Alzheimer’s disease (AD) has a major impact on daily functioning and quality of life and is characterized by a huge socio-economic burden, with at least 50 million persons affected worldwide. There is currently no disease modifying treatment, which can be attributed to important knowledge gaps. For clinical practice, we need algorithms based on easily accessible and time- and cost-effective tests like blood-based biomarkers and digital cognitive tests for personalized diagnosis, prognosis and correct symptomatic treatment. For clinical trial development, we need to optimize the screening procedure to accurately identify individuals with AD in pre-symptomatic stage or prodromal disease stages and predict progression rates at an individual level. The methods need to be robust and generalizable, and the test results need to be optimally communicated to patients. This initiative, EDAP-AD, brings together members from Denmark, France, Germany, Spain and Sweden with expert knowledge in AD, biomarkers, and test disclosure processes. We will leverage demographically and ethnically diverse population-based, primary care and memory clinical cohorts that are deeply phenotyped and have long-term followup data available. Using state-of-the-art machine learning approaches, we will define, validate and implement accessible and cost-effective AD biomarkers for personalized diagnostic and prognostic work-up, and to facilitate development of disease modifying treatments in AD. We will develop tools in close communication with patient organizations, to ensure that we meet the needs of the affected individuals and their proxies. We will also work closely together with both diagnostics and pharma industry, as well as clinical decision-makers, to facilitate the implementation. By revolutionizing the diagnostic work-up and improving participant selection and monitoring for clinical trials, the personalized medicine approach developed in EDAP-AD will meet the challenges posited by AD.