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Background: Safety-in-use (SIU) studies are commonly used by the cosmetic Industry to confirm the skin and ocular compatibility of cosmetic products under realistic in-use conditions. There are only limited case studies published about the design, outcome and interpretation of product SIU studies., Objective: A series of SIU case studies is presented to demonstrate the considerations in study design and how the methodology can help in supporting skin and ocular safety profile of facial cosmetic products within a population of different ethnicities with normal and self-perceived sensitive skin., Subjects/methods: In a series of four single-blinded SIU studies, more than 250 female study subjects of different ethnicities and with normal and self-assessed sensitive skin were asked to use different facial cosmetic products including lotions, essences and cleansers according to the instructed usage conditions of these products. Each study was specifically designed according to product usage scenarios and target consumer groups. The primary measures of safety were based on dermal evaluations by a dermatologist for erythema and dryness/scaling and by an ophthalmologist for any visible signs of an ocular condition on eyelids, conjunctivae and cornea. The study subjects were also asked for any self-perceived skin or eye reactions. Dermal and ocular irritation potential of the products under realistic product usage conditions was evaluated according to the measures., Results: Across all studies, objectively and self-assessed mean scores for skin and eye effects did not indicate any cumulative response of the investigated products over the study period., Conclusions: As a suitable tool for assessing and establishing the skin and eye compatibility of facial cosmetic products, SIU studies can be designed according to specific consumer groups, skin types and product usage scenarios to better predict realistic in-use conditions. It can demonstrate the safe use of the investigated products for people of different ethnicities, skin types and with normal or self-assessed sensitive skin, single product use or regimen use. The test results are consistent with the inherently low irritation potential of the products., (© 2024 Society of Cosmetic Scientists and Societe Francaise de Cosmetologie.)

Recent years have seen an increase in the use of botanicals and natural substances (BNS) in consumer products such as cosmetics and household care products. Most work conducted to date to assess botanicals for human safety has focused their use as dietary supplements and thus on systemic toxicity. However, the induction of skin sensitization is a possible adverse effect of natural products in particular those that come into skin contact, especially for cosmetics that remain on the skin and are not rinsed off following use. Assessments of BNS ingredients are often challenging for a number of reasons: the BNS are complex mixtures that can be of mostly unknown composition; the composition can be highly variable even within the same plant species and dependent on how processed; the physical form of the BNS raw material can vary from a highly concentrated powdered extract to a liquid extract containing only a small percentage of the BNS; testing of the BNS raw materials in New Approach Methods (NAM) has uncertainty as these methods are often not developed or validated for complex mixtures. In this study, a reference set of 14 selected BNS which span the range of skin sensitization potential was complied. These data were used in a Weight of Evidence (WoE) approach to evaluate their skin sensitization potential with each of the data rich BNS being classified as either having strong evidence of inducing skin sensitization based on human topical use history, animal data, clinical data, composition data and NAM data, or having some but more limited (weak) evidence of inducing skin sensitization, or having strong evidence of no skin sensitization potential. When available data have sufficient potency related information, sensitization potency assessment is also provided based on WoE, classifying these BNS as either strong, moderate, or weak sensitizers, or non-sensitizers. An outline for a BNS skin sensitization risk assessment framework is proposed starting with exposure-based waiving and WoE assessment for higher exposures. In addition to demonstrating the application of the WoE approach, the reference set presented here provides a set of 'data rich' botanicals which cover a range of sensitization potencies that could be used for evaluating existing test methods or aid in the development of new predictive models for skin sensitization., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Consumer products containing botanicals or natural substances (BNS) are often preferred because there is a perception that 'natural' is safe. As with any product ingredient, a thorough safety assessment must be conducted, including a determination of skin sensitization potential. A modification of the Peroxidase Peptide Reactivity Assay (PPRA) was explored for screening BNS (B-PPRA) for their reactivity to a model cysteine peptide. The PPRA incorporates a horseradish peroxidase‑hydrogen peroxide (+HRP/P) oxidation system for the activation of potential pre- and pro-haptens. BNS test materials contained <2% botanical constituent in either glycerin/water or propylene glycol/water. Stock solutions prepared in acetonitrile were diluted to 8 working concentrations. Direct reactivity was determined in reaction mixtures containing peptide and deferoxamine in potassium phosphate buffer. Enzyme-mediated reactivity determinations were performed with addition of +HRP/P. Initial studies demonstrated that results were reproducible and impact of carrier low. To determine the sensitivity of the assay, experiments were conducted with chamomile extract spiked with three sensitizers. Peptide depletion was observed in the +HRP/P reaction mixtures with isoeugenol spikes as low as 0.05%. The B-PPRA shows promise as a screening method for skin sensitization potential and could become part of a framework for the skin sensitization safety assessment of BNS., Competing Interests: Declaration of Competing Interest C.A. Ryan was employed at P&G when the work was conducted and was now funded for support in manuscript writing., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

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.

