PREVENT ALZHEIMERS DISEASE 2020 INC

In the United States two major regulatory hurdles must be overcome for affordable and accessible tools to be developed and deployed for diagnosing assessing and monitoring those at risk of or with cognitive disorders. The FDA and CMS have two different regulatory missions. Developers of new clinical interventions and tools must demonstrate the effectiveness and clinical relevance of their outcomes. They also need to consider factors such as reimbursement and quality. To address these challenges the Campaign to Prevent Alzheimers Disease launched a task force to review recommendations and develop new project proposals. The group titled "The Campaign to Prevent Alzheimers Disease Work Group on Community-Based Detection and Assessment of Cognitive Decline," identified different pathways of community-based detection using electronic health records from different international healthcare systems to detect and monitor individuals with early cognitive impairment. The recommendations aim to guide future sustainability activities public policy campaigns and implementation pilots.

Alzheimers disease poses a significant burden on a global scale which has led to an enormous investment in research to find a cure. However despite these efforts there are very few medications available for people with dementia. The search for new interventions for Alzheimers disease is challenging because the exact relationship between the symptoms of the disease and its neurobiology is not yet fully understood. The diseases heterogeneity complex biological and environmental interactions multiple nonlinear timescales and a lack of modeling systems to integrate complex relationships further complicate this effort. To address these challenges the Calcium System Theory of Alzheimers Disease CAST-AD workgroup aims to design a unified systems theory. The group aims to create new foundational models to study protein dynamics and aggregation in neurodegenerative diseases. These models will be trained using supercomputing and hybrid super- and quantum-computing to simulate large data sets of proteins. The project will establish and validate foundational models using proteins such as bioluminescent enzymes to provide an easy functional readout. The group will then apply these models to crucial proteins and peptides involved in neurodegenerative diseases.