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Our client is bringing new therapeutics to market for neurobehavioral disorders and needed a better way to assess patients with depression and anxiety based on video and audio content. A platform was needed to enable the discovery of behavioral biomarkers to support patient stratification for clinical trials and to assess the efficacy of treatment.
We partnered with the client’s data science and software engineering teams to design and build a platform to use machine learning to improve the assessment of patients with depression and anxiety. We engineered features from time series of audio and video data, via a mobile app, to train a model for predicting clinical outcomes. Improved quantification via behavioral biomarkers will enhance the stratification of patients for trial enrollment and accelerated assessment of therapeutic response.
