Drug repurposing is a state-of-the-art pipeline that expands pharmaceutical research and development portfolia. Despite computational tools are rapidly advancing, they predominantly rely on the examination of textual (1D) data. Herein, we present Cloudscreen ®, a "one-stop-shop" platform for drug repurposing, which seamlessly integrates 3D (structural data through predictive protein-ligand modeling) and 1D data alongside state-of-the-art machine learning algorithms. Our platform leverages a knowledge graph database, curated from diverse sources, including publicly available repositories and databases coupled to in-house computations. We are harnessing the power of artificial intelligence to predict and assess the efficacy and safety of repurposed biomolecules for novel therapeutic indications while interrogating the human variome. Moreover, Cloudscreen ® expands such prediction capabilities based on AlphaFold models, ADMETox and pharmacogenomics (emphasis on missense variants). Cloudscreen ® is a powerful tool that results from the synergy of wet- and dry-lab validated datasets and hence, provides “one-stop-shop” predictive insights into the uncharted therapeutic possibilities for repurposed drugs.