We combine cutting-edge machine learning and biology to identify novel biomarkers.

Biomarkers

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AI-powered biomarkers

We apply AI to multimodal, KOL-defined data to subtype patients and identify novel biomarkers to inform drug discovery, de-risk clinical trials and develop and deploy diagnostics in clinical practice.

Multimodal

to capture the full complex picture of the disease.

Interpretable

to extract key biological insights from heat maps.

Clinically validated

to ensure clinical utility by leaders in the field.

Multimodal

to capture the full complex picture of the disease.

Interpretable

to extract key biological insights from heat maps.

Clinically validated

to ensure clinical utility by leaders in the field.

Our AI-powered orthogonal approach

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We apply interpretable AI to multimodal patient data and pioneer novel technologies such as histogenomics and spatial omics to discover AI-powered biomarkers.

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Stratification (predictive) biomarkers

These biomarkers predict the best treatment for each patient by analyzing subgroups of good and bad responders. → To better predict the response to treatment, create surrogate markers and to steer research for future targets.

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Risk-score (prognostic) biomarkers

These biomarkers predict the course of the disease in a patient (outcome, overall survival, metastatic relapse). → To inform therapeutic decisions, accelerate clinical trial enrolment and design more accurate translational and early-stage trials.

Find out more

Screening (diagnostic) biomarkers

These biomarkers help us identify patients with a particular disease characteristic. → To define and accelerate clinical trial enrolment.

Find out more

Stratification (predictive) biomarkers

These biomarkers predict the best treatment for each patient by analyzing subgroups of good and bad responders. → To better predict the response to treatment, create surrogate markers and to steer research for future targets.

Find out more

Risk-score (prognostic) biomarkers

These biomarkers predict the course of the disease in a patient (outcome, overall survival, metastatic relapse). → To inform therapeutic decisions, accelerate clinical trial enrolment and design more accurate translational and early-stage trials.

Find out more

Screening (diagnostic) biomarkers

These biomarkers help us identify patients with a particular disease characteristic. → To define and accelerate clinical trial enrolment.

Find out more

Stratification Biomarker

Risk Score Biomarker

Case study

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Impact

Impact

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Biopharma

High-value subgroups

BioPharma companies can use this model to select high-value subgroups of patients that are most likely to respond to the ICI being tested. This improves the statistical power of the trial.

Trial optimization

This also results in better selection of trial participants, success rates across trial phases and ultimately regulatory approval and more precise marketing.