Research Project 3 will develop novel, objective, and portable measures of Parkinson disease features

研究项目 3 将开发新颖、客观、便携的帕金森病特征测量方法

• 批准号: 10459492
• 负责人: Suchi Saria
• 金额: $ 27.7万
• 依托单位: UNIVERSITY OF ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-30 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10459492
• 关键词: Algorithms; Android; Apple; Biophysics; Bradykinesia; Caring; Categories; Cellular Phone; Clinic; Clinical; Clinical Trials; Communities; Country; Data; Development; Devices; Disease Progression; Enrollment; Equilibrium; Evaluation; Gait; Generations; Gold; Incidence; Individual; Information Technology; Levodopa; Measurement; Measures; Monitor; Motor; Movement Disorder Society Unified Parkinson' s Disease Rating Scale; National Institute of Neurological Disorders and Stroke; Noise; Outcome Measure; Parkinson Disease; Persons; Pharmacologic Substance; Phase; Proxy; Recommendation; Reproducibility; Research; Research Personnel; Research Project Grants; Sample Size; Severities; Severity of illness; Signal Transduction; Socialization; Supercomputing; Symptoms; Time; Travel; Universities; Validation; Voice; base; cost; data sharing; improved; innovation; mathematical analysis; neural network; next generation; novel; open source; phase II trial; portability; research study; response; sensor; signal processing; smartphone Application; standard measure; tool; validation studies

SUMMARY Current PD measures are largely limited to the clinic and based on episodic, rater-dependent, categorical scales. The result is that the clinical trials, even early stage ones, require large sample sizes, long durations, and high costs. Moreover, these measures are prone to generating false signals of efficacy in phase 2 trials that are not found in phase 3 and likely generate missed signals of efficacy that are never detected. In the 21st century new tools are available that can generate objective, frequent, sensitive assessments of PD in real-world settings. These super computing devices, or smartphones, are increasingly ubiquitous and powerful. In March 2015, Apple released ResearchKit, an open-source platform for creating smartphone research studies. At the same time, five smartphone research studies, including one for PD (mPower), were also launched. In seven months, over 70,000 individuals across the country enrolled in these studies. Through the P20 and related efforts, we have demonstrated that assessments of voice, gait, balance, and bradykinesia conducted on the smartphone can differentiate individuals with PD from those without, correlate with traditional PD assessments, detect response to levodopa, and can be quantified in a novel mobile PD score that correlates with the MDS-UPDRS but can be administered by almost anyone anywhere anytime. In Research Project 3, we will evaluate the next generation smartphone research application (mPower 2.0) against current gold standard clinical measures of PD, assess its ability to generate novel assessments of socialization based on passively collected data, refine the mobile PD score, and improve the replicability and reproducibility of the score using advanced signal processing algorithms and neural networks In just two years after their large scale introduction, pharmaceutical companies and academic investigators are already incorporating these devices into their clinical trials. This Research Project will help accelerate these efforts to use smartphones to generate objective, passive and active, frequent real-world assessments of motor and non-motor function in PD.

总结 目前的PD测量主要限于临床，并且基于发作性的、评级依赖的、分类的 鳞片结果是，临床试验，即使是早期阶段的临床试验，也需要大样本量，长时间， 和高成本。此外，这些措施在2期试验中容易产生疗效的错误信号 在阶段3中没有发现，并且可能产生从未检测到的遗漏的有效性信号。 在21世纪的世纪，新的工具可以产生客观的，频繁的，敏感的评估PD 在现实世界中。这些超级计算设备或智能手机越来越普遍， 强大. 2015年3月，苹果发布了ResearchKit，这是一个创建智能手机的开源平台 调查研究。与此同时，五项智能手机研究，包括一项针对PD（mPower）的研究， 也推出了。在7个月内，全国有7万多人参加了这些研究。 通过P20和相关的努力，我们已经证明，对声音、步态、平衡和 在智能手机上进行的运动迟缓可以区分患有PD的个体与没有PD的个体， 使用传统的PD评估，检测对左旋多巴的反应，并可在新型移动的PD中进行量化 与MDS-GRS相关的评分，但几乎任何人都可以随时随地进行管理。 在研究项目3中，我们将评估下一代智能手机研究应用（mPower2.0） 对照当前PD的金标准临床指标，评估其产生以下新评估的能力： 基于被动收集的数据进行社交，完善移动的PD评分，并提高可复制性， 使用先进的信号处理算法和神经网络的分数的再现性 在大规模引进后的短短两年里，制药公司和学术研究人员 已经将这些设备纳入临床试验。该研究项目将有助于加快这些 努力使用智能手机来生成客观的，被动的和主动的，频繁的现实世界的评估， 运动和非运动功能在PD。