Optimizing checkpoint efficacy by combining with targeted agents

Translation of a well understood spectrum of in vivo predictive models to studies in the clinical setting would aid the field in understanding how best to predict and represent clinical activity through nonclinical research in Immuno-oncology.

Choosing a model to study tumor/immune system interactions is complicated by the diversity and characteristics of in vivo models (i.e. syngeneic, GEMM, humanized models ). Clinically-relevant combination strategies can be found by use of a matrix of models in a systematic and unbiased approach. Kinase inhibitors are a proven drug class and are promising candidates as combinatorial agents to be studied in the systematic manner suggested here.