RNA-seq Workflow For Rapid Lead Selection And Prioritization In Early Drug Development

By Samuel Rulli1, Stuart Tugendreich2, Kamila Koprowska3, Huw Rees3, Krittika Mittal4, Ke Xu4, Niladri Basu4 ; 1 QIAGEN Sciences, Frederick, MD, USA 2 QIAGEN Digital Insights, Redwood City, CA, USA 3 SPT Labtech, Melbourn, Cambridgeshire, UK 4 Faculty of Agricultural and Environmental Sciences, McGill University, Montreal, Canada

Early drug discovery depends on quickly separating promising candidates from those likely to fail. Gene expression profiling offers a powerful way to see how compounds influence cellular pathways long before downstream studies begin, but traditional RNA‑seq workflows can be slow, resource‑intensive, and limited in the types of RNA they capture. Explore a miniaturized, semi‑automated RNA‑seq workflow that works directly from cell lysates and scales efficiently for high‑throughput screening. By combining reduced reaction volumes, streamlined library preparation, and flexible transcriptome coverage, the approach delivers consistent data quality while cutting reagent use, hands‑on time, and plastic waste. Results show reliable detection of both coding and non‑coding RNA, enabling deeper insight into stress responses, toxicity, and pathway-level effects across multiple conditions. The workflow also supports scalable transcriptomics studies with reduced per-sample costs and simplified library preparation for large screening campaigns.

Read the full application note to see how this workflow supports faster, more informed lead prioritization in early‑stage drug development.