Abstract - Remote Monitoring and Detecting of Tardive Dyskinesia for Improving Patient Outcomes Tardive dyskinesia (TDD) is a common debilitating side effect of antipsychotic use. Characterized most notably by involuntary facial movements such as grimacing, involuntary lip, mouth, and tongue movements, and eye blinking, TDD is difficult to treat and potentially irreversible. Psychiatrists and other mental health professionals are acutely aware of the impairment and disability experienced by patients who develop TDD. Early detection of TDD is critical so that appropriate interventions can be instituted. What interventions are implemented is intimately tied to knowing the patient’s medication adherence. It is difficult for the most qualified diagnosticians to devote the 20-25 minutes of in-person time at the 4 to 6 times per year frequency necessary to provide every patient the 1) “active monitoring,” 2) discussion of results, 3) changes to medication and instructions expected with the urgent demands on every mental health professional today. This is increasingly challenging with the increase in telemedicine and patient populations and decreasing human resources due to the pandemic. Unfortunately, despite professionals’ best efforts, it is often too late in the process and the involuntary movements are permanent. Currently, there are 200,000 individuals taking anti-TDD medications costing $60K and $105K annually and this is increasing rapidly each year. A method for automatic TDD detection and accurate adherence would enable timely intervention and avoid patient stigma, lower quality of life, and expensive ongoing treatment for permanent TDD. Antipsychotic prescriptions exceeded 50 million in 2020 and the reported prevalence of TDD is between 13% and 24%. Risk grows with advancing age, off-label uses, and chronic exposure to antipsychotics. Therefore, prevention and early detection are key to managing TDD. However, current methods for monitoring patients require observation of patients at infrequent in-person visits or self-reporting by vigilant but undertrained patients and their families. Therefore, strong market potential exists for an automated remote adherence monitoring and TDD detection system. Our go-to-market strategy is presented in the commercialization plan. This Phase II project proposes to leverage existing telepsychiatry and video interview data gathering technologies that in Phase I demonstrated up to 77% discrimination in categorizing individuals with TDD compared to a 3- person panel of trained clinical professionals evaluating the same video materials. Based on a power analysis of the Phase I data, we propose here to extend collection and analysis of an additional 300 video recorded AIMS and 5-minute video interviews with individuals taking anti-psychotic medications. Half of the interviews will be with individuals living with diagnosed TDD and the other without a diagnosis of TDD. The participants in the study will be recruited ...