Our client’s requirement
Our client is a large pharmaceutical company based in the United States. One of its research teams is seeking potential new treatments for non-small-cell lung cancer and is engaged in identifying appropriate biomarkers to help design effective clinical trials.
The identification process requires a thorough survey and analysis of existing NSCLC clinical trial data. The data needs to be extracted from a wide library of literature and consistently structured before analysis. This process demands significant time and resources, so the client engaged Excelra to execute the survey, extract the data, and deliver a comprehensive analysis.
The client asked us for a detailed report on clinical studies with checkpoint inhibitors for NSCLC that target PD-L1 or PD-1. The report also needed to include a detailed review of the inhibitors’ potential benefits within four different lines of therapy: naïve patients, first-line therapy, second-line therapy, and third-line therapy.
To meet the client’s requirements, we developed a text-mining algorithm to identify relevant literature. Once the algorithm had delivered an exhaustive list, our scientists manually curated, annotated, and analyzed the information, delivering a refined list to the client.