Computational modeling of immune cell phenotypes enhances prediction of clinical anti-cancer drug response

Preclinical cancer model systems, such as large-scale drug screens in cancer cell lines, are pivotal for identifying drug-sensitive indications and biomarkers of drug efficacy. However, these systems often lack the tumor microenvironment’s complexity, including interactions with immune cells, which play a critical role in modulating drug response. Investigating drug-induced effects on immune cells is experimentally challenging due to the diversity of immune cell types and the complexity of co-culture systems. Computational models of immune cells can help to overcome these limitations, to guide further experiments and to give complementary information.