The network is generated with the Cytoscape.js graph theory library for visualization and analysis . Therefore, users can also play around the LPI network with the graphical interface to better understand the results and can download the LPIn visualization as a SVG image. AlzyFinder is the first free and open access online server that allows virtual screening using machine learning models against key proteins in Alzheimer's disease, and presents the results dynamically, so that users can perform their analysis quickly and effectively. The results can be downloaded in multiple formats (images and data) so that users can continue their analysis independently. In this case study, we can observe that by performing the virtual screening of the molecules described in Figure , AlzyFinder was able to accurately predict (with a probability greater than 0.70) all five molecules as true positives (Table ). Finally, for users who wish to screen more than 100 molecules, the AlzyFinder GitHub repository () provides all the machine learning models, their validations, and a script to perform the screening locally. The availability of these resources as open access is vital for the scientific community, as it facilitates the reproducibility of studies, fosters collaboration, and accelerates the discovery of new drugs. By offering free access to the necessary models and tools, AlzyFinder democratizes the virtual screening process and enhances researchers' ability to explore potential new therapies efficiently and effectively. This accessibility is particularly important in researching complex diseases like Alzheimer's, where collaboration and knowledge sharing are essential to advancing our understanding and treatment of the disease.