While checkpoint inhibitors as monotherapies have fulfilled expectations in some indications, novel combinations are on the horizon in a broader range of cancers says GlobalData, a leading data and analytics company.

The company’s latest report, ‘Immuno-oncology: Focus on Development and Opportunities in Immune Checkpoint Modulators’, reveals that developers are investigating new checkpoint targets to overcome some of the limitations that immune checkpoint inhibitors (ICIs) experience in the majority of tumor types.

Ufuk Ezer, Oncology Analyst at GlobalData, says: “Primary and secondary resistance to ICIs is a tremendous drawback to this drug class, however, there is a growing optimism for novel checkpoints, and developing effective combinations of multiple checkpoint modulatorscould help overcome some of these limitations.”

GlobalData further elaborates on the trend in combination therapies and the move toward earlier treatment settings in multiple tumor types.

Ezer continues: “Developers have realized the immediate-return opportunity in the ICI-based combinations, particularly with targeted therapies. This realization is shaping development strategies in certain indications, and increasingly in the earlier treatment setting. Combinations of multiple checkpoint modulators and other types of immunotherapies are expected to gradually emerge for niche patient populations and cancers that are traditionally known to lack the desired response to ICIs.”

There are major challenges in the development of checkpoint modulators, which are mainly interlinked with the discovery and implementation of robust biomarkers.

Ezer concludes “The development of safer and more effective checkpoint modulator-based combinations requires reliable biomarkers. In addition to tumor and site-agnostic biomarkers that would be shared in multiple tumor types such as mismatch repair deficiency (dMMR) or microsatellite instability (MSI) status, biomarkers that would enable identification of niche patient populations and segment them according to their likelihood of benefit or risk from treatment, would ultimately make checkpoint modulators more personalized.”