Abstract
There is an increasing demand for alternative in vitro methods to replace animal testing, and, to succeed, new methods are required to be at least as accurate as existing in vivo tests. However, skin sensitization is a complex process requiring coordinated and tightly regulated interactions between a variety of cells and molecules. Consequently, there is considerable difficulty in reproducing this level of biological complexity in vitro, and as a result the development of non-animal methods has posed a major challenge. However, with the use of a relevant biological system, the high information content of whole genome expression, and comprehensive bioinformatics, assays for most complex biological processes can be achieved. We propose that the Genomic Allergen Rapid Detection (GARD™) assay, developed to create a holistic data-driven in vitro model with high informational content, could be such an example. Based on the genomic expression of a mature human dendritic cell line and state-of-the-art machine learning techniques, GARD™ can today accurately predict skin sensitizers and correctly categorize skin sensitizing potency. Consequently, by utilizing advanced processing tools in combination with high information genomic or proteomic data, we can take the next step toward alternative methods with the same predictive accuracy as today’s in vivo methods—and beyond.
Highlights
The support and demand for developing accurate, non-animal alternative methods for safety assessment have been the top priority for scientists and regulatory authorities for many years
The focus has initially been on the development of in vitro methods based on these key events and has resulted in a handful of in chemico and in vitro tests that have been assigned a test guideline by the Organization for Economic Co-operation and Development (OECD)
Our view is that, when developing new predictive models, it is important not to be restrained by existing mechanistic understanding or the prevailing assumption that a test by necessity must address all key events. This point can be illustrated by the development of the LLNA assay [19], which was based on the current understanding of the biological mechanisms, in particular that sensitization involved clonal expansion of T-cells in the lymph node upon antigen presentation without the need to consider preceding events
Summary
The support and demand for developing accurate, non-animal alternative methods for safety assessment have been the top priority for scientists and regulatory authorities for many years. Genomics-based methods have the potential to fully explore the complex mechanistic information derived from the transcriptome analysis of cells/tissues/organs, after challenge by a foreign substance. By translating these genomic signals into predictive models, analytical tests could be developed for a variety of readouts, including decision values for hazard determination and sensitizing potency of substances. The GARDTM (Genomic Allergen Rapid Detection) assay was developed with the aim to create a data-driven, scientifically valid in vitro model of skin sensitization with a high informational content to reflect the complex processes underlying the immune response. The assay has been shown to have an accuracy of over 90%, based on more than 100 tested chemicals [10,11,12], and similar models for predicting potency classification of skin sensitizers and respiratory sensitization have been developed [13,14]
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