药物开发中的数字健康技术：示范项目
正文 · 中文译文
药物研发中的数字健康技术：示范项目 科学与研究专题 数字健康技术 推进监管科学 临床试验与人类受试者保护 关键路径倡议 人工智能与医疗产品 FDA的纳米技术项目 新方法学（NAMs） 儿科 科学信息与评估的同行评审 真实世界证据 风险沟通 女性健康研究 为促进与外部利益相关方的共同学习和理解，FDA继续通过多种渠道和项目监督并支持众多关于数字健康技术（DHTs）的示范（即研究）项目，包括FDA的广泛机构公告、CERSI项目及其他资助机会。 以下列出我们当前部分由FDA资助的DHTs项目： 建立肌萎缩侧索硬化症（ALS）中通过可穿戴数字传感器测量的步态速度（SV95C）的临床试验准备 获奖者：马萨诸塞州总医院 项目描述：本项目的主要目标是完成步速第95百分位数（SV95C）在肌萎缩侧索硬化（ALS）患者中的可用性和临床验证，提供支持其作为II期和III期ALS临床试验次要或探索性终点所需的证据。该研究将通过评估SV95C与ALS传统结局指标的关系，确立其结构效度和纵向反应性。该研究还将通过使用总体变化评分和临床重要里程碑（例如，丧失行走能力）估计有意义的患者内变化，以支持终点开发和试验设计，从而确立数字活动能力测量用于临床试验的临床意义和终点性能。该研究将力求了解患者对数字活动能力测量的可用性和临床意义的看法。 运动功能的数字生物标志物作为药物开发工具在腓骨肌萎缩症中的应用 获奖者：Biosensics， LLC 项目描述：腓骨肌萎缩症（Charcot-Marie-Tooth，CMT）是一组导致神经损害的遗传性疾病，主要累及周围神经，而周围神经负责手臂和腿部的运动与感觉。CMT的特征是进行性肌无力和肌萎缩，尤其见于足、腿、手和臂。本项目的主要目标是确立可穿戴设备衍生的数字生物标志物用于监测CMT1A上肢和下肢功能的有效性和可靠性，从而实现标准化的诊室内测量以及客观、可扩展且对临床有意义变化敏感的频繁居家评估。该研究将评估可穿戴传感器衍生的足下垂指标；在日常生活活动中被动采集的可穿戴传感器衍生的行走指标；以及在日常生活活动中被动采集的可穿戴传感器衍生的上肢使用指标，所有这些均作为成人CMT1A患者的纵向结局指标。该研究还将包括定性患者访谈，考察对该技术的感知有用性、感知易用性和使用态度。 测量亨廷顿病中的数字临床终点（MEND-HD） 获奖者：罗切斯特大学 项目描述：本项目旨在证明两个关键数字测量指标——日常生活活动能力（步态）和舞蹈症——在早期亨廷顿病（HD）中的可靠性、有效性和意义，这两个指标通过可穿戴传感器进行远程和连续采集。亨廷顿病是一种无法治愈的罕见进行性神经退行性疾病。此外，本项目将探索日常身体活动、心率变异性和睡眠的可靠性和有效性。这些测量指标有潜力成为亨廷顿病临床试验结局的有意义终点，但首先需要解决关键缺口。随着遗传干预和疾病修饰干预的出现，迫切需要对亨廷顿病中疾病特异性运动障碍进行早期和准确评估。传统测量方法具有主观性和片段性，捕捉早期、更细微运动特征的能力有限。数字测量指标有潜力远程量化疾病特异性损伤。本研究将为亨廷顿病更大规模的验证工作和临床终点研究提供信息，并有可能影响其他更常见的伴不自主运动的神经系统疾病（例如帕金森病）。 通过多重插补技术的严格模拟研究提高新型数字健康技术衍生终点的完整性 CERSI项目：UCSF Stanford 项目描述：本项目的目标是增进对可穿戴设备数据的理解。为此，研究人员将：（1）开发一个开源工具，利用已完成的临床试验数据库帮助模拟来自可穿戴设备的患者数据，包括非佩戴期；（2）创建并测试处理非佩戴期的策略；（3）为推荐策略建立开源代码。总体而言，科学的进步将有助于将患者可穿戴设备的数据转化为可用于为所有患者获得更好治疗的证据。 以数字健康技术（DHT）为中心的新型统计方法，用于受试者水平指纹识别和处理缺失数据 CERSI项目：约翰斯·霍普金斯 项目描述：项目研究人员提出开发新型统计方法，以基于个体的体力活动和睡眠模式验证DHT数据是否由同一个人生成，并通过结合时间序列、函数型和分布型数据分析工具来填补DHT数据中的缺失数据空白。 开发以活动记录仪体力活动和心率测量作为敏感研究终点的复合评分，以促进数字健康技术在儿科临床试验和药物开发中的应用 获奖者：美国国家标准与技术研究院（NIST） 项目描述：本项目旨在利用科学计算方法的力量，推进活动记录仪终点在儿童肺动脉高压（PAH）临床试验中的应用。我们计划实现三个主要目标：（1）开发一个结合活动记录仪体力活动和心率测量的复合评分；（2）检验该复合评分在PAH患儿中用于评估疾病严重程度和检测疾病进展的应用；（3）引入一个框架，将活动记录仪的应用扩展到更广泛的数字健康技术领域和其他儿科疾病。目标是以有节制的方式使用活动记录仪数据，以满足儿童PAH和其他儿童罕见病中未被满足的需求。 开发用于儿童和成人特应性皮炎的客观定量终点 获奖者：Emerald Innovations， Inc. 项目描述：本项目的目标是开发一个客观、定量且用户友好的数字终点，用于评估特应性皮炎患儿的夜间抓挠。该终点将通过评估FDA监管的特应性皮炎和瘙痒症产品的疗效和性能，满足一项关键且未被满足的需求。目前，这些评估严重依赖于主观自我报告的终点，如NRS（数字评定量表）。将开发一个基于无线电信号评估夜间抓挠的机器学习模型，以在抓挠和疾病负担方面与健康对照进行比较。 利用移动健康（mHealth）测量接受精神药物治疗的儿童和青少年在功能行为、活动及睡眠模式方面的影响 CERSI项目：马里兰大学 项目描述：本项目旨在借助移动技术的力量实现三个主要目标：（1）填补行为、功能和活动数据采集方面的空白；（2）减轻患者、照护者和医疗服务提供者在采集与治疗及照护管理相关的、具有可操作性的相关数据方面所面临的负担；（3）识别治疗开始或变更后行为改变的严重程度、不良事件/继发效应的发生率，以及用药模式和依从性模式。最终目标是将这些数据与更大的数据系统和现有数据源整合，以支持标签或实践模式的变更。 评估移动健康工具在捕捉心力衰竭患者以患者为中心的结局测量中的应用 CERSI项目：耶鲁-梅奥 项目描述：本项目的目标是测试在心力衰竭（HF）患者中使用可穿戴传感器连续60天采集可量化的功能容量和生活质量（QoL）指标的可行性和可靠性。急性失代偿性心力衰竭（ADHF）患者将在出院后从新加坡国家心脏中心和国家大学医院招募。患者将在家里使用Biofourmis的BiovitalsHF™平台进行监测，该平台将从两种可穿戴设备采集生物传感器数据：Everion®和Apple Watch Series 4。患者还将使用BiovitalsHF™智能手机应用程序采集电子患者报告结局（ePROs），如用药依从性、症状、堪萨斯城心肌病问卷（KCCQ）回答，并进行引导式基于移动端的2分钟踏步测试。 内容截至日期： 2026年10月30日 受监管产品 药物
正文 · 英文原文
