A living digital twin of the cell.
CytoMind builds dynamic, context-aware digital twins of human cells — integrating multi-omics, in-silico biology and AI to simulate, predict and optimise cellular behaviour before a single experiment.
Integrate biology. Simulate behaviour. Optimise the answer.
Genomics, transcriptomics, proteomics, metabolomics and epigenomics, plus context — cell type, tissue, disease and treatment.
Mechanistic, dynamic, multi-scale models that behave like a real cell over time rather than a static snapshot.
Predict drug response and toxicity, identify and validate targets, screen compounds virtually.
Causal inference identifies drivers rather than correlations — an answer a scientist can interrogate.
Prioritise the candidates worth the wet-lab cost, and discard the rest early.
Built for transformation.
Multi-omics integration
Genomics to epigenomics, unified at scale.
In-silico cell simulation
Mechanistic, dynamic, multi-scale models of cellular processes.
AI & machine learning
Prediction, optimisation and decision intelligence.
Predictive analytics
Drug responses, biomarkers and novel targets.
Drug discovery
Identify and validate targets faster.
Virtual screening
Prioritise and optimise compounds in silico.
From the lab bench to the clinic.
Drug discovery
Prioritise targets and compounds virtually, before costly wet-lab work.
Disease research
Simulate mechanisms and uncover biomarkers in context.
Personalised therapy
Model an individual’s biology against their twin to tailor safer, more effective treatment.
Preventive health
Trajectory simulation that predicts and guides, rather than reacting.
Partner with the Virtual Cell Platform.
For drug discovery teams, disease research groups and institutions building on the engine.