On February 10, 2026, Isomorphic Labs unveiled the Isomorphic Labs Drug Design Engine (IsoDDE), a unified computational system that more than doubles the accuracy of AlphaFold 3 in protein-ligand structure prediction for novel systems and surpasses gold-standard physics-based methods in binding affinity estimation. This milestone does not emerge in isolation: it represents the culmination of a vertically integrated artificial intelligence ecosystem built by Google DeepMind and Isomorphic Labs—spanning AlphaFold for structural biology, AlphaMissense for coding variant pathogenicity, and AlphaGenome for non-coding regulatory variant interpretation—that collectively promises to transform how we discover and develop cancer therapeutics. This editorial examines IsoDDE’s capabilities in the context of this ecosystem, argues that its demonstrated capacity to model induced fit and cryptic pocket dynamics suggests the emergence of implicit world models in molecular prediction, and discusses the profound implications for oncology: from reclassifying variants of uncertain significance to rationally designing drugs against historically undruggable targets. While significant translational challenges remain, the convergence of these technologies heralds a paradigm shift from empirical to computational-first drug discovery in oncology.