In June 2021 the Organisation for Economic Co-operation and Development published Guideline No. 497 on Defined Approaches for Skin Sensitisation (DASS GL). There are two DAs published, known as the 2o3 and the ITS. The 2o3 uses two concordant results from either the DPRA, KeratinoSens™, or the h-CLAT assays to predict hazard (sensitiser/non-sensitiser). The ITS applies a score to results from the DPRA, the h-CLAT and an in silico model to predict United Nations Globally Harmonized System (GHS) sub-categories (1A/1B/Not Classified). The ITS can use Derek Nexus as the in silico model (known as ITSv1) or use OECD QSAR Toolbox (known as ITSv2). As limitations of the individual in chemico/in vitro assays and in silico predictions are carried through to the DAs, inconclusive predictions are possible for chemicals with results in the borderline range, and chemicals with out of domain results. However, these inconclusive predictions can be resolved by applying a weight of evidence approach. Herein, four case studies are presented, each 'inconclusive' for skin sensitisation potential according to both DAs. A weight of evidence approach was applied to each using a robust scientific approach to provide a conclusive prediction, where possible, based on several additional, non-animal lines of evidence., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Martyn Chilton reports a relationship with Lhasa Limited that includes: employment. Corresponding author (Donna Macmillan) was previously employed by, and co-author Martyn Chilton is currently employed by, Lhasa Limited. Lhasa Limited produce Derek Nexus, an in silico tool used in one of the defined approaches published by the OECD and described within the manuscript., (Copyright © 2022 Elsevier Inc. All rights reserved.)

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., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Potency determination of potential skin sensitizers in humans is essential for quantitative risk assessment and proper risk management. SENS-IS is an in vitro test based on a reconstructed human skin model, that was developed to predict the hazard and potency of potential skin sensitizers. The performance of the SENS-IS assay in potency prediction for 174 materials was evaluated for this work. The potency used as a benchmark was determined based on the weight of evidence approach, by collectively considering all well-established test data, including human, animal, in chemico, in vitro, and in silico data. Based on this weight of evidence approach, the dataset was composed of 5, 19, 34, 54, and 38 extreme, strong, moderate, weak, and very weak sensitizers, respectively, as well as 24 non-sensitizers. SENS-IS provided good prediction of the skin sensitization potency for 85% of this dataset, with precise and approximate prediction on 46% and 39% of the 174 materials, respectively. Our evaluation showed that SENS-IS provides a good approximation of the skin sensitization potency., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Interest in the development of methods to evaluate the respiratory sensitization potential of low-molecular weight chemicals continues, but no method has yet been generally accepted or validated. A lack of chemical reference standards, together with uncertainty regarding relevant immunological mechanisms, has hampered method development. The first key event in the development of either skin or respiratory sensitization is the formation of stable adducts of the chemical with host proteins. This event is measured in the Direct Peptide Reactivity Assay using cysteine- and lysine-containing model peptides. It is hypothesized that protein reactivity and subsequent adduct formation may represent the earliest point of divergence in the pathways leading to either skin or respiratory sensitization. Direct Peptide Reactivity Assay data for 200 chemicals were compiled and grouped into respiratory, skin and nonsensitizers. Chemicals grouping was based on extensive literature research and expert judgment. To evaluate if chemical groups represent different peptide reactivity profiles, peptide reactivity data were clustered and compared with information on protein binding mechanisms and chemical categories available via the Organization for Economic Co-operation and Development. Toolbox. Respiratory sensitizers (n = 15) showed a significant (3-fold) higher lysine reactivity than skin sensitizers (n = 129). However, this difference was driven largely by the high representation of acid anhydrides among the respiratory sensitizers that showed clear lysine selectivity. Collectively, these data suggest that preferential reactivity for either cysteine or lysine is associated primarily with chemical structure, and that lysine preference is not a unifying characteristic of chemical respiratory allergens., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

A peptide reactivity assay with an activation component was developed for use in screening chemicals for skin sensitization potential. A horseradish peroxidase-hydrogen peroxide (HRP/P) oxidation system was incorporated into the assay for characterizing reactivity of hapten and pre-/prohapten sensitizers. The assay, named the Peroxidase Peptide Reactivity Assay (PPRA) had a predictive accuracy of 83% (relative to the local lymph node assay) with the original protocol and prediction model. However, apparent false positives attributed to cysteine depletion at relatively high chemical concentrations and, for some chemicals expected to react with the -NH2 group of lysine, little to no depletion of the lysine peptide were observed. To improve the PPRA, cysteine peptide reactions with and without HRP/P were modified by increasing the number of test concentrations and refining their range. In addition, removal of DL-dithiothreitol from the reaction without HRP/P increased cysteine depletion and improved detection of reactive aldehydes and thiazolines without compromising the assay's ability to detect prohaptens. Modification of the lysine reaction mixture by changing the buffer from 0.1 M ammonium acetate buffer (pH 10.2) to 0.1 M phosphate buffer (pH 7.4) and increasing the level of organic solvent from 1% to 25% resulted in increased lysine depletion for known lysine reactive chemicals. Refinement of the prediction model improved the sensitivity, specificity, and accuracy for hazard identification. These changes resulted in significant improvement of the PPRA making it is a reliable method for predicting the skin sensitization potential of all chemicals, including pre-/prohaptens and directly reactive haptens., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

