Abstract: High-throughput (HT) gene expression analysis platforms have revolutionised the use of cellular transcriptomic readouts in drug discovery. Use of cDNA barcoding together with laboratory automation, allows assay miniaturisation and pooling to vastly reduce cost whilst enabling rapid transcriptomic profiling of molecules. Within GSK we have implemented an unbiased HT RNA-seq protocol that can screen hundreds of compounds in 384-well format to detect drug-induced whole transcriptome perturbations. When integrated with a standardised analysis pipeline, this approach provides a transcriptomic fingerprint of molecules to inform on the biological pharmacology of differing chemical series. Comparisons with biologically relevant positive and negative controls can be performed to generate multi-dimensional on-phenotype and off-phenotype scores, used to rank and prioritise series of interest. Furthermore, we have applied and integrated additional multi-omic technologies alongside high-content image profiling approaches, to our HT-transcriptomics workflows enabling a greater biological understanding of compound profiles to impact program progression at early drug discovery milestones. Here, we present case studies detailing the implementation of this platform within GSK and it’s recent impact in decoding compound biology. We anticipate that such high-content multi-dimensional technologies will continue to drive more holistic, data-driven and biologically-rich decisions early in the drug discovery pipeline to improve success of first-in-class medicine discovery.