Wearable Sensor and Digital Technologies for Quantitative Assessment and Remote Monitoring of Symptoms in Myasthenia Gravis

用于定量评估和远程监测重症肌无力症状的可穿戴传感器和数字技术

• 批准号: 10470564
• 负责人: Amanda Guidon
• 金额: $ 50万
• 依托单位: BIOSENSICS, LLC
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-15 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10470564
• 关键词: Acoustics; Activities of Daily Living; Adopted; Age; Algorithmic Analysis; Algorithms; Ambulatory Care Facilities; Anxiety; Architecture; Attitude; Autoimmune; Biological Markers; Caring; Characteristics; Chronic; Clinic; Clinic Visits; Clinical; Clinical Research; Clinical Trials; Clinical assessments; Cloud Computing; Collection; Complement; Computer software; Consumption; Data; Data Security; Data Set; Development; Disease; Dysarthria; Enrollment; Face; Fatigue; Feedback; Funding; General Hospitals; Generalized Myasthenia Gravis; Health Insurance Portability and Accountability Act; Health Services Accessibility; Health Technology; Immunosuppressive Agents; Instruction; Interview; Legal patent; Massachusetts; Mediation; Medical; Methods; Modeling; Movement; Muscle Weakness; Myasthenia Gravis; Neck; Neurologist; Neuromuscular Diseases; Ocular Myasthenia Gravis; Online Systems; Onset of illness; Outcome; Participant; Patient Outcomes Assessments; Patients; Perception; Persons; Pharmaceutical Preparations; Pharmacologic Substance; Phase; Protocols documentation; Ptosis; Public Health; Quality of Care; Quality of life; Questionnaires; Rare Diseases; Recording of previous events; Reporting; Research; Risk; Secure; Severities; Site; Small Business Innovation Research Grant; Specialist; Speech; Symptoms; System; Systems Development; Technology; Telemedicine; Testing; Text; Time; Titrations; Training; Travel; Trust; United States National Institutes of Health; Visit; Wrist; base; biomarker discovery; clinical phenotype; clinical research site; clinical trial readiness; common symptom; cost; data access; data exchange; deep learning model; digital; effective therapy; efficacy evaluation; experience; improved; individual response; insight; interest; mHealth; machine learning algorithm; mobile application; motor symptom; nervous system disorder; personalized medicine; prototype; recruit; remote assessment; remote monitoring; sensor; telehealth; usability; wearable device; wearable sensor technology; web site

PROJECT SUMMARY Myasthenia gravis (MG) is a chronic autoimmune neuromuscular disease characterized by fluctuating muscle weakness and symptoms that interfere with activities of daily living and negatively impacts quality of life. MG symptoms are currently assessed in person through a careful history and physical exam by a neuromuscular disease expert. Such in-clinic assessments are time-consuming, subjective, only provide a snapshot of a patient's disease and do not adequately reflect the spectrum of fluctuating weakness and symptoms. In 2019, NIH funded a rare disease clinical research consortium called MGNet. The consortium is focused on improved characterization of clinical phenotypes, discovery of biomarkers, and advancing clinical trial readiness for MG, which would enhance the development of more effective and personalized treatments. In this Fast Track SBIR project, BioSensics will collaborate with Massachusetts General Hospital - one of the key Consortium sites for MGNet that provides care to approximately 200 MG patients - to develop and validate a wearable sensor solution (MGWear) for continuous remote monitoring of motor symptoms and function in MG patients and also a secure mobile application (MG app) for automatic assessment of speech and facial characteristics (i.e. dysarthria and ptosis), which are the most common symptoms of MG. The mobile application will also enable the transfer of data from the wearable device to BioSensics HIPAA-compliant backend cloud called BioDigit Cloud that can be accessed via a secure website. The project will complement outcome and biomarker research by MGNet and represent significant public health need and market opportunity for BioSensics. A key application and market for the proposed solution technology is pharmaceutical clinical trials. Wearable sensors and digital technologies like the technology proposed here will allow drug developers to test and iterate faster, providing a valuable new method for evaluating efficacy. BioSensics is a leader in providing wearable sensor and digital technologies for clinical trials. This project will significantly broaden BioSensics offerings and capabilities by providing mobile health (mHealth) technologies for remote monitoring of motor symptoms, speech and ptosis in MG and other neurological diseases. Clinically, the proposed solution can be used to predict an individual's response to immunosuppressive drugs and to improve mediation titration. Such solutions can enable detecting subtle changes in movement-based and digital biomarkers and provide insight into the phase of clinical disease onset. Additionally, the growing use of telemedicine to expand access and potentially reduce costs of high-quality care will require remote assessment strategies. 20% of states in the US (10 out of 50 states) have no specialized care for MG. Travel time, distance and cost may limit patients' access to expert care, even in states with identified MG specialists. The proposed remote monitoring technologies have potential to lessen barriers to quality care access for MG patients.

项目摘要 肌无力重症（mg）是一种慢性自身免疫性神经肌肉疾病，其特征是肌肉波动 干扰日常生活活动和负面影响的弱点和症状会影响生活质量。毫克 目前，通过神经肌肉进行仔细的病史和身体检查，亲自评估症状 疾病专家。这种临床内评估是耗时的，主观的，仅提供了一个快照 患者的疾病，不能充分反映波动无力和症状的范围。 2019年，NIH资助了一个名为MGNET的罕见疾病临床研究联盟。该财团的重点是 改善了临床表型的表征，生物标志物的发现以及提高临床试验准备就绪 对于MG，这将增强更有效和个性化治疗的发展。在这个快速的轨道 SBIR Project，Biosensics将与马萨诸塞州综合医院合作，这是主要财团之一 对于为大约200毫克患者提供护理的MGNET - 开发和验证可穿戴传感器 溶液（MGWEAR），用于连续远程监测MG患者的运动症状和功能 安全的移动应用程序（MG应用程序），用于自动评估语音和面部特征（即 构造障碍和ptosis），这是Mg最常见的症状。移动应用程序也将启用 数据从可穿戴设备转移到符合符合生物的后端云的生物敏化云称为BioDigit 可以通过安全网站访问的云。 该项目将补充MGNET的结果和生物标志物研究，并代表重要的公共卫生 生物密度的需求和市场机会。提议的解决方案技术的关键应用和市场 是药物临床试验。可穿戴传感器和数字技术，例如这里提出的技术 将允许药物开发人员更快地测试和迭代，从而为评估功效提供了宝贵的新方法。 Biosensics是为临床试验提供可穿戴传感器和数字技术的领导者。这个项目将 通过为移动健康（MHealth）技术提供可显着扩大生物密度的产品和能力 远程监测MG和其他神经疾病中运动症状，语音和ptosis。临床上， 建议的解决方案可用于预测个人对免疫抑制药物的反应并改善 调解滴定。这样的解决方案可以使检测基于运动和数字的细微变化 生物标志物并洞悉临床疾病发作阶段。此外，日益增长的使用 远程医疗以扩大访问权限并有可能降低高质量护理的成本将需要远程评估 策略。美国有20％的州（50个州中有10个州）没有对MG的专业护理。旅行时间，距离 即使在拥有已确定的MG专家的州，成本也可能会限制患者获得专家护理的机会。提议 远程监测技术有可能减少MG患者优质护理障碍的障碍。