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Evaluation of the GARD assay in a blind Cosmetics Europe study

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Henrik Johansson 1, Robin Gradin 1, Andy Forreryd 2, Maria Agemark 1, Kathrin Zeller 2, Angelica Johansson 1, Olivia Larne 1, Erwin van Vliet 3, Carl Borrebaeck 2 and Malin Lindstedt 2
1 SenzaGen AB, Lund, Sweden
2 Dept. of Immunotechnology, Lund University, Lund, Sweden
3 Cosmetics Europe – The Personal Care Association, Brussels, Belgium


Chemical hypersensitivity is an immunological response towards foreign substances, commonly referred to as sen­sitizers, which gives rise primarily to the clinical symptoms known as allergic contact dermatitis. For the purpose of mitigating risks associated with consumer products, chemicals are screened for sensitizing effects. Historically, such predictive screenings have been performed using animal models. However, due to industrial and regulatory demand, animal models for the purpose of sensitization assessment are being replaced by non-animal testing methods, a global trend that is spreading across industries and market segments. To meet this demand, the Genomic Allergen Rapid Detection (GARD) assay was developed. GARD is a novel, cell-based assay that utilizes the innate recognition of xenobiotic substances by dendritic cells, as measured by a multivariate readout of genomic biomarkers. Following cellular stimulation, chemicals are classified as sensitizers or non-sensitizers based on induced transcriptional profiles. Recently, a number of non-animal methods were comparatively evaluated by Cosmetics Europe, using a coherent and blinded test panel of reference chemicals with human and local lymph node assay data, comprising a wide range of sensitizers and non-sensitizers. The outcome of the GARD assay is presented in this paper. It was demonstrated that GARD is a highly functional assay with a predictive performance of 83% in this Cosmetics Europe dataset. The average accumulated predictive accuracy of GARD across independent datasets was 86% for skin sensitization hazard.


Keywords: GARD, sensitization, in vitro, predictive accuracy, alternative methods

Supplementary file (.pdf)


ALTEX 34(4), 2017: 515-523

doi: 10.14573/altex.1701121


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