BioGPU
Where AI Runs to Resolve Biology
Enabling AI models to reason inside cells through massive parallel visual biology experiments

Causal biology resolved across the discovery lifecycle

Understand the causal biology driving disease, the function of targets, and the effects of compounds.
Pathway
Resolution

Identify the pathways driving disease and distinguish them from adaptive or compensatory biology.

Target
Resolution

Understand what targets do, how they are regulated, and how they influence disease biology.

Compound
Resolution

Explain what compounds do in biology, why they succeed or fail, and how resistance emerges.

The biology runtime for AI.

BioGPU enables AI models to reason inside cells through massive parallel visual biology experiments.

BioGPU Agent

BioGPU Runtime

Massive parallel visual biology experiments

Visual Biology Tokens
  • Protein
    localization
  • Nuclear
    translocation
  • Phospho-
    signaling
  • Cytoskeletal
    dynamics
  • Mitochondrial
    state
  • RNA
    granules
  • Protein
    interactions
1000+
Experiments at each iteration
Cells
Millions of cells across diseases,
conditions and perturbations

Visual Biology Tokens

FRONT: THE STATEMENT
Textual statement of biological activity
VB-0001
SOD1 is abnormally enriched in the nucleus.
VB-0002
P-TDP-43 accumulates strongly in both cytoplasm and nucleus.
VB-0003
4EBP1 is phosphorylated across both nuclear and cytoplasmic compartments despite unchanged levels.
VB-0004
SRSF2 is strongly upregulated in the nucleus.
front
VISUAL BIOLOGY TOKENS
THOUSANDS OF TOKENS
produced per experiment
Across pathways, cell types, conditions and diseases
back
BACK: THE EVIDENCE
Dynamic visual evidence (Healthy vs Disease)
SOD1
H
D
P-TDP-43
H
D
4EBP1 (p)
H
D
SRSF2
H
D

Visual Biology Tokens enable AI agents to reason inside biology at scale

Introducing
Experimental reasoning inside cells

BioGPU enables AI models to design experiments, observe real cellular responses, and reason causally within the complexity of living systems.

  • Design hypotheses
  • Run visual biology experiments
  • Observe real cellular outcomes
  • Iterate and refine understanding
  • Resolve biology causally
Visual Biology Tokens

Foundational
pathway-image-to-text model

Converting visual biology into language AI can reason about.
PATHWAY IMAGES
Visual representations of biological reality
  • Protein
    localization
  • Nuclear
    translocation
  • Phospho-
    signaling
  • Cytoskeletal
    dynamics
  • RNA
    granules
  • Mitochondrial
    state
  • Protein
    interactions
  • Pathway
    responses
FOUNDATIONAL MODEL
Pathway-image-to-text
Trained on 2B+ pathway visualizations across 140 cell types and 25 diseases
TEXTUAL BIOLOGICAL STATEMENTS
Biological facts extracted from images
TDP43 accumulates in the cytoplasm.
mTOR signaling is hyperactivated.
Mitochondrial fragmentation increases.
RNA granule formation is enhanced.
Protein co-localization increases under perturbation X.
Nuclear translocation of TFs is enriched under condition Y.

BioGPU Agent

Chat with cells.

Experimentally resolving the biology of
pathways, targets, and compounds.

BioGPU Runtime

Massive parallel visual biology experiments

Resolution hypothesis

The agent generates and refines causal hypotheses across pathways, targets and compounds.

Design experiments

The agent designs visual biology experiments to test hypotheses at scale.

Run visual biology experiments

Experiments are executed in the BioGPU Runtime at massive parallel scale.

Resolve understanding

The agent analyzes results to resolve biological insights and reduce uncertainty.

The Biology Resolution Loop

Design, run and analyze visual biology experiments

BioGPU Runtime

executes visual biology experiments inside cells.

