The new approach marks a major step forward in the design of AI tools to support clinical decisions in cancer diagnosis, therapy. The model uses features of a tumor’s microenvironment to forecast how a patient might respond to therapy and to help inform individualized treatments. The model can expedite the identification of patients not likely to benefit from standard treatments used in some forms of cancer.