Columbia Technology Ventures

Detection tool for identifying individuals at high-risk of developing major depressive disorder

This technology is a screening tool for identifying individuals with increased risk of developing major depressive disorder (MDD).

Unmet Need: Early detection of highest risk population for MDD

Major depressive disorder (MDD) is the leading cause of disability worldwide, affecting over 300 million people. Development of an early detection test, and subsequent implementation of preventive interventions could help reduce the worldwide prevalence of MDD and associated economic burden.

The Technology: Method for identifying individuals with high-risk for MDD using PET imaging

This technology is a screening tool for detecting individuals who are most susceptible to developing MDD, and allows for targeted preventive interventions by identifying the children of parents who carry the endophenotype for depression. Using positron emission tomography (PET), this technology quantifies serotonin 1A receptor binding potential and compares results to a predetermined threshold to distinguish between individuals with and without MDD. Machine learning-based, multivoxel pattern analyses are then applied to accurately classify high- and low-risk individuals. This technology may reduce the prevalence of MDD by enabling early preventive intervention and can also be used to track the efficacy of treatment.

This technology has been validated in a pilot study of human subjects with MDD, high-risk of MDD, and healthy volunteers.

Applications:

  • Identifying individuals at high-risk for MDD
  • Method for diagnosing depressive disorder
  • Identification of patients in need of preventative intervention for MDD
  • Monitoring treatment efficacy

Advantages:

  • Early-detection
  • Screening and stratification of individuals based on risk of developing MDD
  • Minimally invasive
  • Can facilitate early preventative intervention for MDD
  • May potentially reduce economic burden of MDD
  • Minimizes burden on healthcare professionals by emphasizing patients that need immediate intervention
  • More individualized approach to treatment
  • Can detect patients with MDD who discontinued treatment

Lead Inventor:

J. John Mann, M.D.

Patent Information:

Patent Status

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