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The SHE assay (pH 6.7) is being considered as a ‘3Rs’ alternative in animal laboratory studies (1). We have previously developed a protocol to conduct Fourier-transform infrared spectroscopy in the Syrian hamster embryo (FTIRS-SHE) experiments, and corresponding software to build up a FTIRS-SHE database. Subsequently, we applied machine learning and statistical methods to analyse our datasets towards chemical-treatment classification, morphological transformation classification, and extraction of biomarkers (i.e. spectral wavenumbers) related to chemical treatment (2). In the present study, we set out to validate and develop further our biomarker extraction techniques. Biomarker validation is of extreme importance, for it was found that depending on different biomarker extraction methods (i.e. computational algorithms), there was marked variability in the subsequently identified discriminating biomolecular entities and this would inevitably give rise to different mechanistic interpretations. Furthermore, currently a number of techniques used for such biomarker extraction purposes employed in a variety of fields were never initially conceived with this intention. In this work, we compare different techniques used to extract biomarkers and present rationales for their possible disagreement. We recommend an analysis framework that can derive robust biomarkers for the FTIRS-SHE assay based on pattern classification. The application of our framework can be extended to other studies that use FTIR or Raman spectroscopy. This work was funded by Unilever and the SHE assays were conducted at BioReliance, USA