Project Abstract Alcohol use disorders (AUDs) are globally prevalent neurobehavioral disorders where individuals consume excessive alcohol despite its adverse effects on their lives. The global incidence of deaths related to AUDs was estimated at 3 million in 2016, while in the US, 140,000 deaths annually are alcohol-related. While there are FDA-approved treatments for AUDs, they require chronic treatment to remain effective. In contrast, psychedelics offer a potential paradigm shift in addiction treatment because a single dose can cause long-lasting abstinence from alcohol. However, natural psychedelics, such as ibogaine, have serious side effects that make them unsuitable neurotherapeutics. Pyschoplastogens are non-hallucinogenic derivatives of psychedelics with improved safety profiles that make them good candidates for new neurotherapeutics for AUDs. NemaLife, Inc.’s Infinity Screening System 2.0 (ISS 2.0) is a high-throughput in vivo screening platform that uses the nematode Caenorhabditis elegans for drug discovery. ISS 2.0 records video data that is automatically processed by our AI pipeline for metrics such as live/dead and animal activity. This Phase 1 project will combine the novelty of a targeted psychoplastogen library and new machine learning-based behavioral screening. This foundational capability will allow us to perform AI-assisted behavioral profiling of worm models of AUDs to screen for new neurotherapeutics for alcohol addiction. AIM 1: Develop high-throughput AI-assisted behavioral profiling assays for alcohol use disorders The ISS 2.0 platform offers the ability to conduct high-throughput drug screens using the nematode C. elegans. In Aim 1, we will optimize assays for alcohol use disorder and test a series of well-established psychedelic compounds to identify positive controls. We will examine two AUD paradigms and develop behavioral metrics. Finally, we will correlate these metrics to create phenotypic profiles of animals exhibiting AUD behavior, which will be used to train and implement additional machine learning algorithms into ISS 2.0 to allow it to distinguish between addictive and non-addictive behavior in real-time. AIM 2. Identify potential AUD therapeutics from a targeted library of psychoplastogens Psychoplastogens have better safety profiles than psychedelics and might make effective treatments for AUDs. We can leverage our AI-enabled platform for screening psychoplastogens and establishing their therapeutic value. Therefore, we propose to use the ISS 2.0 behavioral profiling capabilities developed in Aim 1 to screen about 200 compounds for their potential as therapeutics for AUD. We will then characterize the potential mechanisms of action of the hits through transcriptomic profiling, laying the groundwork for future studies using rodent models of AUD in a Phase 2 application. Combining rapid identification of anti-addictive compounds with high-throughput worm screens and validation in rodent models will signi...