All cosmetic products placed onto the market must undergo a risk assessment for human health to ensure they are safe for consumers, including an assessment of skin sensitisation risk. Historically, in vivo animal test methods were used to identify and characterise skin sensitisation hazard, however non-animal and other new approach methodologies (NAMs) are now the preferred and mandated choice for use in risk assessment for cosmetic ingredients. The experience gained over the last three decades on how to conduct risk assessments based upon NAMs has allowed us to develop a non-animal, next generation risk assessment (NGRA) framework for the assessment of skin sensitisers. The framework presented here is based upon the principles published by the International Cooperation on Cosmetic Regulation (ICCR) and is human relevant, exposure led, hypothesis driven and designed to prevent harm. It is structured in three tiers and integrates all relevant information using a weight of evidence (WoE) approach that can be iterated when new information becomes available. The initial tier (TIER 0) involves a thorough review of the existing information including; identification of the use scenario/consumer exposure; characterisation of the chemical purity and structure; in silico predictions; existing data pertaining to skin sensitisation hazard (historical or non-animal); the identification of suitable read-across candidates with supporting hazard identification/characterisation information and application of exposure-based waiving. Considering all information identified in TIER 0, the next step is the generation of a hypothesis (TIER 1). All data are considered in an exposure-led WoE approach, taking into account an initial view on whether a chemical is likely to be a skin sensitiser or not, choice of defined approach (DA) and availability of read-across candidates. If existing information is insufficient for concluding the risk assessment, the generation of additional information may be required to proceed (TIER 2). Such targeted testing could involve refinement of the exposure estimation or generation of data from in vitro or in chemico NAMs. Once sufficient information is available, the final stage of the NGRA framework is the determination of a point of departure (POD), characterising uncertainty and comparing to the consumer exposure in a WoE. Thorough evaluation of the sources of uncertainty is essential to ensure transparency and build trust in new risk assessment approaches. Although significant progress has been made, industry must continue to share its experience in skin sensitisation NGRA via case studies to demonstrate that this new risk assessment approach is protective for consumers. Dialogue and collaboration between key stakeholders, i.e. risk assessors, clinicians and regulators are important to gain mutual understanding and grow confidence in new approaches., (Copyright © 2020. Published by Elsevier Inc.)

While the skin sensitization hazard of substances can be identified using non-animal methods, the classification of potency into UN GHS sub-categories 1A and 1B remains challenging. The kinetic direct peptide reactivity assay (kDPRA) is a modification of the DPRA wherein the reaction kinetics of a test substance towards a synthetic cysteine-containing peptide are evaluated. For this purpose, several concentrations of the test substance are incubated with the synthetic peptide for several incubation times. The reaction is stopped by addition of monobromobimane, which forms a fluorescent complex with the free cysteine of the model peptide. The relative remaining non-depleted amount of peptide is determined. Kinetic rate constants are derived from the depletion vs concentration and time matrix and used to distinguish between UN GHS sub-category 1A sensitizers and test substances in sub-category 1B/not classified test substances. In this study, we present a ring trial of the kDPRA with 24 blind-coded test substances in seven laboratories. The intra- and inter-laboratory reproducibility were 96% and 88%, respectively (both for differentiating GHS Cat 1A sensitizers from GHS Cat 1B/not classified). Following an independent peer review, the kDPRA was considered to be acceptable for the identification of GHS Cat 1A skin sensitizers. Besides GHS Cat 1A identification, the kDPRA can be used as part of a defined approach(es) with a quantitative data integration procedure for skin sensitization potency assessment. For this aim, next to reproducibility of classification, the quantitative reproducibility and variability of the rate constants were quantified in this study.

Motivation: Due to the risk of inducing an immediate Type I (IgE-mediated) allergic response, proteins intended for use in consumer products must be investigated for their allergenic potential before introduction into the marketplace. The FAO/WHO guidelines for computational assessment of allergenic potential of proteins based on short peptide hits and linear sequence window identity thresholds misclassify many proteins as allergens., Results: We developed AllerCatPro which predicts the allergenic potential of proteins based on similarity of their 3D protein structure as well as their amino acid sequence compared with a data set of known protein allergens comprising of 4180 unique allergenic protein sequences derived from the union of the major databases Food Allergy Research and Resource Program, Comprehensive Protein Allergen Resource, WHO/International Union of Immunological Societies, UniProtKB and Allergome. We extended the hexamer hit rule by removing peptides with high probability of random occurrence measured by sequence entropy as well as requiring 3 or more hexamer hits consistent with natural linear epitope patterns in known allergens. This is complemented with a Gluten-like repeat pattern detection. We also switched from a linear sequence window similarity to a B-cell epitope-like 3D surface similarity window which became possible through extensive 3D structure modeling covering the majority (74%) of allergens. In case no structure similarity is found, the decision workflow reverts to the old linear sequence window rule. The overall accuracy of AllerCatPro is 84% compared with other current methods which range from 51 to 73%. Both the FAO/WHO rules and AllerCatPro achieve highest sensitivity but AllerCatPro provides a 37-fold increase in specificity., Availability and Implementation: https://allercatpro.bii.a-star.edu.sg/., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2019. Published by Oxford University Press.)

