MERCURIUS™

DRUG-seq Technology

Extraction-free, high-throughput RNA-seq technology for compound screening, mechanism-of-action profiling, toxicology studies, and AI-ready perturbation datasets.

Whole transcriptome
RNA-seq

No need for prior RNA extraction

Ultra-scalable and
cost-efficient

Suited to
lab automation

MERCURIUS™ DRUG-seq brings transcriptomic profiling into high-throughput screening, helping drug discovery and toxicology teams move beyond single-endpoint assays toward richer biological interpretation at scale

MERCURIUS™ DRUG-seq turns high-throughput transcriptomic profiling into a practical decision tool for large-scale compound discovery programs, next-generation toxicology strategies, and mechanism-driven safety assessment. The result is faster insight, better compound prioritization, and more informed decisions across the discovery and safety pipeline.

MERCURIUS™ DRUG-seq detects compound pathway engagement, distinguishes universal cellular stress responses from compound-specific signatures, and uncovers hidden biology, such as off-target activity, shifts in cell differentiation, and immune activation, challenging to detect with other approaches.

By delivering standardized scoring and robust cross-study comparability, MERCURIUS™ DRUG-seq enables researchers to cluster compounds by mechanism of action, prioritize biological pathways, and track dose- and time-dependent responses for more confident go/no-go decisions. 

What is MERCURIUS™ DRUG-seq technology?

MERCURIUS™ DRUG-seq is an extraction-free, plate-based RNA-seq technology designed for high-throughput gene expression profiling directly from cells. Samples are lysed in wells, barcoded early during reverse transcription, pooled, and processed together for sequencing.

This workflow reduces the cost and complexity of standard RNA-seq, making transcriptomic readouts practical for compound screening, perturbation studies, toxicology, mechanism-of-action profiling, and large-scale biological dataset generation.

Why use MERCURIUS™ DRUG-seq for high-throughput transcriptomics?

UMAP animation

Higher-content biological readouts

Quantify pathway engagement, distinguish shared stress programs from compound-specific signatures, and surface unexpected biology such as off-target effects, differentiation shifts, and immune activation early in the pipeline.

Extraction-free workflow from cell lysates

Move from cell lysates to sequencing-ready libraries with fewer steps and less hands-on time. By combining direct-from-lysate processing with an improved reverse transcription step, MERCURIUS™ DRUG-seq avoids the template-switching oligos and pre-amplification used in the original protocol, simplifying the workflow while improving mapping and gene detection rates.

Screening-scale
multiplexing

Run DRUG-seq in 96-, 384-, or 1,536-well plate formats, depending on the stage and scale of your study. Early barcoding and pooling let you process many samples together from the start of the workflow, making it practical to run transcriptomic studies at the scale needed for discovery, development, and cross-study comparison.

A transformative tool for next-gen drug discovery

A scalable and cost-effective transcriptomic profiling solution that accelerates target identification and validation, hit identification, hit-to-lead, and lead optimization. By providing deep gene expression insights across thousands of compounds, MERCURIUS™ DRUG-seq reveals mechanisms of action, detects on/off-target effects, and uncovers toxicity markers, empowering faster, data-driven decisions throughout the drug development pipeline.

MERCURIUS™ DRUG-seq helps you decode

Mechanism of action

Compare compound-induced gene expression signatures across doses, controls, and models to support pathway interpretation and MoA hypothesis generation.

Drug resistance

Identify drug resistance mechanisms at the transcriptomic level by tracking pathway rewiring and molecular adaptation, supporting response stratification and follow-up hypotheses.

Toxicity and stress signals

Detect stress-response, mitochondrial, inflammatory, or cell-state changes earlier in screening and toxicology workflows.

AI-ready datasets

Generate structured expression matrices across compounds, concentrations, time points, and cellular models for predictive modeling and compound-response analysis.

MERCURIUS™ DRUG-seq in action at screening scale

The examples below show how transcriptome-wide readouts can reveal mechanisms of action, detect combination effects, and generate actionable insights across large screening campaigns.

For large scale studies

Gene detection overview of a case study on 22,000 samples and 51 compounds in four doses, on 6 cell lines, sequenced at 1M reads per sample. 

Clustering and co-clustering

Use unbiased gene expression measurements to support accurate compound clustering and co-clustering analyses.

Drug combinations

Detect synergistic or antagonistic combination effects from transcriptomic signatures.

Enables detailed pathway analysis of biological processes

Interrogate the molecular pathways and identify altered biological processes​

Recent publications

2025

Anstett, V.; Heinzelmann, E.; Piraino, F.; Roch, A.; Chrisnandy, A.; Norkin, M.; Garnier, V.; Homicsko, K.; Hoehnel-Ka, S.; Brandenberg, N.

What do our customers say

Start small, confirm performance, then scale with confidence

Step 1: Pilot design

Start with a focused subset to validate the workflow and choose the right DRUG-seq readout (3′ or Total). The pilot can be executed in our labs as a service, or in your lab using MERCURIUS™ DRUG-seq kits.

