Cancer Immunology & Prevention

Optimizing checkpoint efficacy by combining with targeted agents

Current immune-oncology research is focused on a limited number of checkpoint targets. Identification of new targets that improve the efficacy when combined with approved checkpoint antibodies would represent an important cancer treatment advance.

How will your solution make a difference

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.

What is your proposed solution

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.


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Idea No. 771