LIT Analytics
AI-powered personalized mental health insights that accelerate treatment development
Introduction
LIT Analytics streamlines mental health drug development by using an AI-powered data engine to transform physical measurements and behavior patterns into objective measures of depression to find early and accurate signals of treatment effect.
Problem
Clinical trials in mental health are broken, with failure rates greater than 90%. The current technology used to assess a patient's mental health status is a subjective questionnaire that is highly variable and often does not capture a patient's true state of mind, making it difficult to discern the true effect of a drug during clinical testing.
Opportunity
We are developing an AI-powered data engine and predictive depression model trained on an extensive clinically validated dataset that allows for specific and measurable treatment responses. When used during clinical testing this will reduce variability and allow for smaller samples sizes leading to faster drug development while simultaneously improving clinical success rates by utilizing more objective tools to assess treatment effects.