A study published in Cell Reports Medicine reports a scalable, data-driven computational framework for designing combinatorial immunotherapies, offering hope for patients with poor responses to current immunotherapies.

Immunotherapy, particularly immune checkpoint blockade (ICB), has revolutionized cancer treatment. Widespread resistance to ICB is a major challenge in clinical practice.

To enhance treatment efficacy and overcome resistance, combining ICB therapy with chemotherapy or targeted therapy has become an important research direction. However, candidate combinations rely on empirical selection from existing drugs, and it is difficult to discover new candidates.