Identification of pathological signatures is essential to diagnose the onset or advancement of a disorder. Our proprietary model is working to improve typical physician standards on phenotype-detection of neurodegenerative disorders.
In addition, using our longitudinal robotic imaging, we are finalizing a computer vision/AI model to detect phenotypes in the cells derived from our patient and healthy client donors. Collaborations are currently ongoing with "wet labs" to continue to run and improve our phenotype-identification model.
Identification of mutations at the genetic level, epi-genome modifications, and differential expression in the transcriptomics and proteomics of our patients and clients. Combination of this data, is allowing PDx scientists to find novel associations with neurodegenerative disorders, at orders of magnitude higher than previous approaches.
We have successfully established a genetic mutation analysis model that can detect the majority of ALS patients, and not found in our healthy control cohort. Our classifier model allows us to detect ALS at a sensitivity greater than 50%, at 99% Confidence Level.
We are working on associations between the multi-omics project to better understand and elucidate the pathobiology of neurodegenerative disorders such as, Alzheimer's disease and ALS.