With multi-omics as the critical evidence, mProbe has endeavored to interpret that evidence against a proprietary, vast clinically annotated, library of phenotypes using artificial intelligence.
In the same way the Human Genome Project scientists came together to catalog how a specific segment related to a specific genetic expression, we are cataloging how protein and metabolite expression relates to a disease, risk of a disease, progression of a disease and response to an intervention. The availability and application of artificial intelligence and advanced data science now make it possible for us to recognize those patterns using mass spectrometry on blood samples.
The results are foundational for truly personalized health and precision medicine.
Disease Risk Model
Annually new medical records
Our combination of blood, tissue and electronic medical records library on tens of millions of lives and tens of thousands of samples puts us in a unique position to recognize phenotypical patterns. That means we can predict with great accuracy probabilities of having or developing disease in near term outcome windows,
We take laboratory results and medical record data from individuals. The machine looks for patterns to compare against similar individuals in the data and return results on likely disease, disease onset, progression and intervention effectiveness.
That means providers can better individualize care, reduce potential side effects and improve outcomes. Pharmaceutical companies can better target medications for cohorts and monitor effectiveness with subsequent assays.