This webinar shows how we enable identification and prioritization of a novel drug target—MUC16—using data from The Cancer Genome Atlas (TCGA), all without requiring deep bioinformatics expertise. The analyst shows how to mine frequently mutated genes across solid tumors, filter for druggable targets based on subcellular localization and extracellular domain structure and evaluate mutation prevalence and protein context. MUC16 emerged as a compelling candidate, particularly in pancreatic adenocarcinoma, where mutations and high expression levels correlated with poorer patient survival. Despite its relevance, few clinical trials currently target MUC16 in this disease, revealing a potentially untapped therapeutic niche. Network analysis and in silico perturbation simulations further suggested that modulating MUC16 expression could meaningfully influence oncogenic pathways. The session concluded by encouraging attendees to explore digital services and underscoring the speed and accessibility of tools for hypothesis generation and target validation.