Digital Health Technologies for Drug Development: Demonstration Projects Science and Research Special Topics Digital Health Technologies Advancing Regulatory Science Clinical Trials and Human Subject Protection Critical Path Initiative Artificial Intelligence and Medical Products Nanotechnology Programs at FDA New Approach Methodologies (NAMs) Pediatrics Peer Review of Scientific Information and Assessments Real-World Evidence Risk Communication Women's Health Research To promote shared learning and understanding with external stakeholders, FDA continues to oversee and support numerous demonstration (i.e., research) projects on Digital Health Technologies (DHTs) through multiple venues and programs including FDA’s Broad Agency Announcement, CERSI Program, and other funding opportunities. Below lists some of our current FDA-funded projects on DHTs: Establishing Clinical Trial Readiness for Gait Velocity (SV95C) Measured from Wearable Digital Sensors in Amyotrophic Lateral Sclerosis (ALS) Awardee: Massachusetts General Hospital Project Description: The primary aim of this project is to complete the usability and clinical validation of stride velocity 95th centile (SV95C) in patients with Amyotrophic Lateral Sclerosis (ALS), providing the evidence needed to support its use as a secondary or exploratory endpoint in Phase II and III ALS clinical trials. The study will establish construct validity and longitudinal responsiveness of SV95C by evaluating its relationship to traditional outcome measures in ALS. The study will also establish the clinical meaningfulness and endpoint performance of digital mobility measures for clinical trials by estimating meaningful within-patient change using Global Rating of Change and clinically important milestones (e.g., loss of ambulation) to support endpoint development and trial design. The study will seek to understand patient perspectives on usability and clinical meaningfulness of digital mobility measures. Digital Biomarkers of Motor Function as Drug Development Tools in Charcot-Marie-Tooth Disease Awardee: Biosensics, LLC Project Description: Charcot-Marie-Tooth (CMT) disease is a group of inherited disorders that cause nerve damage, primarily affecting the peripheral nerves, which are responsible for movement and sensation in the arms and legs. CMT is characterized by progressive muscle weakness and atrophy, particularly in the feet, legs, hands and arms. The primary goal of the project is to establish the validity and reliability of wearable-derived digital biomarkers for monitoring upper and lower limb function in CMT1A, enabling both standardized in-clinic measurement and frequent at-home assessment that is objective, scalable, and sensitive to clinically meaningful change. The study will evaluate wearable sensor-derived foot drop metrics; wearable sensor-derived ambulation metrics passively acquired during activities of daily living; and wearable sensor-derived upper limb use metrics passively acquired during activities of daily living, all as longitudinal outcome measures in adult CMT1A patients. The study will also include qualitative patient interviews that examine perceived usefulness, perceived ease of use, and attitude toward use of the technology. Measuring Digital Clinical