part of validation exercises. Here we report studies conducted with 11 methacrylate esters and methacrylic acid in which results obtained with 3 validated in vitro tests for which there are OECD guidelines (the Direct Peptide Reactivity Assay, DPRA; ARE-Nrf2 luciferase test methods, and - with some chemicals - a dendritic cell activation test, the myeloid U937 Skin Sensitisation test [U-SENS] assay) have been compared with QSAR approaches (DEREK and TIMES-SS), and with LLNA and guinea pig maximisation test (GPMT) data. The conclusions drawn from these data are that - with this series of chemicals at least - there is a strong correlation between the results of animal tests and the in vitro assays considered, but not with either DEREK or TIMES-SS.

In all current in vitro skin sensitisation assays, DMSO is used to dissolve water-insoluble chemicals. However, our previous study suggested the superiority of the modified IL-8 Luc assay (mIL-8 Luc), in which X-VIVO^TM 15 is used to dissolve chemicals, over the original assay using DMSO (oIL-8 Luc). In this study, to confirm the superiority of the mIL-8 Luc, we first increased the number of chemicals examined and demonstrated the superiority of the mIL-8 Luc, in which the mIL-8 Luc provided 87.6% of sensitivity, 74.2% of specificity, and 84.6% of accuracy. Next, to clarify the cause of false negative judgment by the mIL-8 Luc, we examined the effects of physical properties of chemicals on judgment. The results demonstrated that high molecular weight, high LogKo/w, or poor water solubility, did not cause false negative judgment. When it was accepted as an OECD test guideline, the criteria of the mIL-8 Luc to determine sensitisers were modified to further decrease false negative judgment by poor solubility. By applying the new criteria, the test guideline IL-8 Luc assay (tgIL-8 Luc) improved sensitivity but decreased specificity and increased the number of chemicals that cannot be judged. To overcome this problem, we examined a simple combination of the tgIL-8 Luc with direct peptide reactive assay (DPRA), which could improve specificity and decrease the number of the chemicals that cannot be judged. These data suggest that the tgIL-8 Luc is a promising in vitro skin sensitisation assay in combination with other in vitro or in chemico methods.

Electronic cigarettes (e-cigarettes) are an increasingly popular alternative to combustible tobacco cigarettes among smokers worldwide. A growing body of research indicates that flavours play a critical role in attracting and retaining smokers into the e-cigarette category, directly contributing to declining smoking rates and tobacco harm reduction. The responsible selection and inclusion levels of flavourings in e-liquids must be guided by toxicological principles. Some flavour ingredients, whether natural extracts or synthetic, are known allergens. In this study, we used the Genomic Allergen Rapid Detection (GARD) testing strategy to predict and compare the respiratory and skin sensitising potential of three experimental and two commercial e-liquids. These novel, myeloid cell-based assays use changes in the transcriptional profiles of genomic biomarkers that are collectively relevant for respiratory and skin sensitisation. Our initial results indicate that the GARD assays were able to differentiate and broadly classify e-liquids based on their sensitisation potential, which are defined mixtures. Further studies need to be conducted to assess whether and how these assays could be used for the screening and toxicological assessment of e-liquids to support product development and commercialisation.

The worldwide restricted use of animal testing makes it challenging to identify the skin sensitizing potentials of newly manufactured products. The HaCaSens assay has shown promise as an in vitro skin sensitizing assay comparable to existing assays, and is currently under pre-validation. However, there is little agreement on how to assess the results of the assay to discriminate sensitizers from non-sensitizers as the stimulation index (SI) cutoff value was arbitrarily chosen without appropriate statistical methods. Here, we investigated the SI cutoff values in identifying sensitizers to obtain the optimal value. Sensitivities and specificities were calculated for a set of 30 test substances, and plotted in receiver operator characteristics (ROC) curves. The SI cutoff values with the highest sum of sensitivity and specificity according to LLNA data were 2.2, 1.8 and 3.0 for interleukin 1α (IL-1α), interleukin 6 (IL-6), and the combination of the two cytokines respectively. Also, the same statistical analysis of human data demonstrated optimal SI cutoff values 2.0, 2.0 and 3.2 for the same respective parameters. When considering the predictive capacity of each possible SI cutoff value determined by ROC curves, the optimal value for HaCaSens is 3.0 for the combination of IL-1α and IL-6 as it had the highest sensitivity (90.9%), specificity (75.0%) and accuracy (86.7%) based on LLNA data. Thus, we recommend the wide use of the SI cutoff value of 3.0 to ensure consistent endpoints.

EU regulations call for the use of alternative methods to animal testing. During the last decade, an increasing number of alternative approaches have been formally adopted. In parallel, new 3Rs-relevant technologies and mechanistic approaches have increasingly contributed to hazard identification and risk assessment evolution. In this changing landscape, an EPAA meeting reviewed the challenges that different industry sectors face in the implementation of alternative methods following a science-driven approach. Although clear progress was acknowledged in animal testing reduction and refinement thanks to an integration of scientifically robust approaches, the following challenges were identified: i) further characterization of toxicity pathways; ii) development of assays covering current scientific gaps, iii) better characterization of links between in vitro readouts and outcome in the target species; iv) better definition of alternative method applicability domains, and v) appropriate implementation of the available approaches. For areas having regulatory adopted alternative methods (e.g., vaccine batch testing), harmonised acceptance across geographical regions was considered critical for broader application. Overall, the main constraints to the application of non-animal alternatives are the still existing gaps in scientific knowledge and technological limitations. The science-driven identification of most appropriate methods is key for furthering a multi-sectorial decrease in animal testing.

