BostonGene unveils AI foundation models to predict immunotherapy response and toxicity
Dr. Michael Goldberg presents multimodal AI architecture at 22nd RadMed Symposium today.
BostonGene, a leader in AI-driven tumor and immune biology, is participating in the 22nd Annual Industry/Academia Precision Oncology & RadMed Symposium on June 11, 2026. Dr. Michael F. Goldberg, VP of R&D, will present the company’s latest AI foundation models designed to decode the complex tumor-immune interface. These models integrate multimodal data—including genomics, transcriptomics, and pathology—to better predict how patients will respond to immunotherapy and whether they may experience toxic side effects. The presentation highlights a major step toward leveraging advanced AI architecture for precision immuno-oncology.
By combining diverse data types into a unified foundation model, BostonGene aims to improve treatment selection and reduce adverse events. This approach moves beyond single-modal analyses, offering a more holistic view of the tumor microenvironment and immune system interactions. The technology could ultimately help oncologists personalize immunotherapy regimens, potentially improving outcomes for patients with various cancers. BostonGene’s work underscores the growing role of AI in transforming cancer care from a one-size-fits-all model to a truly data-driven, individualized strategy.
- BostonGene is presenting AI foundation models at the 22nd Annual RadMed Symposium on June 11, 2026.
- Dr. Michael F. Goldberg will discuss integrating multimodal oncology and immunology data to predict immunotherapy response and toxicity.
- The models aim to decode the tumor-immune interface, enabling more precise treatment decisions in immuno-oncology.
Why It Matters
AI foundation models that predict immunotherapy outcomes could revolutionize personalized cancer treatment and reduce harmful side effects.