SandboxAQ is advancing AI-driven drug discovery with Large Quantitative Models (LQMs) that combine AI with physics-based methods to help teams move faster and make better decisions from target identification and hit finding through hit-to-lead, lead optimization, and clinical translation. SandboxAQ integrates target discovery, structure- and activity-based drug design, and biomarker discovery in adaptive workflows spanning small molecules, antibodies, and other biologics. Its biomedical knowledge graphs connect biology, chemistry, literature, omics, and clinical data to uncover causal relationships, prioritize targets, and identify biomarkers that strengthen translational and clinical development strategies. SandboxAQ works with leading pharma, biotech, academic, and nonprofit partners, including Sanofi, UCSF, Roche, Riboscience, and iOncologi, with additional collaborations supported by the Michael J. Fox Foundation and KU Leuven.