Visual Biology Tokens
The language that connects AI and biology.
Think
Plan
Execute
Learn
BioGPU RESOLUTION AGENT
BioGPU RUNTIME
MORE EXPERIMENTS
MORE UNDERSTANDING
MORE RESOLUTION

Scaling up disease resolution

EARLY UNDERSTANDING
Sparse, disconnected insights
Millions of visual biology experiments.
Millions of biological observations.
Building causal understanding.
RESOLVED NETWORK
Deep, causal understanding

BioGPU Agent - Driving the BioGPU runtime

BioGPU agent executes on the BioGPU runtime to resolve causal biology in ALS and discover novel targets

Biology
Resolved

BioGPU connects AI directly to large-scale biological experimentation, transforming millions of cellular observations into causal biological understanding.
TARGET BIOLOGY RESOLVED
Understand which targets matter, why they matter, and when they matter.
COMPOUND BIOLOGY RESOLVED
Understand mechanism of action, toxicity, resistance, and therapeutic potential.
DISEASE BIOLOGY RESOLVED
Understand the causal mechanisms and pathway architecture driving disease.

The Team Behind the Biology GPU

Expertise:
Visual biology
Software
A.I.
Computational Biology
Chemistry
Operations
Imaging

Visual biology Operations Imaging Iris Alroy PhD., Co-founder & CSO

Software A.I. Ivan Khodyrev PhD., Director, Software Development

Visual biology Imaging Shaul Barth PhD., Principal Scientist, Assay development & screen Team Lead

Visual biology Alik Demishtein PhD., Principal Scientist, Drug Discovery Team Lead

Operations Dana Radha MBA, Head of HR

Visual biology Amihai Karniel PhD., Principal Scientist, R&D Quality and Operations Lead

Visual biology Software Operations Pascal Brandys Board member

Visual biology Ephrem Kassa PhD., Principal Scientist, MOA & Target ID Team Lead

Visual biology Keren Kipnis PhD., Senior Research Scientist, Screen-Unit Manager

Software Operations Fred Voccola Board member

Visual biology Jasmine Khier PhD., Product Integration Specialist, Senior Scientist

Visual biology Ofer Bihari PhD., Senior Research Scientist

Visual biology Sari Trangle PhD., Senior Research Scientist

Visual biology Ben Bar-Sadeh PhD., Senior Research Scientist

Visual biology Irit Reichenstein PhD., Senior Research Scientist

Visual biology Artem Tverskoi PhD., Senior Research Scientist

Visual biology Adi Amar-Schwartz PhD., Research Scientist

Software Operations Miki Shvo CISO & AWS Admin

Visual biology Tamar Frankovits PhD., Research Scientist

Chemistry Luba Ischakov Simhaev PhD., Senior Computational Chemist

Chemistry Andrew Brown PhD., Associate Principal Scientist, Medicinal Chemist

A.I. Chemistry Eitan Margulis PhD., Computational Chemist

Visual biology Racheli Rimmer M.Sc., Senior Research Associate

Visual biology Alon Parsai M.Sc., Senior Research Associate

Visual biology Linoy Vaturi B.Sc., Senior Research Associate

Chemistry Shuyu Chu PhD., Associate Principal Scientist, Medicinal Chemist

Visual biology Ana Miriam Salama M.Sc., Senior Research Associate

Computational Biology Shaked Bergman PhD., Lead Computational Biologist

Visual biology Naama Slonim M.Sc., Senior Research Associate

Visual biology Ziv Landau M.Sc., Laboratory Supervisor

Visual biology Alisa Lysak B.Sc., Research Associate

Visual biology Dana Kadosh-Kariti M.Sc., Senior Research Associate

Software Nir Katz Software QA Manager

Visual biology Yifat Weiss M.Sc., Senior Research Associate

Visual biology Claudia Roussay Maggi M.Sc., Research Associate

Software Mikhail Usik M.Sc., Senior DevOps Engineer

Operations Linda Murikkattu M.Sc., Business Development Executive

Software Aleksei Mushegov Senior Frontend Developer

Software Evelyn Popok B.Sc., Backend Developer

A.I. Imaging Nitsan Elmalam M.Sc., AI Researcher

Computational Biology Odelia Goldberg-Nakar PhD., Senior Research Data Analyst

Software Gilad Livne Senior Backend Developer

A.I. Imaging Yael Elkin M.Sc., AI Data Scientist

Software Anton Akinin B.Sc., Backend Developer

Computational Biology Luis Alejandro de Haro PhD., Bioinformatician

Software Tiferet Gan B.Sc., QA Engineer

Software Tamir Oulu UI/UX Developer

Operations Ronit Cohen Financial Operations Manager

Operations Stav Yohanan BA, Office Manager



Get started with your Biology GPU

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