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Patient-centered population health

We’re using our unique understanding of the factors driving disease for different patient subgroups to build a new generation of precision medicine tools.

Combinatorial risk scores enable earlier and more appropriate targeted interventions to prevent the development of chronic diseases.

Our CRS accurately assess the personal risk level and factors for a patient:

  • Keeping people healthier for longer and avoiding the development of the worst symptoms
  • Giving a more accurate and informed diagnosis
  • Providing insights into the underlying causative mechanisms for disease in an individual patient
  • Allowing targeting of resources towards people at risk of the most serious forms of disease
  • Helping select the most effective treatment options for an individual based on their biology

Avoid the limitations of polygenic risk scores

Polygenic risk scores (PRS) assume that SNP contributions are independent of each other, work the same in every patient, and can be added together.

Unfortunately, none of those assumptions work well in complex polygenic chronic diseases.

Chasing ever rarer variants in founder populations that are often biased towards European ancestries, to add more SNPs with infinitesimal power to a PRS, deprives the models of explanatory value and makes them less transferrable between populations with different ethnicities.

Combinatorial risk scores

Our CRS take full advantage of the non-linear impacts of combinations of genetic, clinical, and epidemiological features, enabling high-resolution patient stratification that describes the different disease etiologies for different patient subgroups.

By understanding the impact of all the factors driving disease in a specific patient we more accurately predict their personal risks, prognoses, and likely therapy response.

Design more accurate and personalized risk models for chronic diseases

Enable earlier and more appropriate targeted interventions to prevent the development of chronic diseases.

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