New therapeutic approaches to identifying molecules for opioid abuse treatment

识别阿片类药物滥用分子的新治疗方法

基本信息

批准号：
10385998
负责人：
SEAN EKINS
金额：
$ 25.62万
依托单位：
COLLABORATIONS PHARMACEUTICALS, INC.
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-04-15 至 2024-04-14
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10385998
关键词：
Acute Adverse effects Agonist Anxiety Biological Assay Businesses Cessation of life Collaborations Coupling Data Set Databases Decision Trees Disease Dose Drug Addiction Drug abuse Ensure Expert Systems Feedback HTR2A gene Hallucinogens Head Ibogaine In Vitro Intellectual Property Lead Learning Link Lysergic Acid Diethylamide Machine Learning Medical Mental disorders Metabolic Methadone Modeling Names Natural Products Network-based Neuronal Plasticity Opiate Addiction Opioid Overdose Pathway interactions Pharmaceutical Chemistry Pharmaceutical Preparations Pharmacologic Substance Phase Production Property Randomized Clinical Trials Reporting Research Seeds Serotonin Solubility Source Specificity Supervision Testing Therapeutic Toxic effect United States Validation Work addiction algorithm training analog base chronic pain compliance behavior cost effective deep learning model ecstasy experience improved improved functioning in vivo innovation interest lead optimization machine learning model novel novel therapeutic intervention novel therapeutics open source opioid abuse opioid epidemic opioid mortality opioid use disorder receptor recurrent neural network research and development response scale up serotonin receptor small molecule libraries supervised learning support vector machine synthetic opioid

项目摘要

Project Summary Collaborations Pharmaceuticals Inc. is a small business focused on developing treatments for difficult to treat diseases. The ongoing overreliance on opioids for chronic pain despite their poor ability to improve function has contributed to a significant and alarming epidemic of opioid overdose deaths and addictions in recent years. Despite the overwhelming addiction crisis, few therapies exist, and with low efficacy. Thus, a critical unmet need is an effective and safe treatment for opioid abuse disorders. Recent research has suggested that psychedelics are also capable of reducing drug-dependence, including opioid abuse, and that serious adverse effects are extremely rare. This drug abuse cessation is linked to the induction of neuritogenesis and increased neuroplasticity, a hallmark of psychedelics. While the psychedelic experience and neuroplasticity induction appear interlinked, several analogs of psychedelics have been proposed which induce neuroplasticity and drug- avoidance while seemingly lacking the psychedelic experience. Although few in number, these analogs have been named “psychoplastogens” and are promising candidates for treatment of opioid drug abuse. The de- coupling of the psychedelic experience and neuroplasticity induction is linked to receptor specificity as psychoplastogens are specific to 5HT2A. Here, we propose to use a combination of generative machine learning models with our extensive experience of supervised machine models to generate new analogs of psychedelics that will have improved 5-HT2A specificity, ADME properties, and are easily synthesizable to rapidly expand the pool of known psychoplastogens, significantly increasing potential therapeutic options for opioid abuse treatment.

项目概要 Collaborations Pharmaceuticals Inc. 是一家小型企业，专注于开发疑难病症的治疗方法尽管阿片类药物改善功能的能力较差，但人们仍然过度依赖阿片类药物来治疗慢性疼痛。近年来，阿片类药物过量死亡和成瘾现象严重且令人震惊。尽管存在压倒性的成瘾危机，但现有的治疗方法很少，而且疗效很低，因此，一个关键的未满足的需求。最近的研究表明迷幻药是治疗阿片类药物滥用障碍的有效且安全的方法。还能够减少药物依赖，包括阿片类药物滥用，并且严重的副作用这种药物滥用的戒断与神经突发生的诱导和增加有关。神经可塑性，迷幻药的标志，而迷幻体验和神经可塑性诱导。似乎是相互关联的，已经提出了几种迷幻药的类似物，它们可以诱导神经可塑性和药物作用尽管数量很少，但这些类似物却似乎缺乏迷幻体验。已被命名为“精神塑性剂”，是治疗阿片类药物滥用的有希望的候选药物。迷幻体验和神经可塑性诱导的耦合与受体特异性相关，如下所示 Psychoplastogens 是 5HT2A 特有的，在这里，我们建议结合使用生成机器学习。模型与我们在监督机器模型方面的丰富经验一起生成新的迷幻药类似物它将具有改进的 5-HT2A 特异性、ADME 特性，并且易于合成以快速扩展已知的精神塑性剂库，显着增加阿片类药物滥用的潜在治疗选择治疗。