AI is moving from hypothesis generation toward actionable biomedical outputs. Google announced a large foundation model that proposed a novel cancer drug combination which the company validated experimentally, signaling maturation of generative models for medicinal chemistry. In parallel the Chan Zuckerberg Initiative expanded its Virtual Cells Platform with NVIDIA to scale data processing, models, and benchmarks—efforts that underpin community access to large‑scale biological simulations and datasets. Both developments point to industry moves to pair high‑capacity compute, large biological datasets and foundational models to speed target identification, compound design, and mechanistic modeling, while raising questions about reproducibility, data governance, and deployment to translational pipelines.