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

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.

No abstract

This chapter explores the concepts, processes, tools and challenges relating to the validation of alternative methods for toxicity and safety testing. In general terms, validation is the process of assessing the appropriateness and usefulness of a tool for its intended purpose. Validation is routinely used in various contexts in science, technology, the manufacturing and services sectors. It serves to assess the fitness-for-purpose of devices, systems, software up to entire methodologies. In the area of toxicity testing, validation plays an indispensable role: "alternative approaches" are increasingly replacing animal models as predictive tools and it needs to be demonstrated that these novel methods are fit for purpose. Alternative approaches include in vitro test methods, non-testing approaches such as predictive computer models up to entire testing and assessment strategies composed of method suites, data sources and decision-aiding tools. Data generated with alternative approaches are ultimately used for decision-making on public health and the protection of the environment. It is therefore essential that the underlying methods and methodologies are thoroughly characterised, assessed and transparently documented through validation studies involving impartial actors. Importantly, validation serves as a filter to ensure that only test methods able to produce data that help to address legislative requirements (e.g. EU's REACH legislation) are accepted as official testing tools and, owing to the globalisation of markets, recognised on international level (e.g. through inclusion in OECD test guidelines). Since validation creates a credible and transparent evidence base on test methods, it provides a quality stamp, supporting companies developing and marketing alternative methods and creating considerable business opportunities. Validation of alternative methods is conducted through scientific studies assessing two key hypotheses, reliability and relevance of the test method for a given purpose. Relevance encapsulates the scientific basis of the test method, its capacity to predict adverse effects in the "target system" (i.e. human health or the environment) as well as its applicability for the intended purpose. In this chapter we focus on the validation of non-animal in vitro alternative testing methods and review the concepts, challenges, processes and tools fundamental to the validation of in vitro methods intended for hazard testing of chemicals. We explore major challenges and peculiarities of validation in this area. Based on the notion that validation per se is a scientific endeavour that needs to adhere to key scientific principles, namely objectivity and appropriate choice of methodology, we examine basic aspects of study design and management, and provide illustrations of statistical approaches to describe predictive performance of validated test methods as well as their reliability.

No abstract