Utilizing NLP in the Context of COMP360 Psilocybin Therapy for Treatment Resistant Depression


Psilocybin therapy has experienced a renaissance in recent years with regards to the treatment of various mental health disorders. COMPASS Pathways is leading this effort, developing its COMP360 psilocybin therapy to help patients suffering with treatment-resistant depression (TRD) as well as other indications. As part of the investigational COMP360 therapy protocol, a specially trained therapist provides psychological support to the patient before, during and after the psilocybin session. In this talk, we will describe how we have built out an NLP platform to monitor these interactions and provide tools to therapists in quasi-real time, allowing them to provide better support to their patients. We will discuss how this platform is being deployed in our trials and the considerations required from AI, engineering and security viewpoints.


Greg Ryslik is a data science and machine learning executive experienced in leading AI and engineering initiatives ranging across the biotech, healthtech and fintech domains. As senior vice president at COMPASS Pathways his work focuses on developing technology to improve the therapeutic journey for patients with treatment resistant depression. Concurrently, Greg is an assistant professor of practice in the Department of Computer Science & Engineering at Ohio State University as well as an Instructor at Stanford Continuing Studies where he lectures on statistics for artificial intelligence.

Greg started his career as an actuary at PricewaterhouseCoopers in New York City. After his PhD he spent several years in Silicon Valley at companies such as Tesla Motors, Mindstrong Health and Genentech. He is a fellow of the Casualty Actuarial Society, as well as a member of the American Academy of Actuaries. In September 2020, he was named one of Boston Business Journal’s “40 under 40”.

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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