Cytos Multiomics Workflow Maps a Single Cell at Once

Biotech company Element Biosciences has started shipping Cytos, and the Cytos Multiomics Workflow promises to do in a single automated run what once took a bench full of instruments: read a cell's gene guides, its shape, its proteins and its entire transcriptome at once. The launch, announced in a statement dated October 19, 2026, targets CRISPR screening and drug discovery labs that have long been forced to choose between rich imaging data and deep molecular data, according to the company's announcement carried by Business Wire.

The pitch is scale. Cytos captures guide RNA, cell morphology, protein expression and the whole transcriptome from the very same single cell in one experiment, then links a genetic perturbation directly to everything that happened as a result. Setup takes as little as thirty minutes of offboard preparation before the run consolidates everything into one automated pass on the company's multiomics sequencing system. The workflow is available to order now, and the company will show more of it at a virtual showcase in early November, according to the release text.

Four readouts from the same cell

Until now, screening forced a trade-off. Researchers could choose imaging for rich visual data or sequencing for deep molecular data, but never both from the same cell at the same moment. The Cytos Multiomics Workflow eliminates that split: imaging, sequencing and protein analysis run together, generating a complete multimodal picture of a cell's biology that had not been achievable before. Under the hood it is built on the company's Direct In Sample Sequencing technology, and it represents the next generation of an earlier assay the firm developed for pooled screening.

Early users are already pointing to the gap it closes. Lucas Pelkmans, a professor of systems biology at the University of Zurich, said the multimodal view provides the high-dimensional readouts needed to train AI models that can resolve how a drug works, predict complex cellular responses, and design molecules with the desired biological activity. Sejla Salic-Hainzl, chief technology officer at bit.bio, added that imaging had been the missing readout in pooled CRISPR screening, and that layering transcriptomics and a protein panel on top of imaging in one experiment is what makes the approach powerful for complex human cell types.

Why drug hunters and AI labs are watching

The bigger story is what this data unlocks. AI-driven drug discovery runs on training data, and the scarcest input has been causal data: proof that changing a gene actually caused the observed effect, rather than a correlation reconstructed after the fact. Because the Cytos Multiomics Workflow natively links the genetic guide, the transcriptome, proteins and morphology in the same cell, the data arrives causal by construction. As Element Biosciences chief executive Molly He put it, that closes the loop between experiment and model: run it, learn from it, design the next one. Scientists get to ask bigger what-if questions, and the answers arrive faster.

The same workflow extends beyond basic research. The company says it can resolve a compound's efficacy, dose response and mechanism of action from the same treated cells, and that it applies to toxicity screens and other phenotypic assays without reconfiguring the setup. Tilmann Buerckstuemmer, chief scientific officer at Myllia Biotechnology, said the addition of high-performance imaging as a readout lets his team explore areas of biology they simply could not reach before, and lets customers assess how genetic changes alter cell shape and disease biomarkers, generating fresh hypotheses for drug targets.

For readers, the payoff is indirect but real. Better screening tools mean candidate medicines fail earlier and succeed more often, which is one of the quietest ways new treatments get cheaper and faster to develop. No single instrument will cure anything on its own, but each time the gap between a genetic tweak and its full cellular consequence gets smaller, the odds improve that the next breakthrough therapy started as a what-if question asked in a lab the Cytos Multiomics Workflow is built for.

There is a counterweight worth keeping in mind. The announcement says the workflow brings capabilities once requiring multiple vendors within reach of labs of any size, but it discloses no price, and the run still depends on the company's own multiomics system. If the economics only work for well-funded institutes, the democratization story will be thinner than the marketing suggests. Still, the direction of travel is clear: single-cell tools are collapsing multiple instruments into single runs, a trend we have been tracking across biotech, from new T-cell therapies to the instruments behind discoveries like the starless cloud that could be a dark galaxy and Webb's first map of an alien world's true shape.