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, such as expert systems software. Here we selected three different types of expert systems: VEGA (statistical), Derek Nexus (knowledge-based) and TIMES-SS (hybrid), and evaluated their performance using two large sets of animal data: one set of 1249 substances from eChemportal and a second set of 515 substances from NICEATM. A model was considered 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 other outcomes, which ranged from 79% to 86%. We found that the highest balanced accuracy of any of the expert systems evaluated was 65% when making global predictions. For substances within the domain of TIMES-SS, however, balanced accuracies for the two datasets were found to be 79% and 82%. In those cases where a chemical was within the TIMES-SS domain, the TIMES-SS skin sensitisation hazard prediction had the same confidence as the result from LLNA or GPMT.

Skin sensitization is a toxicity endpoint of widespread concern, for which the mechanistic understanding and concurrent necessity for non-animal testing approaches have evolved to a critical juncture, with many available options for predicting sensitization without using animals. Cosmetics Europe and the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods collaborated to analyze the performance of multiple non-animal data integration approaches for the skin sensitization safety assessment of cosmetics ingredients. The Cosmetics Europe Skin Tolerance Task Force (STTF) collected and generated data on 128 substances in multiple in vitro and in chemico skin sensitization assays selected based on a systematic assessment by the STTF. These assays, together with certain in silico predictions, are key components of various non-animal testing strategies that have been submitted to the Organization for Economic Cooperation and Development as case studies for skin sensitization. Curated murine local lymph node assay (LLNA) and human skin sensitization data were used to evaluate the performance of six defined approaches, comprising eight non-animal testing strategies, for both hazard and potency characterization. Defined approaches examined included consensus methods, artificial neural networks, support vector machine models, Bayesian networks, and decision trees, most of which were reproduced using open source software tools. Multiple non-animal testing strategies incorporating in vitro, in chemico, and in silico inputs demonstrated equivalent or superior performance to the LLNA when compared to both animal and human data for skin sensitization.

Although the Organization for Economic Cooperation and Development (OECD) has adopted several in vitro methods with reasonable predictive capacity, alternative methods for identifying skin sensitizers and non-sensitizers with reliability and simplicity are still required for more efficient and economic prediction. The present study was to design an in vitro system with the use of a β-galactosidase-expressing E. coli culture for simpler but sufficiently accurate classification of skin sensitizers and non-sensitizers. A LacZ gene-containing E. coli strain that is capable of producing β-galactosidase enzyme was induced by isopropyl β-D-1-thiogalactopyranoside with concomitant treatment with test chemicals. After 6-hr incubation, cells were lysed and β-galactosidase enzyme activity was monitored colorimetrically by using O-nitrophenyl-D-galactopyranoside as a substrate. Following optimization of several experimental conditions, 22 skin sensitizers and 11 non-sensitizers were examined to assess predictive capacity of this method. The results indicated that predictivity was as follows: 90.9% sensitivity, 81.8% specificity, and 87.9% accuracy, when 17.3% of control activity was used as the cut-off value to separate sensitizers from non-sensitizers. Data suggested that the current bacterial system expressing β-galactosidase may serve as a useful alternative test for classifying skin sensitizers and non-sensitizers, without the utilization of animals or mammalian cell cultures.

In this research, firstly astaxanthin (ASX)-loaded nanoemulsions (NEs) were produced using a convenient low-energy emulsion phase inversion method. The optimised ASX-NEs were prepared in the presence of Cremophor^® EL and Labrafil^® M 1944 CS, with a surfactant-to-oil ratio of 4:6. The ASX-NE droplets were spherical with a mean droplet diameter below 100 nm and a small negative surface charge. The system was stable without alteration of mean droplet diameter for three months. Then, the ASX-NE was functionalised with carboxymethyl chitosan (CMCS) through direct CMCS (0.02%) incorporation during the preparation process. The ASX chemical stability and skin permeability increased in the following order: ASX solution control < ASX-NE < CMCS-ASX-NE. Cell viability assays on L929 cells revealed low cytotoxicity of blank NE, ASX-NE and CMCS-ASX-NE in the range from 5 to 500 μg mL^-1. In conclusion, the CMCS-ASX-NE might be a promising delivery vehicle in dermal and transdermal products.

Human cell-based approaches to assess defined key events in allergic contact dermatitis (ACD) are well-established, but lack cutaneous penetration and biotransformation as well as cellular cross-talk. Herein, we integrated in vitro-generated immature MUTZ-3-derived Langerhans-like cells (MUTZ-LCs) or monocyte-derived LC-like cells (MoLCs) into reconstructed human skin (RHS), consistent of a stratified epidermis formed by primary keratinocytes on a dermal compartment with collagen-embedded primary fibroblasts. LC-like cells were mainly localized in the epidermal compartment and distributed homogenously in accordance with native human skin. Topical application of the strong contact sensitizer 2,4-dinitrochlorobenzene (DNCB) induced IL-6 and IL-8 secretion in RHS with LC-like cells, whereas no change was observed in reference models. Increased gene expression of CD83, PD-L1, and CXCR4 in the dermal compartment indicated LC maturation. Importantly, exposure to DNCB enhanced mobility of the LC-like cells from epidermal to dermal compartments. In response to the moderate sensitizer isoeugenol and irritant sodium dodecyl sulphate, the obtained response was less pronounced. In summary, we integrated immature and functional MUTZ-LCs and MoLCs into RHS and provide a unique comparative experimental setting to monitor early events during skin sensitization.