CASE STUDY

Identifying subpopulations for a personalized treatment

Learn how this immune-oncology research team gained an easy visualization of complex scRNA-seq data to support patient stratification decisions within their clinical trials programs, allowing the study to reflect the population that would benefit the most from an innovative therapy.

The Clarivate Bioinformatics Consulting team helped the researchers by applying single-cell RNA sequencing (scRNA-seq) and CITE-sequencing analysis techniques to identify immune cell populations with an increased expression level of a particular target, and identify patient subpopulations in which its drug may overcome resistance to checkpoint inhibitor therapy.