The GARD® technology.

Key elements of GARD®

SenzaGen’s GARD (Genomic Allergen Rapid Detection™) platform comprises a series of tests that are all designed according to the same principle, which is comprised of four key elements: a biological cell system, a training dataset, a genomic biomarker signature and a prediction model.

  • Biological cell system

    The biological cell system used by all the GARD tests is a human dendritic-like cell line (SenzaCells™) which mimics a critical part of the human immune system and is able to recognize allergens.

  • Training dataset

    The training dataset consists of genome-wide gene expression profiles from cellular exposures to a set of well-characterized chemical sensitizers and non-sensitizers. The training dataset can be used both for biomarker discovery and subsequent training of the prediction model.

  • Genomic biomarker signature

    By performing gene expression pattern analysis of the training dataset, relevant genes can be selected as the biomarkers for the toxicological endpoint, thereby establishing a so-called genomic biomarker signature.

  • Prediction model

    Based on the gene expression patterns of the genomic biomarker signature studied in the training dataset, machine-learning technology is used to create prediction models for the investigated endpoint. These models are used to perform future classifications of test chemicals.

Holistic approach – improved accuracy and human relevance

The GARD assays were developed with a holistic view, utilizing genomics and machine-learning technology to reflect the complex processes underlying an immune response, e.g. skin sensitization.

Traditional in vitro tests investigate only a few biomarkers and provide limited information to give reliable results. Animal tests provide much more information which, however, are not always human-relevant. By using a genomics-based approach with machine-learning technology, GARD combines the simplicity of in vitro methods and the biological intricacy of in vivo models.

This holistic approach contributes to improved accuracy and human relevance. For example, the predictive accuracy of animal tests for skin sensitization assessment is estimated from 70% to 75%; the traditional in vitro tests are ranging from 75% to 80%, while GARDskin has a predictive accuracy of over 90%.