Scalable drug discovery demands phenotypic data that is both mechanistically rich and compatible with high-throughput, AI/ML-driven analysis, yet conventional RNA-seq workflows remain difficult to scale due to cost, manual complexity, and variability. This poster presents an integrated, automation-ready transcriptomics solution combining Alithea Genomics’ MERCURIUS™ DRUG-seq—an RNA extraction-free, cells-to-library workflow compatible with 1536-well formats, with fully automated cell preparation and treatment on Arctoris’ Ulysses^® modular automation platform. By minimising hands-on time and technical variability while maintaining robust gene detection sensitivity across multiple human cell lines, this approach enables reproducible whole-transcriptome screening at scale, supporting mechanism-of-action studies, safety assessment, and data-rich phenotypic profiling suitable for downstream AI/ML analysis.

How the new MERCURIUS™ 1536-well DRUG-seq workflow enables large-scale transcriptomic screening
How integration with Arctoris’ Ulysses® platform unlocks true high-throughput execution
What makes the workflow capable of delivering consistent, high-quality transcriptomic results at scale
The approach used to process thousands of samples per run while maintaining reproducibility
Key performance outcomes, including gene detection and data robustness
How standardised datasets can be generated to support AI/ML-driven drug discovery applications

High-Throughput Transcriptomics for Scalable Phenotypic Screening