Liver Injury

Axiom accurately predicts human liver toxicity

20-25% of clinical trials fail due to drug-induced liver injury, Axiom wants to eliminate these failures

Inside our model: how it works

Axiom uses molecular structure, properties, and cell biology to predict clinical toxicity outcomes.

Proprietary data combined with the latest ML/AI methods

We combine the world's largest human liver dataset with the latest AI/ML methods to train highly accurate models.

Step 1

We’ve created the world’s largest primary human liver dataset

  • 115,000+ small molecules exposed to primary human liver cells.

  • High content imaging of key cell organelles paired with biochemical assays.

  • Learn more about Axiom's training set.

Step 2

We quantify biology with unprecedented precision

  • 10+ models of unique biology (confluency, ER-stress, mitochondrial toxicity, and more).

  • Bile canalicular networks, efflux/uptake transporters, steatosis coming soon.

  • Full, 8-point dose-response curves.

Step 3

Our models learn how chemistry affects biology

  • Molecules induce diverse cellular phenotypes.

  • Axiom's models learn which molecules induce which toxic cell phenotypes.

  • For a new molecule, our models identify its cellular phenotype and clinical toxicity risk, and how these vary with dose.

Step 4

Precise clinical risk assessment

  • Understand the relationship between human exposure and human toxicity.

  • Accurately compute the therapeutic index.

  • Reason about risk of adverse events.

Assess toxicity in a modern web application

Reason about clinical liver injury risk with powerful data visualization and predictions.

Liver Services

Axiom offers a variety of services for understanding drug induced liver injury.