Alzheimer?s Disease (AD) is a debilitating neurodegenerative disease affecting more than 5 million Americans. Despite significant investment in drug discovery and development, no therapeutic options yet exist that can prevent, slow, or cure AD. The Accelerating Medicines Partnership in Alzheimer?s Disease Target Discovery and Preclinical Validation project (AMP-AD) was designed to help address this problem by identifying candidate targets through evaluation of AD-induced changes in human molecular state on a systems level. The program uses an open science paradigm to support early, iterative integration of resources and evaluation of findings across multiple independent teams. To extend this work we propose a cross team analytic effort to 1. Create a machine learning model of temporal Alzheimer?s disease progression. 2. Harmonize CNS model of disease progression and peripheral measures of disease state, and 3. Combine heterogeneous biomolecular networks with the molecular model of disease progression for a unified multi-scale model of disease mechanism and progression. This will amplify the impact of the individual team?s efforts, and help disentangle the molecular and temporal complexity of this devastating disease.
AD is a universally fatal disease for which no disease-modifying therapies have been successfully brought to market. The Accelerating Medicines Partnership in Alzheimer?s Disease Target Discovery and Preclinical Validation project (AMP-AD) is working to use systems biology approaches to identify candidate targets with potential therapeutic impact. By building a unified analytical framework to understand the molecular nature of the disease across multiple data modalities we will better understand early disease mechanisms, identify molecular subtypes of disease and their drivers, and improve the stratification of patients into these subtypes based on peripheral biomarkers.
