ADMdx presents at the Alzheimer’s Disease Neuroimaging Initiative (ADNI) Private Partner Scientific Board meeting on machine learning and early-frame amyloid PET to measure neuronal activity based on cerebral blood flow. Our technology optimizes the information obtained from the first few minutes after injection of amyloid PET tracers such as florbetapir. Information about neurodegeneration and amyloid burden can thus be obtained from the same scan.
ADMdx’s analysis of tau PET in Down Syndrome patients with emerging Alzheimer’s disease to be presented on December 5 at CTAD 2016. Dr. Michael Rafii, Principal Investigator of the Down Syndrome Biomarker Initiative (DSBI) study, will present ADMdx’s analysis of tau PET image data in adult patients with Down Syndrome at CTAD. This analysis showed a striking association between the presence of tau as measured using the PET tracer AV1451 (Avid Radiopharmaceuticals) and amyloid positivity, and is the first to report findings in DS adults using AV-1451.
ADMdx participates in Alzheimer’s Association Greater Illinois Chapter Annual Research Symposium, an important intersection of research and clinical care ADMdx exhibited at the Annual Scientific Symposium held by the Greater Illinois Chapter of the Alzheimer’s Association. Focus was on the diagnosis and clinical management of Alzheimer’s disease, including the integration of imaging biomarkers into clinical assessment. The symposium included several excellent talks from members of Northwestern University, Rush Medical Center, and other institutions. The strong attendance and interest shown by caregivers, patients, and the medical community reflected the importance of education, access to information and care, and the advancement of diagnostic and therapeutic approaches in dementia.
ADMdx presents advances at the Alzheimer’s Association International Conference in Toronto, July 26 and 27. ADMdx will present three posters at the conference: Measurement of Amyloid Burden Using the Early Frames of Amyloid PET and a Multivariate Classifier” and “Combining Neurodegenerative Characterization with Amyloid Burden Measurement Using an Early Frame Amyloid PET Multivariate Classifier”. The first presentation demonstrates application of ADMdx classifier technology to the first few minutes of an amyloid scan to measure neurodegeneration, enabling better patient characterization and prediction of clinical worsening for stratification. The second presentation introduces novel ADMdx technology allowing detection of amyloid burden during the first 20 minutes of a PET scan, in contrast to current 50 – 70 minute wait times.
Our CTO, Dr. Miles Wernick, was interviewed by Crain’s Chicago Business about how ADMdx was started and its technology to diagnose and predict dementia.
ADMdx publishes work demonstrating the potential of ADMdx image analysis technology to detect Alzheimer’s disease and treatment effects in at-risk, enriched populations. Adults with Down Syndrome (DS) provide a potentially enriched population for the preclinical and prodromal evaluation of Alzheimer’s disease (AD) therapeutics due to their accelerated rate of amyloid plaque formation and development of AD. However, conducting clinical trials in this population requires the ability to identify subjects with a known stage of AD, as well as the capability to detect AD-specific treatment effects distinct from those upon DS. ADMdx technology has achieved differentiation of AD from DS within subjects using either MRI or FDG PET imaging, enabling study of AD interventional treatments. Work was performed in collaboration with Dr. Michael Rafii of the University of California, San Diego and the Alzheimer’s Disease Cooperative Study (ADCS). This work has been published in the June 2016 issue of Alzheimer’s & Dementia: Translational Research and Clinical Intervention.
ADMdx awarded Phase IIB SBIR grant from the National Science Foundation. The grant provides funding to further our development of a multi-modality Alzheimer’s Disease Progression Classifier, which stages preclinical through dementia AD patients and predicts clinical trajectory, and a Dementia Classifier, which distinguishes different types of dementia.
