Foundation Models for Translational Cancer Biology
Published in Annual Reviews, 2025
Cancer remains a leading cause of death globally. The complexity and diversity of cancer-related datasets across different specialties pose challenges in refining precision medicine for oncology. Foundation models offer a promising solution. Trained on vast amounts of data, these models develop a broad understanding across a wide range of tasks. We examine the role of foundation models in domains relevant to cancer research, including natural language processing, computer vision, molecular biology, and cheminformatics.
Recommended citation: Tsang, Kevin K., Kivelson, Sophia, Acitores Cortina, Jose M., Kuchi, Aditi, Berkowitz, Jacob S., Liu, Hongyu, Srinivasan, Apoorva, Friedrich, Nadine A., Fatapour, Yasaman, Tatonetti, Nicholas P. Foundation Models for Translational Cancer Biology, Annual Review of Biomedical Data Science, Volume 8, 2025, https://doi.org/10.1146/annurev-biodatasci-103123-095633
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