Development and validation of novel tests in the DCT drawing analysis platform for the detection of Alzheimer’s Disease-related early cognitive impairment

项目摘要/摘要 早期发现阿尔茨海默病和阿尔茨海默病相关痴呆对于开发新型治疗药物和 进行有效的病人治疗和护理。DCT已经创建了一个能够检测行为细微变化的平台 通过使用数字笔记录绘画动作并自动提示早期认知障碍 使用人工智能和神经心理学分析相结合的方法来分析这些数据。DCT有 成功地在DCTclockTM平台上进行了第一次测试，该平台已被证明可以检测到细微的 早期阿尔茨海默病(AD)和AD相关痴呆的认知改变早于标准认知 测试，与已知的AD生物标志物，如临床前AD患者中的淀粉样蛋白和tau相关，并检测 认知健康参与者中已知的载脂蛋白E遗传风险。该测试获得了FDA批准上市的通用性 认知评估，目前用于跨国临床试验、研究计划和实践 临床医生为病人提供护理。DCT现在正在进行一项涉及400名参与者的研究，参与者的认知范围从 从健康到疯狂验证平板电脑作为图形数据的输入设备，并收集一组 新颖的平板绘画任务包括：符号任务、视觉保持任务、轨迹绘制任务、路径绘制任务 寻找任务和视觉建构任务。 我们的目标是分析研究中收集的任务数据，以产生一套易于部署、快速、经济高效的 敏感测试将在AD和AD相关痴呆的临床试验中用作认知数字生物标记物。 第一个目标是从这些额外的测试中开发新的认知测量方法，并获得初步的 验证。现有数据将被分成训练集和测试集。将对训练集进行分析以开发 指标，遵循带有低级绘图测量的可解释的分层分析结构 组合成一组与认知概念(即信息处理)捆绑在一起的复合量表，然后 进一步结合在一起，得到了简单的0-100分的测试表现。测试集将用于 进行初步验证，包括接收器工作特性曲线分析、关联 对现有神经心理测试的措施，以及确保重复性的重测信度测量 测试稳定性。第二个目标是将所开发的度量在商业DCT平台上实现。 将为新指标的测量、存储和显示创建强大的软件，设置 基金会，使研究和商业合作伙伴能够使用这些指标。

Project Summary/Abstract Early detection of AD and AD-related dementias is critical for the development of novel therapeutic agents and for effective patient treatment and care. DCT has created a platform able to detect subtle changes in behavior indicative of early cognitive impairment by using a digital pen to record drawing motions and automatically analyzing that data using a combination of artificial intelligence and neuropsychological analysis. DCT has successfully launched its first test on the platform, DCTclockTM, which has been demonstrated to detect subtle cognitive change in early Alzheimer’s Disease (AD) and AD-related dementias earlier than standard cognitive tests, correlate with known AD biomarkers such as amyloid and tau in preclinical-AD subjects, and detect known APOE genetic risk in cognitively healthy participants. The test is FDA-cleared to market for general cognitive assessment and is currently used in multinational clinical trials, research initiatives, and by practicing clinicians for patient care. DCT is now conducting a study involving 400 participants ranging from cognitively healthy to demented to validate a tablet as input device for the drawing data, and to collect data on a set of novel tablet-based drawing tasks including: a symbol task, a visual retention task, a trail making task, a path- finding task, and a visuoconstructional task. We aim to analyze task data collected in the study to produce a set of easily-deployable, rapid, cost-effective, and sensitive tests to be used as cognitive digital biomarkers in clinical trials for AD and AD-related dementias. The first aim is to develop novel cognitive measures from these additional tests and obtain preliminary validation. Existing data will be split into training and testing sets. The training set will be analyzed to develop metrics, following an interpretable hierarchical analysis structure with low-level drawing measurements combined in a set of composite scales tied to a cognitive concept (i.e., information processing), and then further combined to obtain a simple 0-100 score for performance on the test. The testing set will be used to conduct preliminary validation consisting of a Receiver Operating Characteristic curve analysis, correlation measures to existing neuropsychological tests, and test-retest reliability measurements to ensure repeat testing stability. The second aim is to implement the developed metrics in the commercial DCT platform. Robust software will be created for the measurement, storage, and display of the novel metrics, setting a foundation to enable usage of the metrics by research and commercial partners.