Toxicological assessments of skin sensitizers have progressed towards a higher reliance on non-animal methods. Current technological trends aim to extend the utility of non-animal methods to accurately characterize skin-sensitizing potency. The GARDskin Dose–Response assay has previously been described; it was shown that its main readout, cDV₀ concentration, is associated with skin-sensitizing potency. The ability to predict potency from cDV₀ in the form of NESILs derived from LLNAs or human NOELs was evaluated. The assessment of a dataset of 30 chemicals showed that the cDV₀ values still correlated strongly and significantly with both LLNA EC3 and human NOEL values (ρ = 0.645–0.787 [p < 1 × 10⁻³]). A composite potency value that combined LLNA and human potency data was defined, which aided the performance of the proposed model for the prediction of NESILs. The potency model accurately predicted sensitizing potency, with cross-validation errors of 2.75 and 3.22 fold changes compared with NESILs from LLNAs and humans, respectively. In conclusion, the results suggest that the GARDskin Dose–Response assay may be used to derive an accurate quantitative continuous potency estimate of skin sensitizers.

Regulations of cosmetic ingredients and products have been the most advanced in embracing new approach methodologies (NAMs). Consequently, the cosmetic industry has assumed a forerunner role in the development and implementation of animal-free next-generation risk assessment (NGRA) that incorporates defined approaches (DAs) to assess the skin sensitization potency of ingredients. A Bayesian network DA predicting four potency categories (SkinSens-BN) was constructed against reference Local Lymph Node Assay data for a total of 297 substances, achieving a predictive performance similar to that of other DAs. With the aim of optimally informing risk assessment with a continuous point of departure (PoD), a weighted sum of the SkinSens-BN probabilities for four potency classes (non-, weak, moderate, and strong/extreme sensitizer) was calculated, using fixed weights based on associated LLNA EC3-values. The approach was promising, e.g., the derived PoDs for substances classified as non-sensitizers did not overlap with any others and 77% of PoDs were similar or more conservative than LLNA EC3. In addition, the predictions were assigned a level of confidence based on the probabilities to inform the evaluation of uncertainty in an NGRA context. In conclusion, the PoD derivation approach can substantially contribute to reliable skin sensitization NGRAs.

Currently two OECD adopted defined approaches (DA) for eye hazard identification of non-surfactant liquids exist (OECD TG467). The purpose of the current study was to develop a DA for eye hazard identification according to the three UN GHS categories (Cat.1, Cat. 2, No Cat.) for solid chemicals: the DAS. The DAS combines two test methods described in OECD TG437 and TG492. The DAS was developed based on in-depth statistical analysis of a database on solids for which in vitro and historically curated in vivo Draize eye test data exist. The performance of the DAS was assessed by comparing the predictions with the classification based on in vivo Draize eye test data, on the one hand, and with the performance criteria established by the OECD expert group, on the other hand. In a first tier of the DAS, the SkinEthic™ HCE EIT method (TG492) is used to distinguish No Cat. from classified substances. For classified substances the BCOP LLBO method (TG437) is used to identify Cat. 1, the remaining solids are predicted Cat. 2. In summary, 77.4% Cat. 1 (N=31), 52.3% Cat. 2 (N=18) and 70.0% of No Cat. (N=60) solids were correctly identified compared to the classification based on the Draize eye test. The percentage of correct predictions met the minimum OECD established performance values of 75% Cat. 1, 50% Cat. 2, and 70% No Cat. and the percentage of mispredictions was below the established maximum values. Therefore, inclusion of the DAS in OECD TG 467 has been achieved. Plain language summaryDefined approaches combine information from different non-animal testing methods in a specific combination and interpret the results according to a fixed procedure. Such defined approaches are already available as full replacements of animal testing to assess the eye hazard of liquid chemicals (OECD Test Guideline 467). This study used two OECD-adopted in vitro methods, based on human cells and corneas from cattle, to create a defined approach that can be used for solid chemicals. The performance of the procedure was assessed against data from previous animal tests for 109 solid chemicals. The results have already led to this defined approach being adopted by the OECD TGs programme for inclusion in TG 467. With the adoption of the new DA, non-animal human relevant strategies are now available for eye hazard assessment of liquids and solids, reducing the need for animal testing.

The Animal-Free Safety Assessment (AFSA) Collaboration invited a select group of international experts, representing regulatory bodies, industry, method developers, and academia, to a workshop to develop a regulatory strategy implementing non-animal approaches to assess acute toxicity endpoints. The workshop, held in Loch Lomond, Scotland, from 28 April to 1 May, 2025, aimed to develop a decision tree (DT) approach that could support the implementation of non-animal methods and the phased-out use of animal testing for systemic acute and local toxicity. This DT approach provides a transparent decision-making workflow that assists users in applying appropriate opportunities for waiving testing, non-animal testing methods (NAMs), and other adaptations consistently across chemical regulations. DTs also serve to increase awareness of the application of non-animal approaches and ensure compliance with the last resort requirement for animal studies. This workshop aimed to review the suitability of the proposed framework, formulate overarching recommendations for its implementation and provide specific feedback and timelines to finalise endpoint-specific DTs for acute oral toxicity, eye irritation and corrosion, skin irritation and corrosion, and skin sensitisation. This report summarises the overarching discussions and findings tackled during the meeting. The individual endpoint-specific DTs will be described in follow-up scientific publications.

