Methods
Building the physical harness that teaches AI to connect lab experiments to human drug outcomes.
Methods
We experimentally measure the full life cycle of a drug, linking exposure and metabolism to cellular biology and human outcomes.
Methods
Scientists meticulously annotate and curate our experimental data to make it ready for AI training.
Methods
Every experiment is rigorously evaluated with Axiom's suite of proprietary quality control tools.
Data Readiness
Keeping track of all compounds
Ingestion Pipeline
Data across different assays
Model Evaluation
Grading model performance
Model Leaderboard
Tracking model performance
Image Segmentation
Mask & Quality Control
Methods
We extract early, subtle biological signals from our experimental data to predict human outcomes.
Methods
Our mechanistic reasoning agents use thousands of clinical reference molecules to translate subtle signals into actionable drivers of human risk.
Method
End-to-end clinical outcomes powered by integrated experimental data and AI-driven mechanistic reasoning.
Clinical Risk Assessment
Axiom generates end-to-end clinical risk assessments powered by integrated experimental data and AI-driven mechanistic reasoning.
Publications
Axiom's Data & Evidence
Counting cells can accurately predict small-molecule bioactivity benchmarks
Nature Communications
Modeling and Interpreting Multiple Readouts for Clinical Liver Toxicity Risk Assessment
Data
Using AI to Combine Exposure, Metabolism, and Liver Function to Model DILI in Modern Molecules
Talk
On AI Infrastructure in Biology
Blog
AI & Biotech: Accelerating Breakthroughs in Medicine
Talk
Goin' up the liver
Blog
Selling AI Products + Services to Big Pharma
Blog
A Shift from Animal Testing
Blog