
Deep Genomics
Decoding the human genome to design life-changing RNA-based therapies.

Reimagining drug discovery by modeling cell behavior through high-dimensional AI.

Cellarity is a clinical-stage biotechnology company that leverages a proprietary AI-driven platform to design medicines based on cellular behavior rather than single molecular targets. By 2026, Cellarity has solidified its position as a leader in 'Digital Biology,' utilizing high-dimensional single-cell transcriptomics to map how disease disrupts cell states. Unlike traditional target-based approaches that focus on a single protein, Cellarity's architecture uses deep learning to understand the 'cell state transition'—the complex interplay of gene networks that define health versus disease. This allows for the discovery of small molecules that can reprogram diseased cells back to a healthy state. The platform integrates massive biological datasets with predictive algorithms, enabling the identification of novel therapeutic candidates across diverse therapeutic areas including hematology, metabolic diseases, and oncology. Their approach significantly reduces the biological uncertainty inherent in drug discovery by focusing on the fundamental unit of life: the cell. As a Flagship Pioneering company, Cellarity represents a paradigm shift toward systems-level pharmacology, where AI acts as the primary bridge between complex biological data and actionable drug leads.
Cellarity is a clinical-stage biotechnology company that leverages a proprietary AI-driven platform to design medicines based on cellular behavior rather than single molecular targets.
Explore all tools that specialize in predictive transcriptomics. This domain focus ensures Cellarity delivers optimized results for this specific requirement.
Uses deep generative models to define the vector between a disease cell state and a healthy cell state in high-dimensional space.
In silico modeling of how billions of molecules might interact with a specific cell's transcriptomic network.
AI models that map mouse or non-human primate cell states to human counterparts to improve translatability.
Ability to layer transcriptomic, proteomic, and epigenomic data into a single unified cell representation.
Unsupervised learning algorithms that identify novel disease drivers without pre-existing biological hypotheses.
Models off-target transcriptomic effects in healthy cell populations to predict side effects early.
Simultaneously optimizes potency, selectivity, and cell-state correction properties of a molecule.
Strategic therapeutic area alignment and project scoping.
Selection of relevant disease tissue and healthy control samples.
High-throughput single-cell RNA sequencing (scRNA-seq) of target tissues.
Data ingestion into the Cellarity Digital Cell platform.
AI-driven mapping of the high-dimensional disease state versus healthy state.
Computational simulation of chemical perturbations on the diseased cell state.
Identification of 'Cellarity Hits'—molecules predicted to reverse disease transcriptomes.
In vitro validation of computational hits in biological assays.
Iterative lead optimization using the AI feedback loop.
Selection of development candidates for clinical trials.
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"Highly regarded by industry analysts as one of the most innovative applications of AI in biology; praised for its potential to tackle 'undruggable' diseases."
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