Rapid and non-invasive device for drug detection through sweat

项目摘要 在NIH SBIR第二阶段项目中，Arborense将继续其成功的工作路线，开发一种便携式 基于汗液的筛查设备，以满足对快速、非侵入性和定量设备的需求 在需要时发现滥用药物。使用和滥用可能使人上瘾的物质已经成为 一场全国性的危机。巨大的社会影响(CDC报告在2020年4月至2021年4月期间有100,000人死亡) 与药物滥用相关的经济成本(每年在医疗保健、工作效率和犯罪方面的成本为4000亿美元) 和滥用呼吁紧急关注实施和支持保健办法，以减少生命损失 以及由此带来的经济负担。定期药物使用测试和监测是管理的关键组成部分 控制这一流行病的战略。在大多数情况下，无论是临床的，法院命令的，治疗中心， 工作场所监测或路边测试，拥有可靠和及时的药物使用数据是至关重要的。然而， 通过检测血液、尿液、唾液、头发、呼吸和汗液来检测药物使用的可用策略有 受到繁琐的收集方法和在接收检测结果方面的重大延误的困扰，从而阻碍了 能够提供有关最近药物使用的最新客观数据。基于对RAPID和FATH的初步研究 人工汗液中4种药物/阿片类药物的定量检测，Arborense获得了NIDA阶段I SBIR(R43 DA052941)奖。在第一阶段，我们：(1)将小组扩大到第5种药物-丁丙诺啡，(2)优化汗液 分析方案，(3)开发了汗液生成和汗液采集模块，(4)对探测器进行了验证 在一项人类受试者的研究中(n=16)，以尿液药物筛查为基准，我们展示了 需要产生(5分钟)和收集(15分钟)20微米L的汗液，然后进行检测(20分钟) 5种药物的检出限为1~3 ng/m L。基于这些结果，在第二阶段，Arborense将进一步优化 整体设备设计和工作流程，以开发真正可移植的健壮原型，并以 工业标准LC-MS(液-质联用)在大规模人体中的应用 受试者研究(n=50)。具体地说，我们将把汗液发生器的尺寸缩小到手持单元和汗液 探测器到鞋盒大小的单位。我们将使微流控流程自动化，以消除机械移动部件和 优化单元，将开始到结束的时间目标定为25分钟。整体设计还将减少多个手动操作 易于操作的接触点。在第二阶段，Arborense将与Biomedical Engineering和 密歇根大学精神病学系设计、共同开发和验证基于汗水的便携式 大规模人体研究中的探测器。我们还将在设计期间与我们的战略行业合作伙伴进行接触 整合市场接受所需功能的过程。我们的探测器之间有良好的通信 LC-MS测量将确认我们检测器的技术和商业可行性，然后可以 提供给行业合作伙伴进行测试，并向投资者推介。

Project Summary In this NIH SBIR Phase II project, Arborsense will continue its successful line of work to develop a portable sweat-based screening device to address the unmet need for a rapid, non-invasive, and quantitative device for detection of drugs of abuse at point-of-need. The use and abuse of potentially addictive substances has become a national crisis. The tremendous social (100,000 deaths reported by CDC between April 2020 and April 2021) and economic ($400B annually in healthcare, work productivity, and crime) costs related to the substance abuse and misuse call for an urgent focus on implementing and supporting health approaches to reduce the loss of life and financial burden inflicted. Regular drug-use testing and monitoring are key components of the management strategies to control this epidemic. Within most settings whether clinical, court-ordered, treatment centers, workplace monitoring, or roadside testing, having reliable and timely data on drug use is essential. However, the available strategies to detect drug use which rely on testing blood, urine, saliva, hair, breath, and sweat, are plagued by cumbersome collection methods and significant delays in receiving test results, thus hampering the ability to provide up-to-date objective data on recent drug use. Based on the preliminary study on rapid and quantitative detection of 4 drugs/opioids in artificial sweat, Arborsense received a NIDA Phase I SBIR (R43 DA052941) award. In Phase I, we: (1) expanded the panel to 5th drug - Buprenorphine, (2) optimized the sweat analysis protocol, (3) developed sweat generation and sweat collection modules, and (4) validated the detector in a human subjects’ study (n=16) benchmarking it with a urine drug screen where we demonstrated point-of- need generation (5 minutes) and collection (15 minutes) of 20 µL of sweat and subsequent detection (20 minutes) of 5 drugs with detection limits of 1-3 ng/mL. Based on these results, in Phase II Arborsense will further optimize the overall device design and workflow to develop a truly portable robust prototype and benchmark it with the industry-standard LC-MS (liquid chromatography coupled with mass spectrometry) in a large-scale human subjects’ study (n=50). Specifically, we will reduce the size of the sweat generator to a hand-held unit and sweat detector to a shoebox size unit. We will automate the microfluidic flow to eliminate mechanical moving parts and optimize the unit to target a start-to-finish time of 25 minutes. The overall design will also reduce multiple manual touchpoints for ease-of-operation. In Phase II, Arborsense will collaborate with Biomedical Engineering and Department of Psychiatry at University of Michigan to design, co-develop, and validate the portable sweat-based detector in a large-scale human study. We will also engage with our strategic industry partners during the design process to incorporate features necessary for market acceptance. Good correspondence between our detector and LC-MS measurements will confirm the technical and commercial feasibility of our detector, which can then be provided to industry partners for testing and pitched to investors.