Poster presented at ACT 2020: Applicability of GARD™skin for Accurate Assessment of Challenging Substances in the Context of Skin Sensitization Testing

J. Schmidt, A. Forreryd, H. Johansson, J. Li, A. Johansson
SenzaGen, Inc., Raleigh, NC, USA, SenzaGen AB, Lund, Sweden


Link to the poster



  • GARDskin demonstrated an overall high applicability for the evaluated challenging substances with 80% predictive accuracy compared to existing human data.
  • GARDskin demonstrated excellent applicability for pre/pro-haptens and low water solubility substances, correctly classifying all such compounds in the herein investigated dataset.
  • GARDskin also showed high applicability for assessment of surfactants with 89% predictive accuracy compared to existing human data, correctly classifying 8 out of 9 internally tested surfactants, including well known challenging ones such as Sodium Dodecyl Sulphate (SDS) and Benzalkonium chloride.


Current legislations and trends in predictive toxicology advocate a transition from in vivo methods for hazard and risk assessments to non-animal alternatives. However, certain groups of chemicals, including substances with severe membrane-damaging properties, pre- and pro-haptens, and those with high log P ratios, have been shown to be challenging to assess using cell-based assays in the context of skin sensitization testing. The aim of this study was to evaluate the applicability of GARDskin for such challenging substances, using an overlapping subset of chemicals previously tested in an integrated tested strategy (ITS) based on validated, aqueous in vitro assays, as well as in a series of Reconstructed Human Epidermis (RHE)-based assays.

The GARDskin assay (Genomic Allergen Rapid Detection) is a robust in vitro assay for identification of potential chemical skin sensitizers with over 90% prediction accuracy and broad applicability. The assay is included in the OECD Test Guideline Program (OECD TGP 4.106) and has gone through a formal validation study. The assay evaluates the gene expression of endpoint-specific genomic biomarkers in a human dendritic-like cell line following exposure to the test substance. Exposure-induced gene expression patterns are analysed using pattern recognition and machine-learning technology, providing classifications of each test item as a skin sensitizer or a non-sensitizer.

The applicability of GARDskin for a total of twelve challenging substances, including pre- and pro-haptens, low water-soluble substances, two surfactants and three additional substances known to have conflictive results when comparing in vitro and in vivo data were evaluated in this study. All twelve substances were selected from the Mehling et al. 2019 publication which reported results from three OECD validated in vitro methods, the “2 out of 3” Integrated Testing Strategy, three RHE-based models and the murine local lymph node assay (LLNA). Human potency classification was available for ten out of the twelve substances.

The GARDskin prediction results were reported from previously published studies, or from in house validation studies. Predictive accuracies were calculated by comparing skin sensitization classifications from different test methods to the available human data of each substance respectively. (N=10). To further explore and substantiate the GARDskin applicability for surfactants, additional GARDskin data for a total of nine surfactants are presented in order to complement the Mehling dataset with respect to the availability of human data.

The GARDskin assay demonstrated overall high applicability for the evaluated challenging substances, with 80% predictive accuracy compared to existing human data. GARDskin correctly classified all pre-and pro-haptens and low water-soluble substances in the data set. Furthermore, high applicability of GARDskin for severe membrane disruptive substances such as surfactants was demonstrated, with 89% predictive accuracy compared to existing human data.