In this episode of SciBud, join your host Maple as we uncover a groundbreaking advancement in cancer treatment: the introduction of the single-cell Adaptive Transfer and Distillation model, or scATD. This sophisticated framework leverages AI and pre-trained large language models to predict drug resistance at the individual cell level, a critical challenge in oncology. Discover how scATD overcomes limitations of traditional approaches by utilizing transfer learning, ultimately providing faster and more accurate insights into treatment responses for patients. We’ll discuss its innovative components that enhance predictive capabilities while maintaining interpretability, as well as explore both the strengths and potential limitations of this exciting research. Tune in to find out how this breakthrough might pave the way for personalized cancer therapies and why understanding single-cell responses is crucial for the future of medicine. Link to episode page with article citation: www.scibud.media/podcast/season/2025/episode/27