Detecting Rare Diseases Early With The Help Of AI

Genomic insights through next-generation phenotyping (NGP)

  • Yael
    Diagnosed at 24 months
    HNRNPH2 gene mutation
     
     

We use artificial intelligence to detect physiological patterns that reveal disease-causing genetic variations. With the world’s largest network of clinicians, labs and researchers creating one of the fastest growing and most comprehensive genomic databases, FDNA™ is changing the game for precision medicine by detecting rare diseases early with the help of AI.

The Problem

 

Cracking the Genetic Code of Disease
Genetic code is at the core of most human diseases—whether in-born genetic errors that cause cancer, autism or other rare diseases, or genetic pathways that affect biological functions.


 

The Unseen Influence 
Every human has thousands of genetic variations and errors that may affect their health. Many of the diseases caused by these variations remain undiagnosed, or will not manifest until later in life.


An Interpretation Challenge
Despite next-generation sequencing (NGS) becoming more available and affordable, the odds of finding a diagnosis through use of these technologies is limited to approximately 25% due to difficulty in identifying which genetic variants are clinically relevant.


Limited Data Means Limited Opportunity
A person’s genetics can predict what therapeutic approach is best for them; however, limited data linking gene variations to therapeutic success limits the scope of this precision medicine approach.

The Solution

FDNA™ is analyzing the world’s most comprehensive database of genetically relevant phenotypic information, crowdsourced from clinicians, labs and researchers. This real-world data, along with FDNA™’s next-generation phenotyping (NGP) technologies, are solving the biggest problems in health.

  • Clinicians and labs can now detect physiological patterns that correlate to disease-causing genetic variations.
  • Researchers can now discover new clinical signs, symptoms and genes that can be used as disease-predicting biomarkers.
  • Labs and bioinformatics organizations can now access the data needed to develop, test and market precision medicines for patients globally.