Researchers have developed CRISP, a novel transfer learning framework that predicts drug perturbation responses in previously untested cell types at single-cell resolution. This approach addresses a vital challenge in drug repurposing and precision medicine by leveraging cell-specific transcriptomic data to forecast therapeutic outcomes. CRISP's capabilities promise to improve drug efficacy predictions and accelerate translational research across diverse biological systems.