There are no effective drugs to prevent Alzheimer?s disease (AD). We seek to prevent onset or progression of AD by discovering and enhancing the activity of naturally occurring pathways that prevent its occurrence. This natural resilience is significant because it is the only known manner in which Alzheimer?s appears to be controlled. Here, we exploit the fact that a proportion of the aging population appear to remain cognitively intact while controlling or compensating AD related Tau pathology and enjoy a relative natural resistance to cognitive impairment or diagnosis of AD. Using whole genome sequencing (WGS) and transcriptome analysis of a naturally AD-resilient population, we will identify novel drug-sensitive resilience associated (RA) pathways in AD. We will implement a novel, validated technology, the Pathway Drug Network (PDN), constructed from human gene expression data enriched in drug?pathway?gene clusters, to identify drugs that enhance RA pathways. First round screening of the PDN-predicted single or combinations of leads will be tested in our innovative 3D human neural cell culture models of AD, which recapitulate various pathogenic stages of AD including Ab deposition (Ab plaque), Ab-driven tau pathology (neurofibrillary tangles (NFTs), and neuroinflammation and neurodegeneration. Validated leads will then be scored in transgenic AD mouse models for reduction of synaptic loss and cognitive integrity. The approach will establish the basis for a therapeutic intervention that can prevent or reduce cognitive decline related to AD. Intellectual merit: This project will significantly advance the understanding of neuroprotection in aging adult human brains while providing novel insights into the relationships between control of AD related pathology and loss of cognition. Broader impact: AD increasingly affects the aging population and there is no effective intervention. Reduction of its incidence will be of major significance. If successful, the project will allow development of clinical application of novel drugs or repurposed FDA approved drugs while creating a powerful new paradigm for developing successful AD drug combinations. Aim1: Using network analytical techniques, we will generate a molecular systems definition of RA pathways using pathways, genes and network modules from whole genome sequencing data and literature, and post mortem brain transcriptomes that show resilient high or low plaque/tangle, low AD symptoms, but high cognitive scores. Aim 2: Compare RA pathways within PDN to predict drug/pathway combinations that confer resilience. A series of drug-repurposing screens will optimise lists of ranked drugs/combinations and pathway activity. Selected combinations will be validated in multiple 3D human neural cell culture models of AD that mimic various pathogenic stages of AD for their impact on AD pathogenic markers. Aim 3: Validate using proxies of cognition in an AD transgenic APP mouse model. Score for the ability to confer resilience and neuroprotection in AD transgenic mouse models for either Ab deposition, synaptic/cognitive deficits and/or neuroinflammation.