Next generation risk assessment (NGRA) for skin sensitisation: Case studies with resorcinol and propyl paraben
Skin sensitisation is one of the key adverse health effects to be addressed in the safety assessment of cosmetic ingredients. In the past, guinea pig assays such as the Guinea pig maximization test (GPMT) were mostly used for skin sensitisation hazard identification. In an attempt to reduce the use of experimental animals and have better quantifiable read outs, these assays were increasingly substituted by the mouse Local Lymph Node Assay (LLNA) allowing to establish dose-response relationships. However, ethical considerations and regulatory demands urged the development of Next Generation Risk Assessment (NGRA) approaches using New Approach Methodologies (NAM) and Defined Approaches (DA) instead of animal models.
To support the progress of skin sensitisation NGRA for cosmetic ingredients, illustrative case studies with resorcinol and propyl paraben in face cream were performed in recent publications of Gautier et al. (2020) and Vandecasteele et al. (2021) using the NGRA framework. Case studies regarded both ‘resorcinol’ and ‘propyl paraben’ as a “new” cosmetic ingredient and did not consider existing animal or human data. However, available NAM, animal and human data for structurally related substances was collected to support NGRA development. Only after the completion of the NGRA, a traditional risk assessment was performed to evaluate the performance of the developed NGRA.
A stepwise approach was followed in both cases:
- Collection of existing information for these ingredients
- Integration of existing information in the sequential testing strategy DA for skin sensitisation hazard and potency prediction
- Collection of NAM and DA data for structurally related substance
- Collection of animal and human skin sensitisation data for structurally related substances
For resorcinol, the NAM data and DA predictions could not provide sufficient confidence to allow determination of a point of departure (POD). Therefore, the application of read-across was explored to increase the level of confidence. Analogue searches in various tools and databases using “mode of action” and “chemical structural features” retrieved >500 analogues. After refinement by excluding analogues without a defined structure, similar reactivity profile and skin sensitisation data, approximately 40 analogues remained. A final selection was made based on expert judgment, chemical similarity and/or available LLNA data. All read-across approaches supported a moderate potency. A POD derived from the LLNA (EC3 of 3.6%) was determined leading to a favourable NGRA conclusion and a maximum use concentration of 0.36% in face cream. This was supported by a traditional risk assessment based on available animal data for resorcinol. The generation of additional NAM data for resorcinol was not considered necessary, as the confidence in the derived EC3 value was deemed sufficient to be used as POD for the risk assessment with respect to skin sensitisation. In case of an “ab initio” NGRA case study for a new ingredient with insufficient animal or human data for analogues, the generation of NAM data for analogues covering different KEs of the skin sensitisation AOP may be useful for the integration in one or more of the available DA for hazard and potency prediction.
With regard to propyl paraben, a sequential stacking tier testing DA based on NAM data predicted it to be a non-sensitiser, while some NAM input data suggested evidence of skin sensitization potential. To increase the confidence in the assessment, structurally related parabens were considered. These 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 the weight of evidence, it was decided that propyl paraben should be considered a non-sensitiser leading to a favourable NGRA conclusion for use of a level of 0.2% in a face cream, in line with the 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.
These case studies demonstrated that a NGRA for skin sensitisation may be sufficiently protective for consumers and may allow an exposure-led skin sensitisation risk assessment of cosmetic ingredients without generating animal data. Further, the approach for analogue identification and selection showed the importance of a flexible and transparent refinement process based on several similarities (i.e., chemical structure, physiochemical properties, reactivity, mode of action). The main lessons learned from these illustrative NGRA case studies are that a DA outcome should not be used by default for NGRA, even if it includes a high level of confidence. Expert judgment from an experienced safety assessor is required to characterise any uncertainties and make a WoE-based decision on the skin sensitisation potency of the ingredient, as was already the case in traditional risk assessment.
Overall, it can be concluded that there will be very interesting and promising developments in NAMs application in NGRA. As regulators, industries as well as researchers are working together and in collaborations to help make toxicity testing paradigm shift in 21st century, despite many challenges, it appears that in coming days more NAMs will be accepted by regulatory authorities around the world.
ToxMinds has extensive scientific as well as regulatory experience in the application of New Approach Methodologies (NAM) in general and read-across specifically for assessment of all toxicological endpoints including skin sensitization. For more details on our expertise and how we can help and support you, contact us at email@example.com.