Stress Resilience

Transforming Lives with AI and Real-World Data

Personalized medicine tailored to the nuanced, and often unique, genetic, biochemical, psychological, exposure and behavioral features in individuals has evolved tremendously in recent years. The use of emerging technologies and the generation of large real-world datasets in the genomics, proteomics, imaging and other fields along with the use of artificial intelligence, including algorithms based machine learning, helps clinical professionals find better prevention and treatment options for complex disorders.  

Stress is a major risk factor for a large number of mental disorders. However, there are many differences between individuals and their response to stress resilience and vulnerability. The development of stress-related disorders is linked to a dysregulation of the stress responsive hypothalamic pituitary adrenal (HPA) axis, where the mineralocorticoid receptor (MR) and the glucocorticoid receptor (GR) play an important role. Other  psychological and/or environmental factors, such as traumatic early life events, are also influential in an individual's stress response.   

OrigenDX generates and uses genomics with special emphasis on the HPA system and other biological and non-biological data sets, to analyze an individual’s risk for negative side-effects of stress. OrigenDX also uses AI and real-world mental health clinical database technology in combination with these biological datasets. This unique integration aids in the development of new and improved tools for early diagnosis, upstream prevention and personalized treatment options for stress-related disorders, with the ultimate goal to prevent damage caused by stress and to improve individuals’ functioning and mental resilience.