Alithea Genomics introduces early access program for MERCURIUS 1536 DRUG-seq

Alithea Genomics has launched an early access program for MERCURIUS™ 1536 DRUG-seq, an ultra-high-throughput transcriptomics kit that enables drug discovery teams to generate transcriptome-wide compound-response data directly from 1536-well plates.

The new solution is designed for pharmaceutical and biotechnology discovery teams that need to understand compound-induced biological responses at screening scale, helping to accelerate therapeutic programs and improve decision-making in early drug discovery.

Addressing the need for transcriptomics at screening scale

Pharmaceutical R&D teams can now screen large compound libraries with increasing speed and automation, but they often rely on narrow assay endpoints that indicate whether a compound has an effect without explaining the underlying biology.

Transcriptomics can provide this deeper biological context, yet it has frequently been too costly, complex, or low-throughput to apply across large screening campaigns.

MERCURIUS 1536 DRUG-seq is designed to close this gap by enabling transcriptome-wide gene expression profiling directly from 1536-well plates. This allows researchers to generate standardized biological response data across compounds, concentrations, time points, and cellular models, supporting more informed compound prioritization and mechanistic insight.

Workflow optimized for 1536-well plate screening

The new kit extends Alithea’s MERCURIUS DRUG-seq platform to 1536-well workflows. Cell lysis and barcoded reverse transcription are performed directly in the 1536-well culture plate, after which all 1536 samples are pooled into a single tube for downstream library preparation.

This miniaturized, pooled workflow is designed to:

• Reduce hands-on time
• Support automation in high-throughput screening laboratories
• Limit batch effects across large experiments
• Preserve the depth and biological resolution required for transcriptomic screening

MERCURIUS 1536 DRUG-seq is compatible with Illumina^®, Ultima Genomics, and AVITI™ sequencing instruments and is available in a 1536-prep format through Alithea Genomics’ early access program.

Applications in drug discovery and AI-driven research

MERCURIUS 1536 DRUG-seq is intended for discovery teams working on:

• Large-scale compound profiling
• Mechanism of action discovery
• Toxicity assessment and mechanism-specific toxicity profiling
• Benchmark dosing studies
• Compound prioritization
• Generation of structured perturbation datasets for AI-driven drug discovery

The technology also provides a complementary molecular readout for high-content imaging workflows, including Cell Painting, enabling integrated phenotypic and transcriptomic analyses.

Performance data and validation results

Early performance data for MERCURIUS 1536 DRUG-seq demonstrate:

• High demultiplexing efficiency, with more than 96% of reads assigned to individual samples
• Consistent gene detection across 1536-well plates
• Robust capture of compound-induced transcriptional responses

In internal validation studies, the kit detected more than 12,000 genes at only 0.7 million reads per sample. The technology also showed reproducible differential expression signatures across independently processed plates and resolved mechanism-specific toxicity responses across compounds.

Practical requirements for miniaturized screening formats

MERCURIUS 1536 DRUG-seq is designed for use with cell lines and primary cells in 1536-well assay plates. The kit requires 400 to 1,000 mammalian cells per well and supports approximately 2.5 hours of hands-on library preparation time.

The workflow does not require a 1536-well thermocycler, helping to remove a common practical bottleneck for laboratories operating in highly miniaturized screening formats.

Enabling AI-ready transcriptomic datasets

By generating large, standardized compound-response datasets, MERCURIUS 1536 DRUG-seq supports the development of AI and machine learning models for target discovery, mechanism prediction, toxicity forecasting, and compound optimization.

“AI-driven discovery depends on the quality, scale, and structure of the biological data used to train and interpret models,” said Frederik Decouttere, CEO at Alithea Genomics. “With MERCURIUS 1536 DRUG-seq, researchers can generate large transcriptomic datasets that connect chemical perturbation to biological response across screening-scale experiments.”

Want the latest science news straight to your inbox? Become a SelectScience member for free today>>