Alzheimer's Disease Paid Clinical Trials in California

The purpose of this study is to assess the safety, tolerability, biomarker, cognitive and clinical efficacy of investigational products in participants with an Alzheimer's disease-causing mutation by determining if treatment with the study drug slows the rate of progression of cognitive/clinical impairment or improves disease-related biomarkers. Read Less

This study aimed to pilot test a non-pharmacological (behavioral) treatment program targeting improved cognition through improving 24-h sleep-wake cycle in people with mild cognitive impairment (MCI) or mild Alzheimer's disease. A treatment program incorporating bright light therapy and a modified cognitive behavioral therapy for insomnia will be developed to address 24-hour patterns of sleep. We will then pilot test its feasibility and explore its preliminary effects on improving sleep/napping and cognition in patients with MCI or mild Alzheimer's disease. Read Less

This is a first in human study that will assess the safety and diagnostic performance of [18F]RP-115 (fluorine-18 labeled RP115), a positron emission tomography (PET) agent. This agent has the potential to identify the early changes that occur in the brains of patients with Alzheimer's disease (AD) and frontotemporal dementia (FTD). Read Less

The goal of the Alzheimer Prevention Trials (APT) Webstudy is to accelerate enrollment for Alzheimer's disease (AD) clinical trials by identifying and tracking individuals who may be at higher risk for developing AD dementia. Read Less

The PREVENTION Trial is a 12-month, two-arm randomized clinical trial (RCT) in adults 50-80 years old experiencing cognitive decline. Our study clinicians will refer patients for enrollment based on three categories: 1) a diagnosis of mild AD according to criteria established by the National Institute of Neurological and Communicative Disorders and Stroke (AD and Related Disorders Association [NINCDS-ADRDA]), 2) those with mild cognitive impairment will be diagnosed according to the Petersen method, and 3) subjective memory impairment as assessed by neuropsychological assessments and self-report. Enrollment will require evidence of AD pathophysiological processes (as defined by a positive amyloid positron emission tomography (PET) scan). The first objective is to evaluate the efficacy of a coached, data-driven, multi-modal lifestyle intervention to treat cognitive decline. Subjects will be randomized into one of two groups: Group 1 (Active Control) or Group 2 (Intervention). Group 1 (Data-driven clinical recommendations (CR)) will serve as the active control group and will receive data-driven clinical recommendations by a study physician based on study assessments and clinical lab values. Group 2 (Data-driven multi-modal intervention with coaching (MMIC)) will receive the same clinical recommendations and also an intensive multi-modal intervention with health coaching, support and resources to carry out these recommendations. This includes health coaching sessions (with an RDN), dietary counseling sessions (with an RDN), and group cognitive and physical exercise classes (CogFit) with a certified personal trainer and a computer-based neurocognitive program at home. Both groups will be measured for treatment related changes in cognitive and functional abilities, quality of life, biological, and biochemical measures. The second objective is to analyze longitudinal multi-omic data, including metabolomics, proteomics, genetics, microbiome, behavior and cognition into personalized, dense, dynamic data (i.e. PD3) from individuals with cognitive decline and underlying Alzheimer's neuropathology. The goal analysis is to identify models of causation that can further advance knowledge and research in neurodegenerative disorders and healthy living. Read Less

The eRADAR Brain Health Study seeks to refine and test a novel, low-cost strategy for increasing dementia detection within primary care. Read Less

The investigators will study performance on computerized cognitive tasks in healthy participants of different ages to gather normative data for newly developed computerized cognitive tests. These tests are designed to permit the early detection of individuals at risk of age-related cognitive decline. Read Less

The primary objective of the study is to evaluate whether a set of algorithms analysing acoustic and linguistic patterns of speech, can predict change in Preclinical Alzheimer's Clinical Composite with semantic processing (PACC5) between baseline and +12 month follow up across all four Arms, as measured by the coefficient of individual agreement (CIA) between the change in PACC5 and the corresponding regression model, trained on baseline speech data to predict it. Secondary objectives include (1) evaluating whether similar algorithms can predict change in PACC5 between baseline and +12 month follow up in the cognitively normal (CN) and MCI populations separately; (2) evaluating whether similar algorithms trained to regress against PACC5 scores at baseline, still regress significantly against PACC5 scores at +12 month follow-up, as measured by the coefficient of individual agreement (CIA) between the PACC5 composite at +12 months and the regression model, trained on baseline speech data to predict PACC5 scores at baseline; (3) evaluating whether similar algorithms can classify converters vs non-converters in the cognitively normal Arms (Arm 3 + 4), and fast vs slow decliners in the MCI Arms (Arm 1 + 2), as measured by the Area Under the Curve (AUC) of the receiver operating characteristic curve, sensitivity, specificity and Cohen's kappa of the corresponding binary classifiers. Secondary objectives include the objectives above, but using time points of +24 months and +36 months; and finally to evaluate whether the model performance for the objectives and outcomes above improved if the model has access to speech data at 1 week, 1 month, and 3 month timepoints. Read Less

Apheleia-001 is a prescreener that aims to identify and characterize participants with reported cognitive impairment using demographic information, clinical history, brief cognitive assessments, and blood-based biomarkers to distinguish appropriate participants for referral to a therapeutic AD clinical trial. Read Less

This is a proof-of-concept study designed to confirm that human phagocytic cells can be labeled with the near-infrared dye indocyanine green (ICG) and the presence of the labeled cells 48 hours later in cerebral cortex can be inferred using near infrared spectroscopy (NIRS). Read Less

The purpose of this research study is to understand the factors that underlie changes in thinking and memory with increasing age. The investigators will test the usefulness of MRI, PET, and cognitive testing in detecting subtle changes in the brain that precede cognitive decline. An addendum to this study includes additional PET scans to examine the relationship between tau protein in the brain and cognitive decline. Tau is a protein that is known to form tangles in the areas of the brain important for memory, and these tau tangles are a hallmark of Alzheimer's disease. This sub-study research aims to look at the tau accumulation in the brain using an investigational drug called MK-6240, which is a radio tracer that gets injected prior to a positron emission tomography (PET) scan. Read Less

The primary objective of the study is to evaluate whether a set of algorithms analysing acoustic and linguistic patterns of speech can detect amyloid-specific cognitive impairment in early stage Alzheimer's disease, based on archival spoken or written language samples, as measured by the area under the curve (AUC) of the receiver operating characteristic curve of the binary classifier distinguishing between amyloid positive and amyloid negative arms. Secondary objectives include (1) evaluating how many years before diagnosis of Mild Cognitive Impairment (MCI) such algorithms work, as measured on binary classifier performance of the classifiers trained to classify MCI vs cognitively normal (CN) arms using archival material from the following time bins before MCI diagnosis: 0-5 years, 5-10 years, 10-15 years, 15-20 years, 20-25 years; (2) evaluating at what age such algorithms can detect later amyloid positivity, as measured on binary classifier performance of the classifiers trained to classify amyloid positive vs amyloid negative arms using archival material from the following age bins: younger than 50, 50-55, 55-60, 65-70, 70-75 years old. Read Less