Available Technology
Software for early detection and assessment of depression
Technology:
Software
Markets Addressed
The advancement in psychiatry and clinical neuroscience is hindered by the heterogeneity of psychiatric disorders and by difficulties in defining and characterizing the phenotype under investigation. A core symptom in Major Depressive Disorder (MDD) is anhedonia, the inability to enjoy pleasurable activities and experiences. Anhedonia is considered one of the most promising MDD endophenotypes to investigate neurobiological correlates of MDD. Recent evidence suggests that anhedonia may result from abnormal functioning of the Brain Reward System, the neurobiological system that mediates pleasure and motivation, in depressed patients. Anhedonia is not only critical for identifying subjects at risk for psychopathology, but has also been found to predict treatment outcome and relapse rate for several mental disorders.
The incidence of mental illness in the United States affects about 22.1 percent of adults annually or 44.3 million people (NIMH). Approximately 1 in 4 (22.10%) or 60.1 million people in the US are afflicted with at least one type of mental illness.
Innovations and Advantages
The invention is a software that objectively and reliably assesses anhedonia. This assessment tool involves a computerized task with a differential reinforcement schedule that utilizes a reward (such as money) to provide an objective, laboratory-based measure of hedonic capacity. The software offers a cost-effective assessment/screening method for (a) developing new anti-depression treatments, through accurate assessments of treatment responses of patients to test compounds; (b) patient pre-selection prior to clinical trials, through early predictions of test subjects’ treatment responses; (c) monitoring treatment responses of depressed patients who are on antidepressant therapies; (d) identifying sub-clinically depressed patients who may be benefited from early treatments.
• Software for assessing anhedonia, the inability to enjoy pleasurable activities and experiences
• The software can help to identify subjects at risk for depression, and to predict treatment outcomes and relapse rates
• Useful for patient stratification and pre-selection in clinical trials
• To identify sub-clinically depressed patients who may benefit from early treatments
Additional Information
Publication:
Pizzagalli, D.A., Jahn, A.L., O'Shea, J.P. (2005). Toward an objective characterization of an anhedonic phenotype: A Signal-detection approach. Biological Psychiatry, 57, 319-327.
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Inventor(s):
Pizzagalli, Diego A.
Categories:
For further information, please contact:
Debra Peattie, Director of Business Development
(617) 495-3067
Reference Harvard Case #2633