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.

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), KeratinoSens TM , h-CLAT (human cell line activation test), U-SENS TM , 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.

Use of quantitative risk assessment (QRA) for assessing the skin sensitization potential of chemicals present in consumer products requires an understanding of hazard and product exposure. In the absence of data, consumer exposure is based on relevant habits and practices and assumes 100% skin uptake of the applied dose. To confirm and refine the exposure, a novel design for in vitro skin exposure measurements was conducted with the preservative, methylisothiazolinone (MI), in beauty care (BC) and household care (HHC) products using realistic consumer exposure conditions. A difference between measured exposure levels (MELs) for MI in leave-on versus rinse-off BC products, and lower MELs for MI in HHC rinse-off compared to BC products was demonstrated. For repeated product applications, the measured exposure was lower than estimations based on summation of applied amounts. Compared to rinse-off products, leave-on applications resulted in higher MELs, correlating with the higher incidences of allergic contact dermatitis associated with those product types. Lower MELs for MI in rinse-off products indicate a lower likelihood to induce skin sensitization, also after multiple daily applications. These in vitro skin exposure measurements indicate conservatism of default exposure estimates applied in skin sensitization QRA and might be helpful in future risk assessments., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Sensitization, the prerequisite event in the development of allergic contact dermatitis, is a key parameter in both hazard and risk assessments. The pathways involved have recently been formally described in the OECD adverse outcome pathway (AOP) for skin sensitization. One single non-animal test method will not be sufficient to fully address this AOP and in many cases the use of a battery of tests will be necessary. A number of methods are now fully developed and validated. In order to facilitate acceptance of these methods by both the regulatory and scientific communities, results of the single test methods (DPRA, KeratinoSens, LuSens, h-CLAT, (m)MUSST) as well for a the simple '2 out of 3' ITS for 213 substances have been compiled and qualitatively compared to both animal and human data. The dataset was also used to define different mechanistic domains by probable protein-binding mechanisms. In general, the non-animal test methods exhibited good predictivities when compared to local lymph node assay (LLNA) data and even better predictivities when compared to human data. The '2 out of 3' prediction model achieved accuracies of 90% or 79% when compared to human or LLNA data, respectively and thereby even slightly exceeded that of the LLNA., (Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.)

To establish further a practical quantitative in chemico reactivity assay for screening contact allergens, lysine peptide was incorporated into a liquid chromatography and tandem mass spectrometry-based assay for reactivity assessments of hapten and pre-/pro-hapten chemical sensitizers. Loss of peptide was determined following 24 h coincubation with test chemical using a concentration-response study design. A total of 70 chemicals were tested in discrete reactions with cysteine or lysine peptide, in the presence and absence of horseradish peroxidase-hydrogen peroxide oxidation system. An empirically derived prediction model for discriminating sensitizers from nonsensitizers resulted in an accuracy of 83% for 26 haptens, 19 pre-/pro-haptens, and 25 nonsensitizers. Four sensitizers were shown to selectively react with lysine including two strong/extreme and two weak sensitizers. In addition, seven sensitizers were identified as having higher reactivity toward lysine compared with cysteine. The majority of sensitizing chemicals (27/45) were reactive toward both cysteine and lysine peptides. An estimate of the relative reactivity potency was determined based on the concentration of test chemical that depletes peptide at or above a threshold positive value. Here, we report the use of EC15 as one example to illustrate the use of the model for screening the skin sensitization potential of novel chemicals. Results from this initial assessment highlight the utility of lysine for assessing a chemical's potential to elicit sensitization reactions or induce hypersensitivity. This approach has the potential to qualitatively and quantitatively evaluate an important mechanism in contact allergy for hazard and quantitative risk assessments without animal testing.

There is an urgent need to develop data integration and testing strategy frameworks allowing interpretation of results from animal alternative test batteries. To this end, we developed a Bayesian Network Integrated Testing Strategy (BN ITS) with the goal to estimate skin sensitization hazard as a test case of previously developed concepts (Jaworska et al., 2010). The BN ITS combines in silico, in chemico, and in vitro data related to skin penetration, peptide reactivity, and dendritic cell activation, and guides testing strategy by Value of Information (VoI). The approach offers novel insights into testing strategies: there is no one best testing strategy, but the optimal sequence of tests depends on information at hand, and is chemical-specific. Thus, a single generic set of tests as a replacement strategy is unlikely to be most effective. BN ITS offers the possibility of evaluating the impact of generating additional data on the target information uncertainty reduction before testing is commenced.

