Benchmarking community drug response prediction models: datasets, models, tools, and metrics for cross-dataset generalization analysis

Deep learning and machine learning models have shown promise in drug response prediction (DRP), yet their ability to generalize across datasets remains an open question, raising concerns about their real-world applicability. Due to the lack of standardized benchmarking approaches, model evaluations and comparisons often rely on inconsistent datasets and evaluation criteria, making it difficult to assess true predictive capabilities. In this work, we introduce a benchmarking framework for evaluating cross-dataset prediction generalization in DRP models. Our framework incorporates five publicly available drug screening datasets, seven standardized DRP models, and a scalable workflow for systematic evaluation. To…

• UD
  U.S. Department of Energy

  Award: ACO22002-001-00000
• NI
  National Institutes of Health

  Award: 75N91019F00134
• NC
  National Cancer Institute