Active clinical trials for "Alzheimer Disease"

A multi-center, double-blind, placebo-controlled out-patient, safety, tolerability, and pilot efficacy study of intramuscular AN-1792 in patients with mild to moderate Alzheimer's disease.

This is a 15-month study with two phases. During the first 12-month phase of this study, patients will be randomly assigned to receive either active study drug or placebo (approximately half of all patients will be on active study drug, the other half on placebo). The second phase is a 3-month randomized withdrawal period. For this phase approximately 10% of the patients will remain on the active drug.

Patients with Mild Cognitive Impairment (MCI) or Subjective Cognitive Decline (SCD) may or may not develop Alzheimer's disease (AD) dementia. Yet identifying patients at risk is crucial: delaying the onset of the disease by 5 years could reduce prevalence by 50%. To achieve this, we need affordable biomarkers combined with clinically meaningful assessment tools. Current approaches (cognition, imaging or Tau and Amyloid peptide assays) lack precision or specificity (e.g., age-related memory deficits) and involve invasive and costly procedures, sometimes inaccessible in France (e.g., the "AT(N)" framework). Recently, quantitative diffusion MRI (dMRI) has identified in-vivo gray matter microstructural changes linked to hyperphosphorylated Tau protein, which are of great diagnostic value. Still, we ignore whether and how these changes are responsible for early memory impairment in AD. The MIMA-P project will combine multi-compartment models of the high-resolution diffusion signal with a cognitive assessment of memory based on recent models of medial temporal lobe function to assess the relevance of a new affordable, rapid and non-invasive early marker of the disease.

In this explorative longitudinal study 50 patients with Alzheimer's disease (AD) and 50 age-matched control subjects will be recruited for their 2 years follow-ups and undergo extensive cognitive testing and quantitative 3 Tesla magnetic resonance imaging (MRI). Regional differences of susceptibility and R2* relaxation rates in deep gray matter and the neocortex will be evaluated in AD patients and controls and related to the patients´ cognitive status at baseline.

To investigate the brain receptor occupancy of idalopirdine in patients with Alzheimer's disease (AD)

The purpose of this project is to study the aging brain among participants enrolled in the Health and Aging Brain Study: Health Disparities project . There are a number of things that can influence how people think as they age, including diabetes, depression, as well as our biology. In this study, the investigators seek to study the aging brain by using brain PET scans that create detailed pictures of the brain.

The aim of the NODAL clinical trial is to demonstrate the feasibility of new, low-cost, non-invasive biomarkers of neurodegenerative pathologies as early Alzheimer and Parkinson, based on the estimation of the multimodal connectome.

Alzheimer's disease (AD) is characterised by a progressive loss of memory and cognitive function. In the early stages of AD, there is a progressive accumulation of molecules: β-amyloid peptides (Aβ) in the brain. There is a link between the accumulation of Aβ peptides and the deterioration of sleep, but current knowledge does not confirmed this link. The objective of this study is to define whether there is a link between cognitive decline and sleep disorders. If a correlation is found, this could allow earlier treatment of sleep disorders in the longer term in order to slow the development of AD.

This study will compare smartphone usage data between three groups of patients diagnosed with either a memory complaint, mild cognitive decline, or Alzheimer's disease.

The goal of this observational trial is to leverage the electronic Self-Administered Gerocognitive Examination (eSAGE), a variety of metadata (a set of data that describes and gives information about other data) collected during eSAGE testing, electronic health records (EHR) information, and advanced machine learning (ML) techniques to develop a new tool that can aid in early-stage prediction of individuals with cognitive impairments.