Build a closed discovery loop of AI-to-biology
Biology GPU
The experimental runtime for AI drug discovery
We’ve built the experimental modality that enables AI models to reason in causal human biology
Pathways seen in action
in space and time
computable for AI
LLM
Multimodal Disease Models
Chat with Cells
Experimental Reasoning Loop
Experimental Reasoning Loop
BioGPU
Visual Biology Model Runtime
Multiple cell types across diseases, conditions and perturbations
The Biology GPU
Transforming AI models into experimental self-driving discovery engines
Visual Biology Automation: Proprietary visualization modality that directly images biological pathways and mechanisms in action inside cells at AI scale
Experimental Biology Runtime: Large-scale experimental infrastructure that enables AI models to visually compute inside cells and reason experimentally about disease mechanisms
Visual Biology Model: Trained on more than 2 billion proprietary pathway images, designed to recognize active biological pathways in healthy and diseased cells. Its runtime can be deployed in a customer’s private cloud
Agentic Chat Loop: The BioGPU Agent connects AI models (LLMs) to the BioGPU infrastructure, creating an explainable reasoning loop grounded in real biology
Enabling the discovery of causal targets, mechanisms, and therapeutic modalities
Large Visual Biology Model
Generated from 25 disease models trained in real projects with Pharma
Total: 2B+ process visualizations
Visual mRNA Biology Model
Generated with mRNA biology regulatory visualizations mechanisms
Enabling the discovery of target modulators via mRNA biology
Visual Biology GPU Agent
LLM’s research partner for experimental reasoning inside cells
The functional biology modality that grounds AI in visual causal reasoning
A unified experimental imaging runtime connecting multiomics to intracellular biological activity at AI scale
Building disease models that map pathway connectivity and give AI cell-specific biological grounding and mechanistic insight into disease
Visual Computing
inside cells
inside cells
Biological Processes and Pathways
Partner
AI Disease
Model
AI Disease
Model
Visual Biology
Causal AI
Disease Model
Causal AI
Disease Model
Genomics
Transcriptomics
Proteomics
Pathology
Cellular morphology
What AI can do with the Biology GPU
Disease Signature & Target ID
Discover pathway signatures - compare cellular systems
Discover novel targets that modulate pathway signatures
Target Validation
Understand a target’s biological function
Compare and rank targets by pathway modulation
Hit Identification
Discover compounds with pathway selectivity
Compare clusters for their biological activity - de-risk programs early
Hit To Lead
Elucidate compound’s MOAs
Optimize activity on core pathways
Lead Optimization
Optimize chemistry in a visual biology loop - optimize pathway activity
Predict off-target effects
Preclinical Development
Visual computing toxicity panels
Compare biology across human and animal models
+ Additional use cases in mRNA biology with a specialized mRNA neural network
Partner with Anima to Build an
End-to-End AI-to-cell Stack
1
Biology GPU
2
Biology GPU Agent
See and compute on pathways inside real biology
3
Targets and Drugs
Identify disease driving pathways, novel targets and drugs that modulate the phenotype