Background: Development, evaluation and validation of alternatives to skin sensitisation testing require the availability of reliable databases with which comparative analyses can be conducted to establish performance characteristics. To facilitate this we have published previously a database comprising results from local lymph node assays (LLNAs) conducted with 211 chemicals. That database embraced a substantial range of chemistry, and of relative skin sensitising potency, and has found application in the assessment of new or refined methods., Objective: In this paper we describe a second compilation to extend the LLNA database., Methods: This second data compilation was derived from previously conducted LLNA studies involving an additional 108 chemicals. In addition, the first database contained a small number of inaccuracies, affecting results recorded with a few chemicals. In this paper these have been corrected., Results: The inclusion of 108 new substances has served to extend and consolidate the areas of chemistry covered by the database. In addition, the entire dataset was evaluated for pre and prohaptens which will facilitate the choice of chemicals for alternative assay developments., Conclusions: It is anticipated that the new revised and extended database totalling over 300 chemicals will now serve as the primary resource to support the development and evaluation of new approaches to hazard identification and potency assessment.

In previous studies we have developed categorical QSAR models for predicting skin-sensitization potency based on 4D-fingerprint (4D-FP) descriptors and in vivo murine local lymph node assay (LLNA) measures. Only 4D-FP derived from the ground state (GMAX) structures of the molecules were used to build the QSAR models. In this study we have generated 4D-FP descriptors from the first excited state (EMAX) structures of the molecules. The GMAX, EMAX and the combined ground and excited state 4D-FP descriptors (GEMAX) were employed in building categorical QSAR models. Logistic regression (LR) and partial least square coupled logistic regression (PLS-CLR), found to be effective model building for the LLNA skin-sensitization measures in our previous studies, were used again in this study. This also permitted comparison of the prior ground state models to those involving first excited state 4D-FP descriptors. Three types of categorical QSAR models were constructed for each of the GMAX, EMAX and GEMAX datasets: a binary model (2-state), an ordinal model (3-state) and a binary-binary model (two-2-state). No significant differences exist among the LR 2-state model constructed for each of the three datasets. However, the PLS-CLR 3-state and 2-state models based on the EMAX and GEMAX datasets have higher predictivity than those constructed using only the GMAX dataset. These EMAX and GMAX categorical models are also more significant and predictive than corresponding models built in our previous QSAR studies of LLNA skin-sensitization measures.

The local lymph node assay (LLNA) is a skin sensitization test that provides animal welfare benefits. To reduce animal usage further, a modified version (rLLNA) was proposed. Conducting the rLLNA as a screening test with a single high dose group and vehicle control differentiated accurately between skin sensitizers and non-sensitizers. This study examined whether a reduction in animal number/group is feasible. Historical data were utilized to examine the impact of conducting the rLLNA with two mice/group. To assess the effect on the stimulation index (SI) 41 datasets with individual animal data derived using five mice/group were analysed. SIs were calculated on all possible combinations of two control and two high dose group disintegrations per minute (dpm) values. For 25 of 33 sensitizer datasets, > 96% of possible dpm combinations resulted in a calculated SI > 3. The lowest percentages of positive SIs were observed with weak allergens when, in the standard LLNA, the mean SIs would have been nearer to the threshold value of 3. The results indicate that moderate, strong and extreme allergens are more likely than weak allergens to be identified as sensitizers when group sizes of two mice are used within the rLLNA. It is concluded that a rLLNA with two mice/group would display decreased sensitivity and is inappropriate for use in hazard identification., (Copyright (c) 2007 John Wiley & Sons, Ltd.)

Three and four state categorical quantitative structure-activity relationship (QSAR) models for skin sensitization have been constructed using data from the murine Local Lymph Node Assay studies. These are the same data we previously used to build two-state (sensitizer, nonsensitizer) QSAR models (Li et al., 2007, Chem. Res. Toxicol. 20, 114-128). 4D-fingerprint descriptors derived from the 4D-molecular similarity paradigm are used to generate these models. A training set of 196 and a test set of 22 structurally diverse compounds were used in this study. Logistic regression, and partial least square coupled logistic regression were used to build the models. The three-state QSAR model gives a classification accuracy of 73.4% for the training set and 63.6% for the test set, while the random average value of classification accuracy for any three-state data set is 33.3%. The two-2-state [four categories in total] QSAR model gives a classification accuracy of 83.2% for the training set and 54.6% for the test set, while the random average value of classification accuracy for any two-2-state data set is 25%. An analysis of the skin-sensitization models developed in this study, as well as the two-state QSAR models developed in our previous analysis, suggests that the "moderate" sensitizers may be the main source of limited model accuracy.

The TImes MEtabolism Simulator platform used for predicting skin sensitization (TIMES-SS) is a hybrid expert system that was developed at Bourgas University using funding and data from a consortium comprised of industry and regulators. TIMES-SS encodes structure-toxicity and structure-skin metabolism relationships through a number of transformations, some of which are underpinned by mechanistic three-dimensional quantitative structure-activity relationships. Here, we describe an external validation exercise that was recently carried out. As part of this exercise, data were generated for 40 new chemicals in the murine local lymph node assay (LLNA) and then compared with predictions made by TIMES-SS. The results were promising with an overall good concordance (83%) between experimental and predicted values. The LLNA results were evaluated with respect to reaction chemistry principles for sensitization. Additional testing on a further four chemicals was carried out to explore some of the specific reaction chemistry findings in more detail. Improvements for TIMES-SS, where appropriate, were put forward together with proposals for further research work. TIMES-SS is a promising tool to aid in the evaluation of skin sensitization potential under legislative programs such as REACH.

