Aptamarkers

2. Stratification of patients within a disease

We use all of the information from the Aptamarker analysis across individuals to build a molecular space which we can observe clustering of the individuals. The identification of these clusters provides a basis for characterizing different pathophysiological processes that lead to the same phenotype. 

We can also include clinical variables such as comorbidities, sex and age as additional variables and add this information to the overall information space. 

Our capacity to convert Aptamarkers into simple qPCR tests also means that we can construct a scaffold of this molecular characterization space with a subset of Aptamarkers. This scaffold can then be used as a basis for patient stratification on a clinical level for diagnosis or treatment streaming. It requires considerable work to build the molecular characterization space, but once it is built future individuals can be positioned within it with a qPCR test with a minimal number of Aptamarkers. 

In the graph that follows we show an abstract example of such a space for any disease. The different colours could represent different aspects of a clinical variable such as age, or different outcomes from a common disease.