Rapid Assessment of Illicit Drugs in Wastewater

废水中非法药物的快速评估

• 批准号: 10576367
• 负责人: Avni A Argun
• 金额: $ 89.31万
• 依托单位: GINER, INC.
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-01 至 2025-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10576367
• 关键词: Accident and Emergency department; Address; Algorithms; Area; Award; Back; Benchmarking; Biological Assay; Boston; Cessation of life; Cities; Collaborations; Collection; Communities; Consumption; Crime; Data; Data Correlations; Detection; Devices; Drug abuse; Drug usage; Drug user; Electronics; Engineering; Environmental Medicine; Epidemic; Epidemiologist; Fentanyl; Goals; Grant; Healthcare; Heroin; High Pressure Liquid Chromatography; Illicit Drugs; Individual; Intervention; Label; Laboratories; Law Enforcement; Massachusetts; Measurement; Measures; Methadone; Methodology; Methods; Microfluidic Microchips; Microfluidics; Monitor; Morphine; National Institute of Drug Abuse; New York; Norfentanyl; Nucleic Acids; Opioid; Overdose; Oxycodone; Pattern; Pharmaceutical Preparations; Phase; Plants; Prevalence; Productivity; Public Health; Safety; Sampling; Scientist; Secure; Site; Specificity; Stigmatization; Stream; System; Technology; Testing; Time; Transistors; Transportation; United States; Universities; Validation; Work; Workplace; aptamer; cohort; college; commercialization; cost; cost effective; design; detection limit; diagnostic strategy; drug misuse; epidemiology study; field study; graphene; heroin use; insight; instrument; instrumentation; interest; mobile sensor; opioid abuse; opioid epidemic; opioid misuse; opioid overdose; opioid use; overdose death; population survey; portability; programs; prototype; research and development; sample collection; sensor; sensor technology; septic; statistics; success; surveillance data; synthetic opioid; technology development; tool; wastewater epidemiology; wastewater monitoring; wastewater samples; wastewater sampling; wastewater testing; water quality

PROJECT SUMMARY/ABSTRACT Opioid crisis (abuse and misuse) is an epidemic of global concern to public health and safety, causing over 70,000 deaths annually in the United States. Obtaining real-time data on the use of opioids is a major challenge as this information is limited to population surveys and drug surveillance data. There is an urgent public health need for monitoring tools to achieve crucial insight into the prevalence of opioid misuse/abuse without stigmatizing communities. Wastewater monitoring is a proven strategy to identify areas needing intervention instead of relying on emergency-room statistics and overdose deaths. However, current wastewater drug analysis requires costly laboratory-based tests that involves labor intensive sample collection, transportation, and analysis, resulting in long (days) turnaround times. Giner proposes to develop a compact, portable, label-free Graphene Field Effect Transistor (G-FET) sensor utilizing high-specificity aptamers for rapid, accurate, cost-effective, and multiplexing monitoring of opioid drug metabolites in wastewater samples. Since it generates rapid results compared to incumbent methods which rely on batch sampling of wastewater streams followed by expensive, time consuming analysis, this technology will provide actionable real time data at a fraction of the cost of incumbent methods, encouraging broad use. The goal of Phase II program is to demonstrate a field-ready prototype and a test methodology for simultaneous detection of multiple opioid metabolites in wastewater at pg/mL levels. During the Phase I work, Giner successfully detected three opioid metabolites in wastewater samples that are also associated with street heroin use: Norfentanyl (a metabolite of fentanyl, a synthetic opioid), EDDP (a metabolite of methadone, fully synthetic opioid), and Noroxycodone (a semisynthetic opioid, metabolite of oxycodone). We will also add Morphine (main heroine metabolite, a natural opioid) to our Phase II program. Multiple samples from wastewater treatment plants will be analyzed with Giner’s sensor and results will be cross-validated using the gold standard HPLC-MS/MS method. Giner will achieve this by using its prior expertise in bio/sensors and wastewater testing and in close collaboration with an interdisciplinary team of scientists, engineers, and environmental wastewater epidemiologists. Once developed, the technology will also be suitable for detection of any target illicit drug for which an aptamer can be prepared.

项目摘要/摘要 阿片类药物危机（虐待和误解）是全球关注公共卫生和安全的流行病，导致了 美国每年70,000人死亡。获取有关使用阿片类药物的实时数据是主要的 挑战由于此信息仅限于人口调查和药物监视数据。有紧急 监测工具的公共卫生需求，以实现对阿片类药物/虐待的普遍性的关键见解 没有污名化社区。废水监测是确定领域需求的验证策略 干预而不是依靠紧急房间统计和过量死亡。但是，当前 废水药物分析需要昂贵的基于实验室的测试，涉及实验室密集样品收集， 运输和分析，导致长时间的周转时间。 Giner提出了发展紧凑的提议， 便携式，无标签的石墨烯场效应晶体管（G-FET）传感器，利用高特异性适体用于 在废水样品中对阿片类药物代谢产物的快速，准确，成本效益和多重监测。 由于与依赖废水批处理采样的现有方法相比，它产生了快速的结果 流进行昂贵，耗时的分析，该技术将提供可行的实时数据 在现有方法成本的一小部分中，鼓励广泛使用。 第二阶段计划的目的是展示一个现场就绪的原型和一种测试方法 在Pg/mL水平的废水中简单检测多种阿片类药物代谢物。在我工作的阶段， Giner在废水样品中成功检测到三种阿片类药物代谢物，这些代谢物也与 街道海洛因使用：诺芬太尼（芬太尼的代谢物，一种合成阿片类药物），EDDP（美沙酮的代谢物， 完全合成的阿片类药物）和Noroxycodone（一种半同步的阿片类药物，羟考酮的代谢产物）。我们还将添加 我们的II期计划的吗啡（主女主角代谢物，天然阿片类药物）。来自多个样本 废水处理厂将使用Giner的传感器进行分析，并将使用该结果进行交叉验证 黄金标准HPLC-MS/MS方法。 Giner将通过使用其先前的生物/传感器专业知识来实现​​这一目标，并 废水测试，并与一个科学家，工程师和 环境废水流行病学家。一旦开发，该技术也将适合检测 可以准备纠纷的任何目标非法药物。