Development of a Remotely Deliverable Cognitive Assessment Sensitive to Early Stage Mild Cognitive Impairment.

摘要 随着人口老龄化，与年龄相关疾病的风险，如阿尔茨海默病(AD)及其 共同前体MCI正在增加。然而，针对预防MCI和AD的研究通常 失败，部分原因可能是在选择仍然处于危险和尚未处于危险中的人群时失败 发展为完全症状性MCI。这个项目利用了我们在新的语义干扰方面的经验 范型，并建议开发一个广泛适用的版本的Loewenstein-Acevedo量表 语义干扰与学习(拉西-L)。正如申请书正文中所指出的，拉西-L已经展示了 在国内和国际研究中，早期发现MCI前期的重大承诺，包括 在没有可检测到的认知功能的情况下识别有淀粉样蛋白沉积证据的个体 用标准的神经心理学测量的损伤。一个电脑版本的拉西，拉西- 简短的计算机化(LASSI-BC)版本已在我们的NIH初步开发和验证 资助的研究，但需要重大改进，使其适用于商业用途。这样做的目的是 第二阶段SBIR是开发下一代语义干扰度量(LASSI-D)，通过使其 对于大规模临床试验筛选和临床使用，远程交付和评分都是可行的。给定 美国和世界其他地区数以百万计的人很早就有患痴呆症的风险 干预是至关重要的，这样的评估战略的可用性将广泛增加获得 早期筛查和检测。拟议的SBIR第二阶段响应PAS-19-316，SBIR第二阶段。 具体地说，该应用程序直接专注于开发：“敏感的、特定的和标准化的测试 轻度认知障碍(MCI)和痴呆症的诊断筛查，包括开发新的、成本低廉的 有效、微创的生物标志物，可用于在普通人群和 社区设置“。在这项研究中，我们将评估LASSI-D是否也对最早时相敏感 MCI以及与基于血液的淀粉样蛋白和tau生物标志物有关。这个系统将被设计成 自我给药，因此在一般大规模临床试验筛查中广泛有用 社区环境中的人口和临床应用。我们公司正在进行第二阶段SBIR，重点是 MCI功能缺陷自理治疗系统及云端平台 功能技能评估和培训方案(FunSat)的交付将用于制定 拉西-D。我们的长期目标是开发一套商业上成功的产品，以帮助 识别、预防和治疗认知和功能衰退的风险，并保持认知健康和 老年人的功能独立。FunSat和Lassi-L的商业化努力已经开始 我们已经得到了几个大型潜在客户的承诺。

Abstract With the aging of the population, the risk for age-related conditions such as Alzheimer’s disease(AD) and its common precursor, MCI, is increasing. However, studies targeting prevention of MCI and AD have commonly failed and part of the reason may be failures in selection of a population that is still at risk and has not yet developed fully syndromal MCI. This project leverages our experience with novel semantic interference paradigms and proposes to develop a widely accessible version of the Loewenstein-Acevedo Scales for Semantic Interference and Learning (LASSI-L). As noted in the body of the application, the LASSI-L has shown significant promise for the early detection of pre-MCI, in both national and international studies including identification of individuals with evidence of amyloid deposition in the absence of detectable cognitive impairments with standard neuropsychological measures. A computerized version of the LASSI, the LASSI- Brief Computerized (LASSI-BC) version has been developed and validated on a preliminary basis in our NIH funded studies but requires significant refinement to make it applicable for commercial use. The goal of this phase II SBIR is to develop the next generation of semantic interference measures (LASSI-D), by making it feasible to remotely deliver and score, for both large-scale clinical trials screening and clinical use. Given the millions of individuals in the US and the rest of the world who are at risk for development of dementia, early intervention is critical and the availability of such as assessment strategy would broadly increase access to early screening and detection. The proposed Phase II SBIR is responsive to PAS-19-316, SBIR Phase II. In specific, this application is directly focused on development of: “Sensitive, specific, and standardized tests for diagnostic screening of mild cognitive impairment (MCI) and dementia, including the development of new, cost- effective, minimally-invasive biomarkers that could be used for screening in the general population and in community settings”. In this study we will evaluate whether the LASSI-D is also sensitive to the earliest phase of MCI as well as being related to blood-based amyloid and tau biomarkers. This system will be designed to be self- administered and hence to be widely useful for large- scale clinical trial screening in the general population and clinical use in community settings.Our company is conducting a phase II SBIR focused on a self-administered system for the treatment of functional deficits in MCI and the cloud-based platform for delivery ofthe functional skills assessment and training program (FUNSAT) will be used for the development of the LASSI-D. Our long-term goal is to develop a commercially successful suite of products that can help identify risk for, prevent, and treat cognitive and functional declines and maintain the cognitive health and functional independence of older adults. Commercialization efforts have begun for both FUNSAT and LASSI-L and we have commitments from several large-scale potential customers.