Bringing Precision Medicine to the Field of Mental Healthcare through Large Language Models, AI, and Psychedelics


In the United States, there are approximately 132 suicides per day in the United States (American Foundation for Suicide Prevention, 2023). In fact, suicide numbers have been rising consistently for the past two decades and 2022 recorded the highest number ever in the US with data suggesting that suicide is more common now than any time since the start of WWII (Centers for Disease Control and Prevention, 2023). This panel will focus on the relative lack of progress in the field of mental health and its root causes ranging from a lack of new and novel drugs to an insufficiency of precision diagnostic tools when compared to the rest of the medical field. It will also focus on a variety of solutions that are currently being developed to help reduce this deficit – from new psychedelic-based treatments to novel precision tools based on wearables, vision, and voice measurement. As an example, we’ll dive into how Generative AI and Large Language Models can be used to get measurements of how treatment is progressing from the provider’s and patient’s viewpoints to get to novel object features that could be used to potentially help predict outcomes or improve care.


Gregory Ryslik is a statistician, data scientist and artificial intelligence researcher with experience building and leading data initiatives in companies across the biotech, autotech, healthtech and fintech domains. Greg leads Artificial Intelligence, Engineering & Data Efforts at Compass Pathways, a biotechnology company dedicated to accelerating patient access to evidence-based innovation in mental health. Prior to Compass, Greg Ryslik was the Chief Data Officer at Celsius Therapeutics in Cambridge, MA, a biotechnology company focused on single cell RNA sequencing. Prior to that, he was Vice President of Data Science at Mindstrong Health, a healthcare company transforming mental health treatment through measurement science and artificial intelligence. Greg has also spent time in the automotive sector, first at Tesla Motors, leading the Service Data Science group in Palo Alto, CA and then as the Head and Senior Director of Data Science at Faraday Future in Los Angeles, CA. Earlier in his career, he performed machine learning research and nonclinical biostatistics research at Genentech and was an actuary in New York City at PricewaterhouseCoopers.

Greg lectures on statistics for artificial intelligence and machine learning at Stanford Continuing Studies and is an Assistant Professor of Practice at The Ohio State University. He is also a fellow of the Casualty Actuarial Society, as well as a member of the American Academy of Actuaries. His research has been published in journals ranging from Nature to BMC Bioinformatics and has led to several software packages on mutational clustering. Greg holds a PhD from Yale University in biostatistics, a master’s degree in statistics from Columbia University and an undergraduate degree in mathematics, computer science and finance from Rutgers University.

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