DRUG-seq
How does the transcriptome respond?
HT-transcriptomics
10,000+ genes per well across 384-well plates, from cell culture to AI/ML-ready counts.
Functional Biology
The world leader in DRUG-seq. See how cells respond to every perturbation.
Transcriptomics, morphology, and custom assays. Library scale. Data built for machine learning.
- 384-well DRUG-seq plates per week
- 100×
- 384-well DRUG-seq plates per week
- DRUG-seq measurements released for open science
- 1B+
- DRUG-seq measurements released for open science
- Cell-types onboarded, including primary cells
- >80
- Cell-types onboarded, including primary cells
- layer on additional profiling and target specific readouts
- Multi-omics
- layer on additional profiling and target specific readouts
What we measure
5 readouts & models
Cell Painting
How does the cell change shape?
High-content imaging
Multiplexed morphological profiling with hundreds of features per cell.
Genetic perturbation
What happens without this gene?
Arrayed CRISPR KO
Arrayed whole-genome knockouts with weekly data delivery.
Chemical & oligo
What does this molecule do?
Compounds · siRNA · ASO
Full library screens, dose-response, MoA deconvolution, and on/off-target oligo screening.
Custom models & assays
Does it work in relevant biology?
iPSC · primary · reporter
iPSC neurons, primary immune cells, organoids, hepatocyte toxicity, and custom assays.
[ Offerings ]
Two ways in
Profile broadly with standardized readouts, or build an assay around your biology.
- [ Profile at scale ]1
Perturbation Response Profiling
Industrialized DRUG-seq and Cell Painting at library scale across primary human cell types.
You receive
Transcriptomic + morphological profiles
- [ Answer your question ]2
Specialized HTS
Custom phenotypic, target-engagement, and reporter assays built around your target and biology.
You receive
Validated hits, leads, and targets
- →Full library screens: 20K+ compounds
- →MoA deconvolution by pathway activation
- →Toxicity in HepaRG, organoid, and primary cells
- →siRNA/ASO on/off-target screening
- →Target engagement and nanoBRET PPI
- →Virtual cell models (VCPI)
[ AI/ML ]
Data built for virtual cell models.
A multilayer perceptron mechanism-of-action classifier trained on the ReFrame library (colored) predicts mechanisms for unannotated compounds from previous VCPI releases (grey).
ReFrame: 13,000 curated, clinically relevant compounds. Thanks to our collaborators at the Calibr-Skaggs Institute for Innovative Medicines at Scripps Research for providing the library.
Explore VCPI
Functional Biology — Service Overview
Perturbation Response Profiling and Specialized HTS in one deck