Deep learning for predicting patient drug response by transferring gene-level and cell-level knowledge to tumors (opens in new tab)

Prediction of patient-level drug response is critical for precision oncology but remains limited by the scarcity of clinical data. While machine learning models trained on cell lines offer a scalable alternative, biological differences introduce domain shifts that hinder direct translation to patient tumors. Here, we present THERAPI (Tumor Heterogeneity-aware Embedding for Response Adaptation and Patient Inference), a deep learning framework designed to bridge this gap. First, THERAPI aligns ...