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

项目总结 重症肌无力(MG)是一种以肌肉波动为特征的慢性自身免疫性神经肌肉疾病 影响日常生活活动并对生活质量产生负面影响的虚弱和症状。镁 目前，症状是由神经肌肉医生通过仔细的病史和体检来亲自评估的 疾病专家。这样的临床评估是耗时的、主观的，只能提供 患者的疾病，不能充分反映波动的虚弱和症状的频谱。 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 改善临床表型特征，发现生物标记物，推进临床试验准备 对于MG来说，这将促进更有效和个性化治疗的发展。在这条快速通道中 SBIR项目，BioSensics将与马萨诸塞州综合医院-主要联盟地点之一-合作 为大约200名MG患者提供护理的MGNet-开发和验证可穿戴传感器 解决方案(MGWear)，用于持续远程监测MG患者的运动症状和功能，还 一种用于自动评估语音和面部特征的安全移动应用程序(MG APP)。 构音障碍和上睑下垂)，这是MG最常见的症状。移动应用程序还将启用 将数据从可穿戴设备传输到名为BioDigit的符合BioSensics HIPAA标准的后端云 可通过安全网站访问的云。 该项目将补充MGNet的成果和生物标记物研究，并代表重要的公共卫生 生物传感的需求和市场机会。建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，就像这里提出的技术 将允许药物开发人员更快地进行测试和迭代，为评估疗效提供了一种有价值的新方法。 BioSensics在为临床试验提供可穿戴传感器和数字技术方面处于领先地位。这个项目将 通过提供移动医疗(MHealth)技术，显著扩展BioSensics的产品和功能 远程监测MG和其他神经系统疾病的运动症状、言语和上睑下垂。在临床上， 提出的解决方案可以用来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检测基于移动的和数字的细微变化 生物标志物，并提供对临床疾病发病阶段的洞察。此外，越来越多的人使用 远程医疗以扩大获取范围并有可能降低高质量护理的成本，将需要远程评估 战略。美国有20%的州(50个州中有10个)没有对MG进行专门护理。旅行时间、距离 费用可能会限制患者获得专家护理的机会，即使在拥有指定的MG专家的州也是如此。建议数 远程监测技术有可能减少MG患者获得优质护理的障碍。

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.