The TImes MEtabolism Simulator platform used for predicting Skin Sensitization (TIMES-SS) is a hybrid expert system that was developed at Bourgas University using funding and data from a Consortium comprising industry and regulators. The model was developed with the aim of minimizing animal testing and to be scientifically valid in accordance with the OECD principles for (Q)SAR validation. TIMES-SS encodes structure-toxicity and structure-skin metabolism relationships through a number of transformations, some of which are underpinned by mechanistic 3D QSARs. Here, we describe the extent to which the five OECD principles are met and in particular the results from an external evaluation exercise that was recently carried out. As part of this exercise, data were generated for 40 new chemicals in the murine local lymph node assay (LLNA) and then compared with predictions made by TIMES-SS. The results were promising with an overall good concordance (83%) between experimental and predicted values. Further evaluation of these results highlighted certain inconsistencies which were rationalized by a consideration of reaction chemistry principles for sensitization. Improvements for TIMES-SS were proposed where appropriate. TIMES-SS is a promising tool to aid in the evaluation of skin sensitization hazard under legislative programs such as REACH.

Skin sensitisation potential is an endpoint that needs to be assessed within the framework of existing and forthcoming legislation. At present, skin sensitisation hazard is normally identified using in vivo test methods, the favoured approach being the local lymph node assay (LLNA). This method can also provide a measure of relative skin sensitising potency which is essential for assessing and managing human health risks. One potential alternative approach to skin sensitisation hazard identification is the use of (Quantitative) structure activity relationships ((Q)SARs) coupled with appropriate documentation and performance characteristics. This represents a major challenge. Current thinking is that (Q)SARs might best be employed as part of a battery of approaches that collectively provide information on skin sensitisation hazard. A number of (Q)SARs and expert systems have been developed and are described in the literature. Here we focus on three models (TOPKAT, Derek for Windows and TOPS-MODE), and evaluate their performance against a recently published dataset of 211 chemicals. The current strengths and limitations of one of these models is highlighted, together with modifications that could be made to improve its performance. Of the models/expert systems evaluated, none performed sufficiently well to act as a standalone tool for hazard identification.

The goal of eliminating animal testing in the predictive identification of chemicals with the intrinsic ability to cause skin sensitization is an important target, the attainment of which has recently been brought into even sharper relief by the EU Cosmetics Directive and the requirements of the REACH legislation. Development of alternative methods requires that the chemicals used to evaluate and validate novel approaches comprise not only confirmed skin sensitizers and non-sensitizers but also substances that span the full chemical mechanistic spectrum associated with skin sensitization. To this end, a recently published database of more than 200 chemicals tested in the mouse local lymph node assay (LLNA) has been examined in relation to various chemical reaction mechanistic domains known to be associated with sensitization. It is demonstrated here that the dataset does cover the main reaction mechanistic domains. In addition, it is shown that assignment to a reaction mechanistic domain is a critical first step in a strategic approach to understanding, ultimately on a quantitative basis, how chemical properties influence the potency of skin sensitizing chemicals. This understanding is necessary if reliable non-animal approaches, including (quantitative) structure-activity relationships (Q)SARs, read-across, and experimental chemistry based models, are to be developed.

The assessment of the potency of a skin sensitizing chemical is a key starting point for its subsequent risk assessment/management. The Local Lymph Node Assay can provide information on the relative skin sensitizing potency of contact allergens by interpolation from the dose response curve the concentration of a chemical required to elicit a threshold positive response (EC3 value). However, interpolation requires that the dose response curve have at least one stimulation index (SI) value above and one SI value below the threshold value of 3. For instances where all test concentrations result in SI values above 3, there was a need to develop a method that would permit estimation of EC3 values. This has been achieved by log-linear extrapolation using the two lowest test concentrations from the dose response curve. Before applying this approach, it is important that data quality is assessed. The dose response must include concentrations on the linear portion of the curve and, ideally, the SI induced by the lowest dose should approach 3. Judicious use of this approach for extrapolating EC3 values can provide information on a likely potency classification for use in risk assessment and may avoid the need for repeat animal testing.