Skin sensitization is an endpoint in the safety evaluation of chemicals. OECD guideline 497 includes three defined approaches (DAs) integrating new approach methodologies (NAMs) for skin sensitization hazard identification or UN GHS potency categorization. The “2 out of 3” (2o3) DA predicts skin sensitization hazard by sequentially testing in up to three NAMs covering key events (KEs) 1-3 of the adverse outcome pathway (AOP). To increase flexibility, OECD is considering the adoption of “alternate” NAMs in guideline 497 targeting the same AOP KE as in test guidelines 442C, 442D, 442E. This study evaluated the feasibility of substituting the h-CLAT with U-SENS™ in the 2o3 DA as NAM for AOP KE 3. To define areas where uncertainty may exist in U-SENS™ predictions, borderline range thresholds around the 150% CD86 stimulation index (SI) cut-off were calculated using a log pooled median absolute deviation method. A revised U-SENS™ prediction model implementing these thresholds classifies a chemical as positive (SI > 176%), negative (SI < 128%), or borderline (128 ≤ SI ≤ 176%). Application of the model changed the U-SENS™ predictions for 35 of 191 chemicals in the OECD database. Substituting the h-CLAT with U-SENS™ in the 2o3 DA resulted in a balanced accuracy of 71% against LLNA (n=168) and 77% against human data (n=66), without considering borderline range thresholds. Incorporating thresholds improved the balanced accuracy to 77% (LLNA, n=142) and 88% (human, n=55). These findings support the inclusion of the U-SENS™ and its borderline range thresholds in OECD guideline 497. Plain language summaryOECD guideline 497 includes three defined approaches (DAs) that combine non-animal test methods to assess a chemical’s potential to cause skin sensitization. The “2 out of 3” (2o3) DA, tests chemicals sequentially using up to three methods that address different mechanistic key events in the skin sensitization process. This study explored the feasibility of substituting the h-CLAT with the U-SENS™ method, which target the same key event, in the 2o3 DA. Borderline range thresholds were established for U-SENS™, allowing chemicals to be classified as positive, negative or borderline for skin sensitization. Using the U-SENS™ instead of the h-CLAT maintained the ability of 2o3 DA to identify chemicals causing skin sensitization, and applying borderline range thresholds for the three methods improved the accuracy of the DA. These findings support the inclusion of the U-SENS™ and its borderline range thresholds in OECD guideline 497.

Skin sensitization is an endpoint in the safety evaluation of chemicals. OECD guideline 497 includes three defined approaches (DAs) integrating new approach methodologies (NAMs) for skin sensitization hazard identification or UN GHS potency categorization. The “2 out of 3” (2o3) DA predicts skin sensitization hazard by sequentially testing in up to three NAMs covering key events (KEs) 1-3 of the adverse outcome pathway (AOP). To increase flexibility, OECD is considering the adoption of “alternate” NAMs in guideline 497 targeting the same AOP KE as in test guidelines 442C, 442D, 442E. This study evaluated the feasibility of substituting the h-CLAT with U-SENS™ in the 2o3 DA as NAM for AOP KE 3. To define areas where uncertainty may exist in U-SENS™ predictions, borderline range thresholds around the 150% CD86 stimulation index (SI) cut-off were calculated using a log pooled median absolute deviation method. A revised U-SENS™ prediction model implementing these thresholds classifies a chemical as positive (SI > 176%), negative (SI < 128%), or borderline (128 ≤ SI ≤ 176%). Application of the model changed the U-SENS™ predictions for 35 of 191 chemicals in the OECD database. Substituting the h-CLAT with U-SENS™ in the 2o3 DA resulted in a balanced accuracy of 71% against LLNA (n=168) and 77% against human data (n=66), without considering borderline range thresholds. Incorporating thresholds improved the balanced accuracy to 77% (LLNA, n=142) and 88% (human, n=55). These findings support the inclusion of the U-SENS™ and its borderline range thresholds in OECD guideline 497. Plain language summaryOECD guideline 497 includes three defined approaches (DAs) that combine non-animal test methods to assess a chemical’s potential to cause skin sensitization. The “2 out of 3” (2o3) DA, tests chemicals sequentially using up to three methods that address different mechanistic key events in the skin sensitization process. This study explored the feasibility of substituting the h-CLAT with the U-SENS™ method, which target the same key event, in the 2o3 DA. Borderline range thresholds were established for U-SENS™, allowing chemicals to be classified as positive, negative or borderline for skin sensitization. Using the U-SENS™ instead of the h-CLAT maintained the ability of 2o3 DA to identify chemicals causing skin sensitization, and applying borderline range thresholds for the three methods improved the accuracy of the DA. These findings support the inclusion of the U-SENS™ and its borderline range thresholds in OECD guideline 497.