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

• 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
• 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

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.

项目摘要 Collaborations PharmPharmticals Inc.是一家专注于开发难以治疗的疗法的小企业 疾病。持续过度依赖阿片类药物治疗慢性疼痛，尽管它们改善功能的能力很差 导致近年来阿片类药物过量死亡和成瘾的严重和令人震惊的流行。 尽管存在着压倒性的成瘾危机，但现有的治疗方法很少，而且疗效很低。因此，一个关键的未得到满足的需求 是治疗阿片类药物滥用障碍的有效和安全的方法。最近的研究表明，迷幻剂 还能够减少药物依赖，包括阿片类药物滥用，严重的不良影响是 极其罕见。这种药物滥用的停止与神经再生的诱导有关，并增加了 神经可塑性，迷幻剂的一个特征。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- 回避，但似乎缺乏迷幻体验。虽然数量很少，但这些类似物有 被命名为“精神增殖剂”，是治疗阿片类药物滥用的有前途的候选药物。那就是- 迷幻体验和神经可塑性诱导的耦合与受体特异性有关，如 精神增殖体是5HT2a的特异性基因。在这里，我们建议使用产生式机器学习的组合 利用我们在监控机器模型方面的丰富经验来生成新的迷幻剂类似物 这将改善5-HT2A的特异性、ADME特性，并且易于合成以快速扩展 已知的精神生物质池，显著增加了阿片类药物滥用的潜在治疗选择 治疗。