Endpoints in Huntington's Disease (MEND-HD) Awardee: University of Rochester Project Description: This project aims to demonstrate the reliability, validity, and meaningfulness of two key digital measures, daily living mobility (gait) and chorea, captured remotely and continuously using wearable sensors, in early-stage Huntington’s disease (HD), a rare, progressive neurodegenerative disease with no cure. Additionally, this project will explore the reliability and validity of daily physical activity, heart rate variability, and sleep. These measures have the potential to be meaningful endpoints for clinical trial outcomes in HD, but critical gaps first need to be addressed. As genetic and disease-modifying interventions emerge, there is an urgent need for early and accurate assessment of disease-specific motor impairments in HD. Traditional measures are subjective and episodic with a limited ability to capture early, more subtle motor features. Digital measures have the potential to remotely quantify disease-specific impairments. This study will inform larger-scale validation efforts and clinical endpoint studies in HD with the potential to impact other, more common neurological diseases with involuntary movements (e.g., Parkinson’s disease). Improving the Integrity of Novel Digital Health Technology-derived Endpoints through Rigorous Simulation Studies of Multiple Imputation Techniques CERSI Program: UCSF Stanford Project Description: The goal of this project is to improve understanding of data from wearable devices. To that end, investigators will: (1) develop an open-source tool to help simulate patient data from wearables including non-wear periods using databases from completed clinical trials; (2) create and test strategies for handling non-wear periods; and (3) establish open source code for recommended strategies. Overall, advancement of science will help take data from patient wearables and translate them into evidence that can be used to get better treatments for all patients. Novel DHT-centric statistical methods for subject-level fingerprinting and handling missingness CERSI Program: Johns Hopkins Project Description: Project investigators propose to develop novel statistical methods to verify that the DHT data has been generated by the same individual based on their physical activity and sleep patterns, and fill in missing data gaps in DHT data by combining tools from time series, functional, and distributional data analyses. Developing a Composite Score with Actigraphy Physical Activity and Heart Rate Measurements as a Sensitive Study Endpoint to Facilitate the Use of Digital Health Technology in Pediatric Clinical Trials and Drug Development Awardee: The National Institute of Standards and Technology (NIST) Project Description: This project aims to use the power of the scientific computation approach to advance the use of actigraphy endpoints in pediatric pulmonary arterial hypertension (PAH) clinical trials. We plan to achieve three primary objectives: (1) Develop a composite score with actigraphy physical activity and heart rate