Development of the OpiAID strength band platform

OpiAID 力量带平台的开发

• 批准号: 10684399
• 负责人: David Alderson MacQueen
• 金额: $ 31.96万
• 依托单位: OPIAID, INC.
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10684399
• 关键词: Accelerometer; Acute; Address; Adopted; Adoption; Agonist; Algorithms; Anxiety; Behavioral; Biometry; Buprenorphine; COVID-19 pandemic; Cessation of life; Charge; Client satisfaction; Clinical; Clinical Trials; Counseling; Criminal Justice; Data; Dependence; Development; Devices; Dose; Epidemic; Event; Health Care Costs; Healthcare; Imprisonment; Intervention; Machine Learning; Maintenance; Methadone; Methods; Opiate Addiction; Opioid; Opioid agonist; Overdose; Pain; Participant; Patient Care; Patient Monitoring; Patient Self-Report; Patients; Performance; Persons; Pharmaceutical Preparations; Pharmacotherapy; Phase; Photoplethysmography; Physicians; Pilot Projects; Price; Productivity; Protocols documentation; Provider; Randomized; Randomized, Controlled Trials; Relapse; Research; Risk Reduction; Services; Site; Sleeplessness; Social Functioning; Survival Analysis; Symptoms; Technology; Telephone; Temperature; Time; Toxicology; Urine; Withdrawal; Withdrawal Symptom; Work; arm; cost; craving; detection platform; digital platform; drug seeking behavior; evidence base; experience; fitbit; flu; improved; innovation; medication for opioid use disorder; monitoring device; opioid agonist therapy; opioid misuse; opioid mortality; opioid overdose; opioid use; opioid withdrawal; overdose death; overdose risk; patient retention; recruit; relapse prevention; relapse risk; satisfaction; sensor; standard of care; success; supervised learning; wearable device

PROJECT SUMMARY Opioid misuse has reached epidemic levels in the U.S., claiming the lives of more than 104,000 people in the twelve months up to February 2022 alone. Opioids are highly addictive and are accompanied by severe withdrawal symptoms such as anxiety, generalized pain, insomnia, and flu-like symptoms that contribute to relapse. Opioid overdose, misuse, and dependence result in an estimated $35B in health care costs, $14B in criminal justice costs, and $92B in lost productivity each year in the U.S. Medications for opioid use disorder (MOUD), which combines behavioral counseling with agonist drug therapies such as buprenorphine or methadone to manage withdrawal, is an evidence-based, whole-patient approach to treating opioid dependence. It has been shown to decrease opioid use and deaths from overdose and increase social functioning and treatment retention. However, establishing the correct initial dose of an opioid agonist to administer during the MOUD induction phase is difficult; low doses may fail to alleviate withdrawal symptoms and increase the risk of relapse, while high doses may fail to reduce the risk of overdose. Such factors present a barrier to patient retention through the MOUD induction phase, and providers currently lack methods for patient monitoring that could inform improved dosing protocols. OpiAID, Inc is addressing this unmet need with the Strength Band Platform, an innovative AI-based digital platform that enables patient monitoring throughout the MOUD induction period. Patient biometrics are captured via a wearable device with a multi-sensor array and are used by our proprietary algorithm to detect relapse and withdrawal during MOUD induction. This first-of-its-kind technology aims to enable physicians to implement just-in-time interventions to enhance patient retention, prevent relapse, and improve the management of withdrawal symptoms. Our pilot studies have shown that our platform can gather and synthesize the biometric data needed for composite quantification and timely identification of acute opioid use and withdrawal. However, our work was done using a research-grade device, the Empatica E4, whose price point and limited adoption may hinder marketability. Building upon this work, we intend to expand our platform to accommodate commercially available and widely adopted devices like the WHOOP Strap 4.0 and Fitbit Charge 5. Further, we plan to conduct a large clinical trial to evaluate the performance of the Strength Band Platform in real-world settings. Successful completion of this project will confirm the utility of OpiAID’s Strength Band Platform for detecting relapse and withdrawal, and for enhancing clinicians’ ability to deliver quality, sustainable care for patients with opioid dependency.

项目总结 阿片类药物滥用在美国已经达到流行水平，夺走了超过10.4万人的生命。 仅到2022年2月就有12个月。阿片类药物非常容易上瘾，并伴随着严重的 戒断症状，如焦虑、全身性疼痛、失眠和流感样症状 旧病复发。阿片类药物过量、滥用和依赖导致的医疗保健成本估计为350亿美元， 刑事司法成本，以及美国每年90亿美元的生产力损失。阿片类药物使用障碍 (Moud)，将行为咨询与丁丙诺啡或丁丙诺啡等激动剂药物治疗相结合 美沙酮管理戒断，是一种基于证据的、针对阿片类药物依赖的治疗方法。 它已被证明可以减少阿片类药物的使用和过量死亡，并增加社会功能和 治疗滞留。然而，确定正确的阿片类激动剂的初始剂量在 MMOD诱导期困难；低剂量可能无法缓解戒断症状并增加戒断症状的风险 复发，而高剂量可能无法降低过量用药的风险。这些因素对患者构成了障碍 在Moud诱导阶段保留，而提供者目前缺乏监测患者的方法 可以通知改进的给药方案。OpiAID，Inc.正在通过力量乐队解决这一未得到满足的需求 Platform，一个创新的基于AI的数字平台，支持在Moud诱导过程中对患者进行监控 句号。患者的生物特征通过具有多传感器阵列的可穿戴设备捕获，并由我们的 在Moud诱导期间检测复发和戒断的专有算法。这种首创的技术 旨在使医生能够实施及时的干预措施，以增强患者的保留率，防止复发， 完善戒断症状管理。我们的初步研究表明，我们的平台可以 收集和合成综合量化和及时识别急性呼吸道合并症所需的生物特征数据 阿片类药物的使用和戒断。然而，我们的工作是使用研究级设备Empatica E4完成的，该设备 价格点和有限的采用率可能会阻碍市场。在这项工作的基础上，我们打算扩大我们的 平台，以适应商业上可获得和广泛采用的设备，如呼喊背带4.0和 Fitbit Charge 5.此外，我们计划进行一项大型临床试验，以评估力量带的性能 真实世界环境中的平台。这一项目的成功完成将证实OpiAID力量的效用 BAND平台，用于检测复发和戒断，并提高临床医生提供质量的能力， 阿片类药物依赖患者的可持续护理。