AI-assisted behavioral profiling of an invertebrate model to identify new psychedelic therapeutics for stimulant use disorders

项目摘要 物质使用障碍是指患者持续使用某种物质的神经行为障碍。 尽管它对他们的生活产生了不利影响。阿片类药物和可卡因的使用分别占70%和22%， 分别为2019年仅在美国的药物过量死亡人数。虽然有FDA批准的治疗方法 在阿片类药物使用障碍的情况下，没有治疗可卡因成瘾的药物。阿片类药物具有良好的特性 大脑中的作用机制。然而，可卡因针对的是多个神经递质途径，而 成瘾的分子基础尚未阐明。在发现新的治疗方法方面面临的重大挑战 可卡因使用障碍(CUD)是需要对动物进行行为测试以确定候选 毒品可以减少或消除成瘾行为。对啮齿类动物进行行为分析的需要与 高通量药物发现筛选。 NemaLife，Inc.开发了一种微流控平台，该平台能够使用 线虫。我们平台记录的视频数据由我们的人工智能自动处理 分析管道NemaStudio.ai以获取活体/死亡和动物活动等指标。这个第一阶段的项目将 在NemaStudio.ai中实现其他机器学习算法，以对蠕虫行为进行分类。这是一项新的 这一功能将使我们能够对动物进行高通量的行为分析。这种形式的行为 使用CUD蠕虫模型的分析有望迅速找到治疗可卡因成瘾的新方法。 目的1-建立高通量人工智能辅助的可卡因使用障碍行为特征分析方法。在……里面 为了实现这一目标，我们将采用现有的WORM CUD范例，并针对我们的微流体平台进行优化。具体来说， 我们将创建基于微流控芯片的线索条件位置偏好和自我管理线索版本 范例。一旦这些分析方法被开发出来，我们将收集动物行为的大型数据集，无论是开启还是关闭 可卡因。这些数据将被用来训练NemaStudio.ai对动物的成瘾行为进行分类和量化 暴露在可卡因中形成了我们的行为特征分析管道。 目标2-从迷幻化合物的靶向文库中确定潜在的CUD疗法。使用 我们的筛选流程已经到位，我们将检查迷幻化合物，这种已知具有抗肿瘤作用的化合物 成瘾特性，可能代表了治疗CUD的新来源。我们会放映各种迷幻药 化合物，选择最好的候选化合物，并对迷幻剂处理和未处理的线索进行RNA-SEQ 动物。这些数据将有助于确定这些候选人削减/废除的可能行动机制。 可卡因成瘾对蠕虫的影响。我们以数据为导向的洞察力将使有针对性的啮齿动物研究成为可能 命中化合物的临床验证。总之，这项工作利用人工智能工具在活体中构建了高通量 药物发现平台加速CUD治疗新疗法的开发。

Project Abstract Substance use disorders are neurobehavioral disorders in which afflicted individuals continue to use a substance despite its adverse effects on their lives. Opioids and cocaine use were responsible for 70% and 22%, respectively, of drug overdose deaths in the US alone in 2019. While there are FDA-approved treatments for opioid use disorders, no such therapeutics are available for cocaine addiction. Opioids have a well-characterized mechanism of action in the brain. However, cocaine targets multiple neurotransmitter pathways, and the molecular basis of addiction has not been elucidated. A significant challenge in discovering new therapeutics for cocaine use disorders (CUD) is the need to perform behavioral assays on animals to determine if a candidate drug reduces or abolishes addictive behavior. The need for behavioral assays in rodents is not compatible with high-throughput drug discovery screens. NemaLife, Inc. has developed a microfluidic platform that enables high-throughput in vivo screening using the nematode Caenorhabditis elegans. Video data recorded by our platform is automatically processed by our AI analysis pipeline NemaStudio.ai for metrics such as live/dead and animal activity. This Phase 1 project will implement additional machine learning algorithms into NemaStudio.ai to classify worm behavior. This new functionality will enable us to perform high-throughput behavioral profiling of animals. This form of behavioral profiling using worm models of CUD is expected to rapidly identify new treatments for cocaine addiction. Aim 1 - Develop high-throughput AI-assisted behavioral profiling assays for cocaine use disorders. In this aim, we will take existing worm CUD paradigms and optimize them for our microfluidic platform. Specifically, we will create microfluidic chip-based versions of cue-conditioned place preference and self-administration CUD paradigms. Once these assays are developed, we will collect large datasets of animal behavior either on or off cocaine. This data will then be used to train NemaStudio.ai to classify and quantify addictive behaviors in animals exposed to cocaine and form our behavioral profiling pipeline. Aim 2 - Identify potential CUD therapeutics from a targeted library of psychedelic compounds. With our screening pipeline in place, we will examine whether psychedelic compounds, which are known to have anti- addiction properties, might represent a new source of treatments for CUD. We will screen a variety of psychedelic compounds, select the top candidates, and perform RNA-seq on psychedelic-treated and untreated CUD animals. This data will help identify possible mechanisms of action by which these candidates reduce/abolish the effects of cocaine addiction in the worm. Our data-driven insights will enable targeted rodent studies for pre- clinical validation of the hit compounds. In sum, this work leverages AI tools to build a high throughput in vivo drug discovery platform to accelerate the development of new therapeutics for CUD.