A convenient spectrophotometric test for screening skin-sensitizing chemicals using reactivity with glutathione in chemico

To initiate skin sensitization, haptens react with endogenous proteins. During this process, skin sensitizers react with small endogenous molecules containing thiol or amino groups. In this study, a simple spectrophotometric method to identify skin sensitizers in chemico was developed using the reactivity of glutathione (GSH) with test chemicals in a 96-well plate. To quantitate the remaining GSH following the reaction with a skin sensitizer, 5,5'-dithiobis-(2-nitrobenzoic acid) (DTNB) was employed. The optimized experimental conditions included the pH- and time-dependent stability of GSH, stability of derivatized products of GSH with optimal concentration and incubation time of DTNB, incubation time of GSH with the test chemicals, and molar ratios of GSH to the test chemicals. With the optimized conditions with both acetonitrile and DMSO as vehicles and incubation of GSH with test chemicals in 1:10 and 1:15 ratios for 24 h at 4 °C, 23 skin sensitizers and 23 non-sensitizers, based on the local lymph node assay, were tested to determine the predictive capacity of individual conditions. The best result showed a predictive capacity of 95.2% sensitivity, 91.3% specificity, and 93.2% accuracy, with 93.2% consistency in three trials, when 5.8% depletion was used as a cut-off value in 1:10 of GSH:test chemicals in DMSO. It would be an economic and useful screening tool for determining the skin sensitization potential of small molecules, because the present method employs simple endogenous GSH as an electron donor for sensitizers with a spectrophotometric detection system in 96-well plates, and because the method requires neither experimental animals nor cell cultures.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43188-023-00218-9.

Estimating uncertainty in LLNA EC3 data and its impact on regulatory classifications

The murine Local Lymph Node Assay (LLNA) is a test that produces numerical results (EC3 values) quantifying the sensitization potency of chemicals. These results are broadly used in toxicology and serve as a basis for various classifications, which determine subsequent regulatory decisions. The continuing interest in LLNA data and the diminished likelihood of new experimental EC3 data being generated sparked this investigation of uncertainty. Instead of using the Gaussian distribution as a default choice for assessing variability in a data set, two strictly positive distributions were proposed and their performance over the available experimental EC3 values was tested. In the application stage, how the uncertainty in EC3 values affects the possible classifications was analyzed, and the percentage of the chemicals receiving ambiguous classification was determined. It was shown that this percentage is high, which increases the risk of improper classification. Two approaches were suggested in regulatory practice to address the uncertainty in the EC3 data: the approaches based on "grey zones" and the classification distribution. If a chemical cannot be classified unambiguously, the latter appears to be an acceptable means to assess the level of sensitization potency of chemicals and helps provide better regulatory decisions.

Peptide reactivity assays for skin sensitisation - scope and limitations

The direct peptide reactivity assay (DPRA) is an OECD test guideline method that aims to determine if a chemical is reactive enough to be a skin sensitiser. It involves incubation of the test chemical at 5 mMolar concentration for 24 h with a cysteine-based peptide at 0.5 mMolar concentration and measurement of the percentage depletion (DP) of the peptide. The kinetic direct peptide reactivity assay (kDPRA) is derived from the DPRA and involves incubating the peptide with the test chemical at a range of concentrations and incubation times to produce a data matrix of DP values, which is analysed to give a reactivity parameter logk_max that assigns chemicals to the 1A potency class (high potency) if logk_max reaches the threshold value of -2. Here the DPRA, with a threshold of 47% DP, is compared against the kDPRA for their abilities to distinguish between the 1A and non-1A potency classes. It is found that they perform very similarly against a dataset of 157 chemicals with known potency, with only marginal differences in predictive performance. The thresholds of -2.0 (kDPRA) and 47% DP (DPRA) to distinguish 1A sensitisers are not scientific absolutes but the best compromises for a heterogenous set of data containing classes of chemicals for which different thresholds would be applicable. It is concluded that although the kDPRA represents a major advance towards predicting skin sensitisation potency on a continuous basis without animal testing, it offers no significant advantage over the DPRA for the purpose of 1A classification.

Accounting for Precision Uncertainty of Toxicity Testing: Methods to Define Borderline Ranges and Implications for Hazard Assessment of Chemicals

For hazard classifications of chemicals, continuous data from animal- or nonanimal testing methods are often dichotomized into binary positive/negative outcomes by defining classification thresholds (CT). Experimental data are, however, subject to biological and technical variability. Each test method's precision is limited resulting in uncertainty of the positive/negative outcome if the experimental result is close to the CT. Borderline ranges (BR) around the CT were suggested, which represent ranges in which the study result is ambiguous, that is, positive or negative results are equally likely. The BR reflects a method's precision uncertainty. This article explores and compares different approaches to quantify the BR. Besides using the pooled standard deviation, we determine the BR by means of the median absolute deviation (MAD), with a sequential combination of both methods, and by using nonparametric bootstrapping. Furthermore, we quantify the BR for different hazardous effects, including nonanimal tests for skin corrosion, eye irritation, skin irritation, and skin sensitization as well as for an animal test on skin sensitization (the local lymph node assay, LLNA). Additionally, for one method (direct peptide reactivity assay) the BR was determined experimentally and compared to calculated BRs. Our results demonstrate that (i) the precision of the methods is determining the size of their BRs, (ii) there is no "perfect" method to derive a BR, alas, (iii) a consensus on BR is needed to account for the limited precision of testing methods.

The index of ideality of correlation: A criterion of predictability of QSAR models for skin permeability?

New criterion of the predictive potential of quantitative structure-property/activity relationships (QSPRs/QSARs) is suggested. This criterion is calculated with utilization of the correlation coefficient between experimental and calculated values of endpoint for the calibration set, with taking into account the positive and negative dispersions between experimental and calculated values. The utilization of this criterion improves the predictive potential of QSAR models of dermal permeability coefficient, logKp (cm/h).