Currently, the only validated methods to identify skin sensitization effects are in vivo models, such as the local lymph node assay (LLNA) and guinea pig studies. There is a tremendous need, in particular due to novel legislation, to develop animal alternatives, for eaxample, quantitative structure-activity relationship (QSAR) models. Here, QSAR models for skin sensitization using LLNA data have been constructed. The descriptors used to generate these models are derived from the 4D-molecular similarity paradigm and are referred to as universal 4D-fingerprints. A training set of 132 structurally diverse compounds and a test set of 15 structurally diverse compounds were used in this study. The statistical methodologies used to build the models are logistic regression (LR) and partial least-square coupled logistic regression (PLS-LR), which prove to be effective tools for studying skin sensitization measures expressed in the two categorical terms of sensitizer and non-sensitizer. QSAR models with low values of the Hosmer-Lemeshow goodness-of-fit statistic, X(2)HL, are significant and predictive. For the training set, the cross-validated prediction accuracy of the logistic regression models ranges from 77.3% to 78.0%, whereas that of the PLS-logistic regression models ranges from 87.1% to 89.4%. For the test set, the prediction accuracy of logistic regression models ranges from 80.0% to 86.7%, whereas that of the PLS-logistic regression models ranges from 73.3% to 80.0%. The QSAR models are made up of 4D-fingerprints related to aromatic atoms, hydrogen bond acceptors, and negatively partially charged atoms.

The local lymph node assay (LLNA), an alternative approach to skin-sensitizing testing, has made a significant contribution to animal welfare by permitting a reduction and refinement of animal use. Although there is clearly an aspiration to eliminate the use of animals in such tests, it is appropriate also to consider other opportunities for refinement and reduction of animal use. We have therefore explored the use of a modified version of the LLNA for screening purposes when there is a need to evaluate the sensitizing activity of a large number of chemicals, as will be the case under the auspices of registration, evaluation and authorization of chemicals (REACH). Using an existing LLNA database of 211 chemicals, we have examined whether a cut-down assay comprising a single high-dose group and a concurrent vehicle control would provide a realistic approach for screening chemicals for sensitizing potential. The analyses reported here suggest this is the case. We speculate that the animal welfare benefits may be enhanced further by reducing the number of animals per experimental group. However, a detailed evaluation will be necessary to provide reassurance that a reduction in group size would provide adequate sensitivity across a range of skin sensitization potencies.

Background: Within the toxicology community, considerable effort is directed toward the development of alternative methods for skin sensitization testing. The availability of high-quality, relevant, and reliable in vivo data regarding skin sensitization is essential for the effective evaluation of alternative methodologies. Ideally, data derived from humans would be the most appropriate source because the test methods are attempting to predict a toxicologic effect in humans. Unfortunately, insufficient human data of the necessary quality are available, so it is necessary to rely on the best available animal data. In recent years, the local lymph node assay (LLNA) has emerged as a practical option for assessing the skin sensitization potential of chemicals. In addition to accurately identifying skin sensitizers, the LLNA can also provide a reliable measure of relative sensitization potency, information that is pivotal to the successful management of human health risks., Objective: To provide a database of robust in vivo data to calibrate, evaluate, and eventually validate new approaches for skin sensitization testing., Methods: LLNA data derived from previously conducted studies were compiled from the published literature and unpublished sources., Results: We provide a database that comprises LLNA data on 211 individual chemicals. This extensive chemical data set encompasses both the chemical and biologic diversity of known chemical allergens. To cover the range of relative allergenic potencies, the data set includes data on 13 extreme, 21 strong, 69 moderate, and 66 weak contact allergens, classified according to each allergen's mathematically estimated concentration of chemical required to induce a threefold stimulation index. In addition, there are also 42 chemicals that are considered to be nonsensitizers. In terms of chemical diversity, the database contains data pertaining to the chemical classes represented by aldehydes, ketones, aromatic amines, quinones, and acrylates, as well as compounds that have different reactivity mechanisms. In addition to two-dimensional chemical structures, the physicochemical parameters included are log Kp, log K(o/w), and molecular weight., Conclusions: The list of chemicals contained in the data set represents both the chemical and biologic diversity that is known to exist for chemical allergens and non-allergens. It is anticipated that this database will help accelerate the development, evaluation, and eventual validation of new approaches to skin sensitization assessment.

A quantitative structure-activity relationship (QSAR) system for estimating skin sensitization potency has been developed that incorporates skin metabolism and considers the potential of parent chemicals and/or their activated metabolites to react with skin proteins. A training set of diverse chemicals was compiled and their skin sensitization potency assigned to one of three classes. These three classes were, significant, weak, or nonsensitizing. Because skin sensitization potential depends upon the ability of chemicals to react with skin proteins either directly or after appropriate metabolism, a metabolic simulator was constructed to mimic the enzyme activation of chemicals in the skin. This simulator contains 203 hierarchically ordered spontaneous and enzyme controlled reactions. Phase I and phase II metabolism were simulated by using 102 and 9 principal transformations, respectively. The covalent interactions of chemicals and their metabolites with skin proteins were described by 83 reactions that fall within 39 alerting groups. The SAR/QSAR system developed was able to correctly classify about 80% of the chemicals with significant sensitizing effect and 72% of nonsensitizing chemicals. For some alerting groups, three-dimensional (3D)-QSARs were developed to describe the multiplicity of physicochemical, steric, and electronic parameters. These 3D-QSARs, so-called pattern recognition-type models, were applied each time a latent alerting group was identified in a parent chemical or its generated metabolite(s). The concept of the mutual influence amongst atoms in a molecule was used to define the structural domain of the skin sensitization model. The utility of the structural model domain and the predictability of the model were evaluated using sensitization potency data for 96 chemicals not used in the model building. The TIssue MEtabolism Simulator (TIMES) software was used to integrate a skin metabolism simulator and 3D-QSARs to evaluate the reactivity of chemicals thus predicting their likely skin sensitization potency.

