Main applications for transcriptomic profiling in drug discovery and perturbation studies
Drug discovery rarely ends with a simple hit call. The harder question is what that hit is doing biologically, and whether observed effects reflect on-target biology or off-target responses. MERCURIUS™ DRUG-seq and MERCURIUS™ Total DRUG-seq are designed for that next step, bringing extraction-free transcriptomic profiling into screening and downstream discovery workflows. Together, they cover complementary needs, from scalable 3′ gene expression profiling for large compound and genetic perturbation studies to full-length total RNA analysis when transcript structure and broader RNA coverage become important.
Hit triage and mechanism-of-action studies
Gene expression signatures can add a second layer of evidence when teams need to decide which hits deserve deeper follow-up, supporting prioritization and helping distinguish biologically meaningful effects from non-specific or off-target responses. MERCURIUS™ DRUG-seq is used for screening-scale compound and perturbation studies, and its published performance materials emphasize transcriptional clustering and co-clustering analyses that help compare compound responses across many conditions.
Phenotypic screening follow-up
Phenotypic assays can show that cells changed state without fully explaining why. When paired with high-content imaging or Cell Painting workflows, transcriptomic profiling can help connect image-based phenotypes to underlying biology. Revvity's Cell Painting portfolio is built around phenotypic profiling with high-content screening, and PhenoVue™ Cell Painting Kits are validated for systems such as Opera Phenix® Plus and used with Operetta CLS™ imaging workflows.
Signature-based comparison across perturbations
Transcriptomic profiling enables systematic comparison of biological responses across compounds, doses, or genetic perturbations. Gene expression signatures can be used for clustering, co-clustering, and pathway-level analysis, helping identify shared mechanisms, group related perturbations, and prioritize candidates based on biological similarity. MERCURIUS™ DRUG-seq supports scalable signature generation across large studies, enabling consistent cross-condition comparisons.
Target discovery and downstream validation
Some discovery programs need more than a 3' expression signature, particularly when non-coding RNA, transcript variants, alternative splicing, gene fusions, or promoter usage are important. MERCURIUS™ Total DRUG-seq supports target discovery and downstream validation by providing a fuller RNA view when broader transcript coverage is needed to interpret screening results and guide next steps.
Large compound and genetic perturbation studies
Transcriptomic profiling is also useful in studies where responses need to be compared across many compounds, combinations, or genetic perturbations. MERCURIUS™ DRUG-seq is designed for high-throughput workflows, enabling consistent gene expression readouts across large studies and supporting the generation of datasets for clustering, pathway analysis, and data-driven discovery.
