Chemical hypersensitivity reactions induced in the skin or in the respiratory tract are important health concerns and develops following repeated exposure to certain chemicals, termed sensitizers. To prevent such hazardous compounds from entering the consumer market, legal frameworks within EU require chemicals to be tested for their capacity to induce hypersensitivity. This type of testing has traditionally been performed in animals, but a recent paradigm shift has been initiated to promote the development of in vitro alternatives. However, currently, such proposed strategies can only be used for identification of skin sensitizing hazard, and are unable to inform on other endpoints of regulatory concern, such as skin sensitizing potency and respiratory sensitization. The GARD assay was developed as a multiparametric alternative to current in vitro tests. The assay measures chemically-induced changes within a predictive biomarker signature of 200 genes using transcriptome-wide microarray profiling and has proven to be highly accurate for identification of skin sensitizers. The overall ambition of the work presented in this thesis has been to utilize novel transcriptomic technologies, advanced computational tools, and powerful machine learning strategies to further transform GARD into a versatile and highly standardized tool for regulatory decision-making.The first part of this thesis addressed the need for a more versatile test platform capable of targeting additional toxicological endpoints. By measuring complete transcriptomes of cells following chemical stimulations, two separate biomarker signatures could be identified and demonstrated to have potent ability to predict respiratory sensitizing properties and skin sensitizing potency, respectively. The second part of this thesis addressed modifications to current GARD protocols to facilitate progression from biomarker discovery into a highly standardized tool for chemical risk assessment. A novel streamlined workflow was presented, where gene expression measurements had been transferred from transcriptome-wide profiling into the NanoString nCounter platform, measuring only genes in the biomarker signatures, which enabled for increased sample throughput, simplified protocols, and reduced assay costs in a format adapted to routine testing.To conclude, by combining the novel biomarker signatures identified in this thesis with the previous biomarker signature for identification of skin sensitizers, the GARD platform demonstrates a unique possibility to simultaneously screen for skin sensitizing hazard and potency, as well as respiratory sensitizing properties in a single test sample. Following the introduction of a novel pipeline to progress from initial biomarker discovery into a highly standardized testing format, results presented in this thesis shows that GARD is a state-of-the-art platform ready to replace animal experimentation for testing of chemical sensitizers