Step 2: Pilot execution

Validate the workflow on a focused subset and review library QC, sequencing QC, signal-to-noise, reproducibility, and sequencing depth before scaling.

Step 3: Scale

Expand into the full matrix of models, doses, time points, and combinations, while keeping controls and reporting consistent across plates and batches.

Choose the right DRUG-seq workflow

Scroll right

DRUG-seq workflow

Best for

Available as

MERCURIUS™
DRUG-seq

High-throughput compound screening, MoA studies, toxicity profiling, and perturbation studies

MERCURIUS™
Total DRUG-seq

Studies requiring broader transcript coverage, non-coding RNAs, isoforms, alternative splicing, or target validation

MERCURIUS™
Spheroid DRUG-seq

Transcriptomic profiling directly from 3D spheroids and organoids

MERCURIUS™
1536 DRUG-seq

Ultra-high-throughput perturbation datasets, large compound screens, and AI-ready screening-scale studies

Trusted by

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FAQ

MERCURIUS™ DRUG-seq is a transformative tool for compound screening and drug discovery, combining unbiased, ultra-high-content, and high-throughput compound screening with massively parallel and extraction-free transcriptomics. This metho d uses highly optimized and rigorously evaluated sample barcodes and unique molecular identifiers to tag the 3’ poly(A) tail of all mRNA molecules in a sample-specific manner during the first-strand synthesis step of cDNA library preparation.

The DRUG-seq protocol is designed to work with frozen cells and bypass RNA extraction. Thanks to the highly optimized lysis buffers for cell lysis of 2D cell cultures and organoid models, it efficiently generates library preps without prior RNA isolation.

Unlike the original DRUG-seq protocol, which relies on the use of template-switching oligos (TSO) and pre-amplification for the second-strand cDNA synthesis, the MERCURIUS™ DRUG-seq streamlines the workflow by performing the reverse transcription with a high-yield enzyme, thus eliminating the potential biases and duplication introduced with pre-amplification.

This optimized workflow not only simplifies the protocol but also delivers superior performance: higher mapping and gene detection rates.

MERCURIUS™ DRUG-seq stands out from standard RNA-seq methods by offering a high-throughput, cost-efficient, and streamlined workflow specifically designed for large-scale screening applications. One of the key differences lies in its sample multiplexing strategy: DRUG-seq allows multiple RNA samples to be barcoded and pooled at the earliest step of the protocol—right after cell lysis—so that the entire library preparation can proceed in a single tube. This significantly reduces both hands-on time and reagent costs.

In contrast, standard RNA-seq workflows typically require individual RNA extraction and processing for each sample, followed by separate library preparations. This makes them more labor-intensive, costly, and less scalable, especially when working with large numbers of conditions, compounds, or replicates—common in drug discovery pipelines.

MERCURIUS™ DRUG-seq is used for:

Drug discovery: Identifying new drug candidates and understanding how existing drugs work at a molecular level.

Mechanism of action studies: Understanding how drugs affect cellular pathways and gene regulation.

Drug repurposing: Identifying new uses for existing drugs based on gene expression changes.

Personalized medicine: Tailoring treatments based on individual genetic responses to drugs.

MERCURIUS™ DRUG-seq can be performed on various sample types, including: Cell lines, Primary cells, Organoids or Spheroids.

Validated cells lines

Cell line/Tissue Organism
HT1080 SMARCA4 KO Human
hTEC Human
iPSC microglia Human
MCF7 Human
HepG2_IGF1RKO Human
Beas-2B Human
dTHP-1 Human
iPSC derived cardiomyocytes Human
Endothelial Human
Hepatocyte Human
HEPG2 Human
Hepatocyte Human
SF9 Spodoptera
A549 Human
Breast Cancer (MCF7) Human
B lymphoblast MM.1s. Human
Hek293 Human
Cell line/Tissue Organism
HeLa Cells Human
U2-OS Human
Hek293 Human
dTHP-1 Human
AsPC-1 Human
PBMC (TCD4) Human
Skeletal muscle (LHCN-M2) Human
HepaRG Human
Macrophage (MV-4-11) Human
PBMCs (Blood) Human
Microglia Human
Fibroblast Like Synoviocyte donor 1502 Human
Fibroblast Human
iPSC-derived neuron Human
Human lung carcinoma epithelial cell line Human
Human breast epithelial adenocarcinoma cell line Human
Human liver hepatocellular carcinoma cell line Human
Human cardiomyocytes derived from induced pluripotent stem cells (iPSCs) Human

We require the cells/organoids to be washed in PBS to avoid interference with our proprietary lysis and reverse transcription.

The recommended range of input material is in the range of 5’000-50’000 cells.

Yes. Alithea offers MERCURIUS™ DRUG-seq as kits for in-house implementation and services for teams that want Alithea to run library preparation, sequencing, QC, and data delivery.

Ready to talk about your next RNA-seq study?

Tell us about your project and we will help you find the right approach.