Patient stratification biomarkers

Mechanism-based biomarkers

At the heart of our approach are our mechanistic biomarkers.

Our biomarkers stratify clinically relevant patient subgroups by causal biology of their disease and/or treatment response.

From this stratification we can accurately map patients to drug targets, clinical trials, and treatments with unprecedented genetic evidence.

We've discovered mechanism-based biomarkers for all clinically relevant patient subgroup in over 60 diseases and their endotypes.

Improving disease prediction, diagnosis and treatment

De-risking drug discovery, development, and launch

Mapping patients to the right clinical trials and treatments

In clinical development, our biomarkers enable the design of faster, smaller clinical trials that are more likely to succeed, enriched with 'super responders' to treatment.

During discovery, selecting targets supported by our patient stratification biomarkers yields new insights into the target’s product profile, prevalence, druggability, clinical efficacy, and market opportunity.

Post-approval, our biomarkers support launch and market adoption of new products through their reduction to practice as genotypic tests that rapidly identify the patients who will benefit based on their underlying disease biology.

Reduced to clinical practice

Our biomarkers are reduced to clinical practice as highly-scalable, low-cost and non-invasive precision medicine tests based on the Axiom genotyping array.

These tests rapidly determine an individual's disease risk and mechanistic cause of disease. Their use cases include:

Optimizing clinical trial design and patient recruitment
Screening populations to identify at risk patients
Enabling fast and accurate differential triage of patients in clinic
Guiding diagnostic decisions and treatment selection
Supporting market adoption as complementary diagnostic tools

Mechanism-based patient stratification biomarkers accurately predict patient subgroups even in diseases with no previous genetic associations.

An example is our hypothesis-free analysis of ME/CFS (myalgic encephalomyelitis / chronic fatigue syndrome), a highly heterogenous disease that is debilitating for millions of patients, costing billions of dollars.

30 years of international research had yielded no effective diagnostic tests, disease modifying treatments, or reproducible genetic associations with ME/CFS.

Then, a recent PrecisionLife study found 14 novel genetic associations, enhancing disease understanding and enabling mechanistic stratification of it's biology for the very first time.

In the figure below, the green patient subgroup (27% of cases) was found to have a specific fatigue presentation due to defects in mitochondrial respiration. Only ME/CFS patients in this group will respond to a drug targeting that gene.

Patients with other disease mechanisms will respond to different drugs. For example, the blue group whose ME/CFS is mediated by genes involved in neurotransmitter precursor transport and show symptoms that include cognitive impairment.

These findings highlight how mechanistic stratification and the biomarkers to identify the right patients is essential for improving drug development and healthcare.