AI-Clinical Outcome Assessment (AI-COA) for Depression: an Innovative Drug Development Tool
Depression is a major public health issue affecting hundreds of millions globally, with significant implications for suicide risk and overall health. Reliable assessment of depression severity is crucial for the development and validation of new medications, yet the current FDA-approved scales, the Hamilton (HAM-D) and Montgomery and Åsberg (MADRS) Depression Rating Scales, are limited by their subjective nature and lack of standardization. These limitations introduce measurement error and contribute to the particularly high failure rate of Phase 3 clinical trials in depression. The Depression AICOA®, a novel multimodal AI-based tool, has been developed to address these challenges by providing a more reliable and standardized method for assessing depression severity. Utilizing a computational approach that objectively measures multimodal features of depression severity, AICOA® has shown high concurrent reliability with HAM-D scores. Recognizing its potential, the FDA has recently accepted AICOA® into its Innovative Science and Technology Approaches for New Drugs (ISTAND) Pilot Program, marking it as the first AI and Digital Health Technology, as well as the inaugural Neuroscience project in the program. This SBIR project aims to advance AICOA® to regulatory qualification and a commercially ready stage through extensive clinical validation. The project will support the technical development and clinical validation of AICOA® through a comprehensive study. The outcomes of this research will enable AICOA® to progress with FDA qualification as a Drug Development Tool, paving the way for more precise and reliable depression assessments in clinical trials, ultimately leading to the development of more effective treatments.
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Imported from NIH RePORTER | Grant 1R44MH140727-01.
Open sourceOverview
Grant agreement 1R44MH140727-01
Open sourceDepression is a major public health issue affecting hundreds of millions globally, with significant implications for suicide risk and overall health. Reliable assessment of depression severity is crucial for the development and validation of new medications, yet the current FDA-approved scales, the Hamilton (HAM-D) and Montgomery and Åsberg (MADRS) Depression Rating Scales, are limited by their subjective nature and lack of standardization. These limitations introduce measurement error and contribute to the particularly high failure rate of Phase 3 clinical trials in depression. The Depression AICOA®, a novel multimodal AI-based tool, has been developed to address these challenges by providing a more reliable and standardized method for assessing depression severity. Utilizing a computational approach that objectively measures multimodal features of depression severity, AICOA® has shown high concurrent reliability with HAM-D scores. Recognizing its potential, the FDA has recently accepted AICOA® into its Innovative Science and Technology Approaches for New Drugs (ISTAND) Pilot Program, marking it as the first AI and Digital Health Technology, as well as the inaugural Neuroscience project in the program. This SBIR project aims to advance AICOA® to regulatory qualification and a commercially ready stage through extensive clinical validation. The project will support the technical development and clinical validation of AICOA® through a comprehensive study. The outcomes of this research will enable AICOA® to progress with FDA qualification as a Drug Development Tool, paving the way for more precise and reliable depression assessments in clinical trials, ultimately leading to the development of more effective treatments.