measurements; (2) Examine the use of the composite score in children with PAH to assess disease severity and detect disease progression; (3) Introduce a framework to expand the use of actigraphy to a broader digital health technology space and other pediatric diseases. The goal is to use actigraphy data in a measured way to address the unmet need in pediatric PAH and other pediatric rare diseases. Developing an Objective and Quantitative Endpoint for Atopic Dermatitis in Pediatric and Adult Populations Awardee: Emerald Innovations, Inc. Project Description: The goal of this project is to develop an objective, quantitative, and user-friendly digital endpoint to assess nocturnal scratching in children with atopic dermatitis. This endpoint will fulfill a crucial unmet need by for assessing the efficacy and performance of FDA-regulated products for atopic dermatitis and pruritus. Currently, these assessments heavily rely on subjective self-reported endpoints like the NRS (Numeric Rating Scale). A machine learning model for assessing nocturnal scratching from radio signals will be developed to draw comparison to healthy controls in terms of scratching and disease burden. Using mHealth to Measure Impact in Functionality Behavior, Activity and Sleep Patterns in Children and Adolescents Treated with Psychotropics CERSI Program: University of Maryland Project Description: This project aims to leverage the power of mobile technology to address three primary objectives: (1) fill the gap in the capture of behavioral, functional and activity data; (2) ease the burden on patients, caregivers, and providers struggling to capture relevant and actionable data related to treatment and care management; (3) identify severity of behavioral changes after treatment initiation or change, rates of adverse events/secondary effects, along with patterns of medication use and adherence. The ultimate goal is to integrate these data with larger data systems and existing data sources to support changes in labeling or in practice patterns. Evaluation Mobile Health Tool Use for Capturing Patient-Centered Outcome Measures in Heart Failure Patients CERSI Program: Yale-Mayo Project Description: The goal of this project is to test the feasibility and reliability of capturing quantifiable measures of functional capacity and quality of life (QoL) using a wearable sensor in heart failure (HF) patients for a period of 60 days. Acute Decompensated Heart Failure (ADHF) patients will be recruited post-discharge from the National Heart Centre and National University Hospital in Singapore. Patients will be monitored at home using the Biofourmis' BiovitalsHF™ platform which will capture biosensor data from two wearable devices: Everion® and Apple Watch Series 4. Patients will also use the BiovitalsHF™ smartphone application to capture electronic patient reported outcomes (ePROs) such as medication adherence, symptoms, the Kansas City Cardiomyopathy Questionnaire (KCCQ) responses, and perform the guided mobile-based 2-minute-step-test. Content current as of: 10/30/2026 Regulated Product(s) Drugs