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Finding better treatments

Our unique approach powers an Innovation Engine creating new treatment opportunities for precision biopharma and healthcare.

We generate the deepest understanding of the biology driving chronic diseases, stratifying patient populations at an unprecedented resolution to define new subgroups of patients.

With these insights we discover novel drug targets, drug repositioning candidates, and biomarkers to identify the patients who will benefit from them.

Finding better ways to treat disease-min

Creating more personalized therapeutic opportunities from concept to clinic

Chronic diseases, such as dementia, diabetes, cardiovascular and autoimmune disorders, account for over 80% of healthcare spending.

However, they haven’t benefited from advances in genomic medicine as much as cancer or rare diseases because they are caused by a more complex interplay of multiple genes and biological factors.

People with a chronic disease may share a diagnosis, but have different causes of disease and respond to different treatments.

Multiple biological mechanisms can lead to the same clinical symptoms. Depending on which mechanism a drug targets, different treatments will be more successful in some patients than others.

The challenge for biopharma and healthcare is understanding which targets and drugs will work for which subgroups of patients.

We generate patient stratification biomarkers to deliver these precision medicine insights across dozens of chronic diseases.


Novel drug targets and indication extension opportunities with patient stratification biomarkers


Biomarkers of drug response to identify patient responders and enrich clinical trials


Diagnostic biomarkers and combinatorial risk scores


Clinical decision support and personalized digital health tools

Generating the deepest disease biology insights

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Combinatorial analytics

Our concept of chronic disease is different from traditional genomic approaches. Instead of looking for variants in single genes to explain disease, we analyze how interactions between multiple, relatively common variants, and other external factors come together to trigger disease processes.

Understanding the non-linear impact of these interactions allows us to perform high-resolution patient stratification, revealing how different aspects of disease biology affect subgroups of patients and enabling us to identify novel drug targets tailored to these patient subgroups.

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We’ve now run over 40 chronic disease datasets through our PrecisionLife® combinatorial analytics platform, and we’re analyzing 2 more every month. Our studies have generated deep insights into the mechanisms underpinning every one of these diseases.

We’ve discovered hundreds of new biomarkers that identify clinically relevant patient subgroups who share a disease mechanism, with novel drug targets and indication extension opportunities for treating them. All of these proprietary and protectable insights are stored in our DiseaseBank repository.

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