Allergic contact dermatitis resulting from skin sensitization is a common occupational and environmental health problem. In recent years, the local lymph node assay (LLNA) has emerged as a practical option for assessing the skin-sensitization potential of chemicals. In addition to accurate identification of skin sensitizers, the LLNA can also provide a reliable measure of relative sensitization potency, information that is pivotal in successful management of human health risks. However, even with the significant animal welfare benefits provided by the LLNA, there is interest still in the development of non-animal test methods for skin sensitization. Here, we provide a dataset of chemicals that have been tested in the LLNA and the activity of which correspond with what is known of their potential to cause skin sensitization in humans. It is anticipated that this will be of value to other investigators in the evaluation and calibration of novel approaches to skin-sensitization testing. The materials that comprise this dataset encompass both the chemical and biological diversity of known chemical allergens and provide also examples of negative controls. It is hoped that this dataset will accelerate the development, evaluation and eventual validation of new approaches to skin-sensitization testing.

The transition metals nickel (Ni), chromium (Cr) and cobalt (Co) are common causes of allergic contact dermatitis (ACD). Given the high frequency with which these allergens can be associated with hand eczema in those responsible for domestic work, it has been suggested that contamination of household consumer products with these metals may be of relevance to the causation/chronicity of hand dermatitis. Dose-response studies using 48 h occlusive patch test conditions in sensitized individuals show that >/=90% of sensitized patients fail to react below 1 p.p.m., even on irritated skin. Assessment under more realistic exposure conditions has shown that in the presence of irritants and/or following repeated exposures, such individuals rarely react to levels below 10 p.p.m. On the basis of this information, it was recommended a decade ago that household (and other consumer) products should not contain more than 5 p.p.m. of each of Ni, Cr or Co and that, for an even greater degree of protection, the ultimate target level should be 1 p.p.m. The data generated since the original recommendations were made serve to reinforce the validity of these recommendations. Indeed, it is our view that typically the level of each of these transition metals should not normally exceed 1 p.p.m. Then, where consumer products meet this guideline fully, modern quantitative risk assessment shows clearly that elicitation of ACD is highly improbable, and the chance of the induction of sensitization is even lower.

Using NMR spectroscopy, we determined the solution structure of a single-chain T-cell receptor (scTCR) derived from the major histocompatibility complex (MHC) class II-restricted D10 TCR. The conformations of complementarity-determining regions (CDRs) 3beta and 1alpha and surface properties of 2alpha are different from those of related class I-restricted TCRs. We infer a conserved orientation for TCR V(alpha) domains in complexes with both class I and II MHC-peptide ligands, which implies that small structural variations in V(alpha) confer MHC class preference. High mobility of CDR3 residues relative to other CDR or framework residues (picosecond time scale) provides insight into immune recognition and selection mechanisms.

The crystal structure of the two immunoglobulin variable-like domains of the murine CD8alphaalpha homodimer complexed to the class I MHC H-2Kb molecule at 2.8 A resolution shows that CD8alphaalpha binds to the protruding MHC alpha3 domain loop in an antibody-like manner. Comparison of mouse CD8alphaalpha/H-2Kb and human CD8alphaalpha/HLA-A2 complexes reveals shared as well as species-specific recognition features. In both species, coreceptor function apparently involves the participation of CD8 dimer in a bidentate attachment to an MHC class I molecule in conjunction with a T cell receptor without discernable conformational alteration of the peptide or MHC antigen-presenting platform.

This study was developed to test whether prospective dietician counseling could abrogate the unwanted weight gain seen among women receiving adjuvant chemotherapy for resected breast cancer. It was also designed to examine predictive factors for weight gain in an exploratory manner. Premenopausal women starting adjuvant chemotherapy for primary breast cancer were recruited for this trial. After appropriate stratification, they were randomized to a group which received monthly dietician counseling primarily aimed at weight maintenance versus a control group (whose attending physicians and nurses told them about possible weight gain but provided no formalized dietician counseling). One hundred and seven evaluable women were equally divided between the two protocol arms. The median weight changes 6 months after start of chemotherapy were gains of 2.0 kg in the dietician counseling group versus 3.5 kg in the control group. The median changes in average calorie consumption were reductions of 120 versus 46 cal/day on weekdays and 196 versus 20 cal/day on weekends for the counseling and control groups, respectively. Study data suggest that more weight was gained by patients with higher Quetelet's indices (p = 0.01) and patients who had been on a diet in the preceding 6 months (p = 0.02). Routine prospective dietician counseling aimed at weight maintenance appeared to produce small but statistically insignificant reductions in both calorie consumption and weight gain in this group of patients.