Human biology is subject to billions of interacting components. TuringDB manages this complexity, offering auditable and explainable accelerated drug discovery, optimised clinical trials, and simulated biological systems.
Therapy responses vary based on individual biology, disease evolution, sex, exposures, nutrition, and more. This vast complexity results in frequent treatment failures.
A holistic approach demands multimodal data integration: omics, clinical data, EHR, and knowledge graphs. All of this can be represented visually.
Spatially & dynamically interacting biological components
View connections between omics, clinical, EHR, and knowledge data
Account for biology, disease evolution, and exposures
These systems need multilayer representation that can deal with every abstraction of biology. Our reasoning AI & graph engine analyses, interprets, and simulates the mechanisms underlying drug response in individuals and groups.
We build custom graph solutions for pharma and biotech companies with TuringDB Custom, unifying siloed data into actionable insights.
Unify siloed clinical, omics & trial data
Real-time insights at sub-ms speed
Built-in audit trail & compliance
Branch & simulate "what-if" scenarios
Power explainable AI & LLM grounding
Build-up or expand your internal AI capabilities
Predict drug effects on individual patient biopsies using multilayer graph models that capture cell-cell interactions, spatial relationships, and molecular pathways.
Multilayer models for hot vs cold tumours
Personalised response prediction
Root cause and critical event analysis
Spatial and temporal event prediction
Characterize & simulate mechanisms, synergetic effects, and drugs to increase safety & efficacy. Build rationale based on data and knowledge of mechanisms for new drugs or repurposed drugs.
Identify synergetic drug combinations
Map immune circuit interactions
Discover novel mechanisms of action
Predict drug safety & efficacy profiles
Integrate multimodal spatial data (10X Visium, IF Multiplex, H&E) to analyse cell-cell spatial interaction networks and tumour microenvironment dynamics.
• Cell-cell interaction mapping
• TME spatial analysis
• Multi-cohort validation
Identify and prioritise drug targets through automated reasoning paths with evidence, simulating biological responses to novel and repurposed drugs.
• 545+ drug candidates analysed
• Novel mechanism discovery
• Patient group stratification
Build causal graphs to analyse drug combinations and predict synergistic effects on downstream cellular interactions in responder vs non-responder patients.
• Immunotherapy combinations
• Logical reasoning paths
• Mechanism of action mapping
Build comprehensive knowledge graphs connecting genes, proteins, diseases, and compounds for faster target identification and pathway analysis.
• Multi-omics data integration
• Pathway analysis at scale
• Real-time hypothesis testing
Optimise patient recruitment and trial design by analysing complex relationships in clinical data and predicting adverse events.
• Patient cohort identification
• Adverse event prediction
• Trial site optimisation
Discover new therapeutic applications for existing drugs through deep graph traversals and mechanism of action discovery.
• Drug-disease relationship mapping
• Side effect similarity analysis
• Novel indication discovery
Analyse millions of biological entities and their relationships in real time. Run complex multi-hop queries on protein interaction networks, metabolic pathways, and disease associations without waiting.
Built with critical industries like healthcare in mind. Track every reasoning path, maintain full audit trails, and ensure explainable AI for regulatory compliance.
Run deep graph traversals and multihops on large graphs to simulate complex biology. Analyse cell-cell interactions, spatial relationships, and temporal dynamics at scale.
Deploy on-premises or in your VPC with full control over sensitive research data. Meet HIPAA, GDPR, and other regulatory requirements with built-in security features.
Join the leading biopharma companies using TuringDB to accelerate research and bring therapies to patients faster.